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Journal Cover Control Engineering Practice
  [SJR: 1.245]   [H-I: 67]   [34 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0967-0661
   Published by Elsevier Homepage  [2801 journals]
  • Advanced decision control system for effluent violations removal in
           wastewater treatment plants
    • Abstract: Publication date: Available online 29 January 2016
      Source:Control Engineering Practice
      Author(s): I. Santín, C. Pedret, R. Vilanova, M. Meneses
      This paper presents the application of control strategies for wastewater treatment plants with the goal of effluent limits violations removal as well as achieving a simultaneous improvement of effluent quality and reduction of operational costs. The evaluation is carried out with the Benchmark Simulation Model No. 2. The automatic selection of the suitable control strategy is based on risk detection of effluent violations by Artificial Neural Networks. Fuzzy Controllers are implemented to improve the denitrification or nitrification process based on the proposed objectives. Model Predictive Control is applied for the improvement of dissolved oxygen tracking.


      PubDate: 2016-02-01T15:16:35Z
       
  • Iterative learning control of a drop foot neuroprosthesis —
           Generating physiological foot motion in paretic gait by automatic feedback
           control
    • Abstract: Publication date: March 2016
      Source:Control Engineering Practice, Volume 48
      Author(s): Thomas Seel, Cordula Werner, Jörg Raisch, Thomas Schauer
      Many stroke patients suffer from the drop foot syndrome, which is characterized by a limited ability to lift the foot and leads to a pathological gait. We consider treatment of this syndrome via Functional Electrical Stimulation (FES) of the peroneal nerve during the swing phase of the paretic foot. We highlight the role of feedback control for addressing the challenges that result from the large individuality and time-variance of muscle response dynamics. Unlike many previous approaches, we do not reduce the control problem to the scalar case. Instead, the entire pitch angle trajectory of the paretic foot is measured by means of a 6D Inertial Measurement Unit (IMU) and controlled by an Iterative Learning Control (ILC) scheme for variable-pass-length systems. While previously suggested controllers were often validated for the strongly simplified case of sitting or lying subjects, we demonstrate the effectiveness of the proposed approach in experimental trials with walking drop foot patients. Our results reveal that conventional trapezoidal stimulation intensity profiles may produce a safe foot lift, but often at the cost of too high intensities and an unphysiological foot pitch motion. Starting from such conservative intensity profiles, the proposed learning controller automatically achieves a desired foot motion within one or two strides and keeps adjusting the stimulation to compensate time-variant muscle dynamics and disturbances.


      PubDate: 2016-01-21T20:53:39Z
       
  • Kalman filter for adaptive learning of look-up tables with application to
           automotive battery resistance estimation
    • Abstract: Publication date: March 2016
      Source:Control Engineering Practice, Volume 48
      Author(s): Björn Fridholm, Torsten Wik, Magnus Nilsson
      In online automotive applications, look-up tables are often used to model nonlinearities in component models that are to be valid over large operating ranges. If the component characteristics change with ageing or wear, these look-up tables must be updated online. Here, a method is presented where a Kalman filter is used to update the entire look-up table based on local estimation at the current operating conditions. The method is based on the idea that the parameter changes observed as a component ages are caused by physical phenomena having effect over a larger part of the operating range that may have been excited. This means that ageing patterns at different operating points are correlated, and these correlations are used to drive a random walk process that models the parameter changes. To demonstrate properties of the method, it is applied to estimate the ohmic resistance of a lithium–ion battery. In simulations the complete look-up table is successfully updated without problems of drift, even in parts of the operating range that are almost never excited. The method is also robust to uncertainties, both in the ageing model and in initial parameter estimates.


      PubDate: 2016-01-21T20:53:39Z
       
  • Fractional order PI control applied to level control in coupled two tank
           MIMO system with experimental validation
    • Abstract: Publication date: Available online 19 January 2016
      Source:Control Engineering Practice
      Author(s): Prasanta Roy, Binoy Krishna Roy
      Often in a coupled two tank MIMO system, the level of the first tank is required to be kept at a constant level while the level of the second tank is required to follow a time varying reference signal. Sometimes controllers of the PID family along with conventional feedforward controllers may not be able to maintain the constant level in the first tank rejecting the disturbance due to the change in the level of the second tank without deteriorating the tracking performance of the level of the second tank. This paper shows analytically as well as experimentally that Fractional Order Proportional Integral (FOPI) controllers along with conventional feedforward controllers work better than PI/PID/2DOF-PI/3DOF-PI with feedforward controllers in such situation. FOPI controller is designed using the frequency domain approach. Effectiveness of the controllers is tested to maintain a constant level in the first tank while making the level of the second tank to follow a sinusoidal and square wave reference signals. Experimental results validate the objective of the paper.


      PubDate: 2016-01-21T20:53:39Z
       
  • Sensor runout compensation in active magnetic bearings via an integral
           adaptive observer
    • Abstract: Publication date: Available online 13 January 2016
      Source:Control Engineering Practice
      Author(s): S. Mahdi Darbandi, Alireza Habibollahi, Mehdi Behzad, Hassan Salarieh, Hamid Mehdigholi
      Sensor runout is one of the main sources of harmonic disturbances in active magnetic bearing systems. This type of the disturbance not only causes harmonic vibrations in the system but also changes the steady-state position of the axis of rotation from the geometric center of the AMB. In this paper, an integral adaptive observer is proposed to identify the dc and harmonic content of the sensor runout and to estimate the states of the system at the same time. The Lyapunov method is used to prove asymptotic stability of the proposed observer. Unlike the proportional observer which amplifies the measurement error, the sensor runout can be completely compensated when the states of the integral adaptive observer are used for feedback stabilization. It is shown that the proposed technique can also attenuate rotor displacements, when both sensor runout and mass unbalance disturbances are applied to the system. Simulation results have been presented for both cases to demonstrate the performance of the integral adaptive observer. Experimental results are also obtained by an AMB test rig, which confirm the effectiveness of the proposed method.


      PubDate: 2016-01-13T20:33:24Z
       
  • LPV model development and control of a solution copolymerization reactor
    • Abstract: Publication date: Available online 8 January 2016
      Source:Control Engineering Practice
      Author(s): Sandy Rahme, Hossam S. Abbas, Nader Meskin, Roland Tóth, Javad Mohammadpour
      In this paper, linear parameter-varying (LPV) control is considered for a solution copolymerization reactor, which takes into account the time-varying nature of the parameters of the process. The nonlinear model of the process is first converted to an exact LPV model representation in the state-space form that has a large number of scheduling variables and hence is not appropriate for control design purposes due to the complexity of the LPV control synthesis problem. To reduce such complexity, two approaches are proposed in this paper. First, an approximate LPV representation with only one scheduling variable is obtained by means of a parameter set mapping (PSM). The second approach is based on reformulating the nonlinear model so that it provides an LPV model with a fewer number of scheduling parameters but preserves the same input–output behavior. Moreover, in the implementation of the LPV controllers synthesized with the derived models, the unmeasurable scheduling variables are estimated by an extended Kalman filter. Simulation results using the nonlinear model of the copolymerization reactor are provided in order to illustrate the performance of the proposed controllers in reducing the convergence time and the control effort.


      PubDate: 2016-01-09T20:19:49Z
       
  • A fault detection scheme based on minimum identified uncertainty bounds
           violation for broken rotor bars in induction motors
    • Abstract: Publication date: March 2016
      Source:Control Engineering Practice, Volume 48
      Author(s): Mohammed Obaid Mustafa, George Nikolakopoulos, Thomas Gustafsson, Dariusz Kominiak
      In this paper, a novel method for broken bars fault detection in the case of three-phase induction motors and under different payloads will be presented and experimentally evaluated. In the presented approach, the cases of a partially or full broken rotor bars are being also considered, caused by: (a) drilling 4mm and 8mm out of the 17mm thickness of the same rotor bar and (b) fully drilled (17mm) one, two and three broken bars. The proposed fault detection method is based on the Set Membership Identification (SMI) technique and a novel proposed minimum boundary violation fault detection scheme, applied on the identified motor's parameters. The system identification procedure is being carried out on the simplified equivalent model of the induction motor, during the steady-state operation (non-fault case), while at the same time the proposed scheme is able to calculate on-line the corresponding safety bounds for the identified variables, based on a priori knowledge of the measuring corrupting noise (worst case encountered). The efficiency, the robustness and the overall performance of the established fault detection scheme is being extensively evaluated in multiple experimental studies and under various time instances of faults and load conditions.


      PubDate: 2016-01-09T20:19:49Z
       
  • Bond Graph modeling for fault detection and isolation of a train door
           mechatronic system
    • Abstract: Publication date: Available online 4 January 2016
      Source:Control Engineering Practice
      Author(s): Laurent Cauffriez, Sébastien Grondel, Pierre Loslever, Christophe Aubrun
      In this paper, monitoring and diagnosis of a new generation of train door mechatronic system is proposed. Bond Graph methodology is applied to obtain a reference model. In addition to this reference model, a global model based-FDI (Fault Diagnostic and Isolation) is developed for the generation of fault indicators and residual thresholds in presence of door failures. The ability of the proposed diagnostic approach to detect train door failures is demonstrated. The main contribution of this paper concerns the implementation of FDI procedure on a train door instead of health monitoring as it is usually performed in maintenance field.


      PubDate: 2016-01-05T20:06:24Z
       
  • A revised Durbin-Wu-Hausman test for industrial robot identification
    • Abstract: Publication date: March 2016
      Source:Control Engineering Practice, Volume 48
      Author(s): Alexandre Janot, Pierre-Olivier Vandanjon, Maxime Gautier
      This paper addresses the topic of robot identification. The usual identification method makes use of the inverse dynamic model (IDM) and the least squares (LS) technique while robot is tracking exciting trajectories. Assuming an appropriate bandpass filtering, good results can be obtained. However, the users are in doubt whether the columns of the observation matrix (the regressors) are uncorrelated (exogenous) or correlated (endogenous) with the error terms. The exogeneity condition is rarely verified in a formal way whereas it is a fundamental condition to obtain unbiased LS estimates. In Econometrics, the Durbin-Wu-Hausman test (DWH-test) is a formal statistic for investigating whether the regressors are exogenous or endogenous. However, the DWH-test cannot be straightforwardly used for robot identification because it is assumed that the set of instruments is valid. In this paper, a Revised DWH-test suitable for robot identification is proposed. The revised DWH-test validates/invalidates the instruments chosen by the user and validates the exogeneity assumption through the calculation of the QR factorization of the augmented observation matrix combined with a F-test if required. The experimental results obtained with a 6 degrees-of-freedom (DOF) industrial robot validate the proposed statistic.


      PubDate: 2016-01-05T20:06:24Z
       
  • Determining the propagation path of a disturbance in multi-rate process
           and electromechanical systems
    • Abstract: Publication date: Available online 5 January 2016
      Source:Control Engineering Practice
      Author(s): Inês M. Cecílio, James R. Ottewill, Nina F. Thornhill
      This paper proposes a multi-rate method to identify the propagation path of a persistent disturbance in an enlarged system envelope which includes the process plant and its electromechanical equipment. The need to integrate process and equipment diagnosis has been highlighted by industrial commentators. However, process and electromechanical measurements often have different sampling rates. The multi-rate method proposed extends a state-of-the-art propagation path method so that it combines fast-sampled electromechanical measurements and slow-sampled process measurements. The method is based on non-linear mutual prediction, which yields the directionality in the relationship between two time series. The method was demonstrated and validated, giving the expected outcome in an experimental case study, in which the root cause and propagation path of the disturbance were known.


      PubDate: 2016-01-05T20:06:24Z
       
  • Explicit MPC: Hard constraint satisfaction under low precision arithmetic
    • Abstract: Publication date: Available online 29 December 2015
      Source:Control Engineering Practice
      Author(s): Andrea Suardi, Stefano Longo, Eric C. Kerrigan, George A. Constantinides
      MPC is becoming increasingly implemented on embedded systems, where low precision computation is preferred either to reduce costs, speedup execution or reduce power consumption. However, in a low precision implementation, constraint satisfaction cannot be guaranteed. To enforce constraint satisfaction under numerical errors, we adopt tools from forward error analysis to compute an error bound on the output of the embedded controller. We treat this error as a state disturbance and use it to inform the design of a constraint-tightening robust controller. The technique is validated via a practical implementation on an FPGA evaluation board.


      PubDate: 2016-01-02T10:39:12Z
       
  • Frequency-domain iterative learning control of a marine vibrator
    • Abstract: Publication date: Available online 30 December 2015
      Source:Control Engineering Practice
      Author(s): Olof Sörnmo, Bo Bernhardsson, Olle Kröling, Per Gunnarsson, Rune Tenghamn
      To the purpose of marine seismic acquisition, new acoustic sources have been developed to reduce the environmental impact. The use of marine vibrators makes it possible to define emission frequency ranges, consequently allowing limitation of the frequencies that disturb marine animal life. Constructing marine vibrators with high efficiency and linear dynamics is however difficult, and the vibrators suffer from both friction, backlash and high-order harmonics. These nonlinear effects, in combination with drifting dynamics, make the required control a crucial and challenging problem. This paper presents a model-based iterative learning control solution, performed in the frequency-domain. Additionally, an adaptive reidentification algorithm is developed to cope with drifting dynamics. The proposed solutions are successfully evaluated in experiments with a marine vibrator.


      PubDate: 2016-01-02T10:39:12Z
       
  • Wind turbine performance analysis based on multivariate higher order
           moments and Bayesian classifiers
    • Abstract: Publication date: Available online 29 December 2015
      Source:Control Engineering Practice
      Author(s): Jürgen Herp, Niels L. Pedersen, Esmaeil S. Nadimi
      A data-driven model based on Bayesian classifiers and multivariate analysis of the power curve (wind speed vs. power) for monitoring wind farms' performance is presented. A new outlier detection criterion and various control bounds on the skewness and kurtosis of the data for cluster separation and classification of turbines' faulty and normal state of operation are introduced. Further continuous monitoring is addressed with Hotelling's T 2 and Bayesian network approaches, and it is proven that under certain conditions, the outcomes of these two methods are equivalent. The Bayesian approach, however addresses the likelihood of classification, making supervised controls more flexible.


      PubDate: 2016-01-02T10:39:12Z
       
  • Performance analysis of an energy-efficient variable supply pressure
           electro-hydraulic motion control system
    • Abstract: Publication date: March 2016
      Source:Control Engineering Practice, Volume 48
      Author(s): C. Du, A.R. Plummer, D.N. Johnston
      The electro-hydraulic motion control is implemented in diverse applications due to its high power density and good controllability. For a multi-axis system with a single power source, the conventional fixed supply pressure valve-controlled (FPVC) system is a simple but inefficient method due to its dissipating energy via the throttling valves. In this paper, a load-prediction based energy-efficient variable supply pressure valve-controlled (VPVC) method was introduced and implemented on a two-axis robotic arm system. The VPVC system adopts a fixed capacity pump driven by a brushless servomotor. The feed forward part of the VPVC controller predicts the minimum required supply pressure of the system by assuming the control valve of the highest load branch fully open. It is based on the prediction of the required actuation force for a given motion demand, by applying Lagrange's equations of the-second-kind. The feedback control of VPVC is classic proportional (integral) control for the control valves and the motor speed, with measured actuator positions as the feedback signals. Although the VPVC algorithm was demonstrated for a two-axis robotic arm system here, it is applicable to the systems with any number of axes. By using the variable minimum supply pressure together with the maximum valve opening, the energy-efficiency of VPVC is improved compared with a FPVC system. Moreover, due to the feed forward part in VPVC, the dynamic response is much better than a FPVC system with proportional integral position feedback control. The comparison between FPVC and VPVC validated these advantages. The hydraulic power consumption comparison showed that up to 70% saving was achieved by VPVC over FPVC experimentally. If the energy loss via relief valve in FPVC is taken into account, the saving can be increased greatly. In all the comparison tests, the dynamic errors in VPVC were smaller than in FPVC (both were with constant proportional-integral controllers setting). The experimental dynamic errors of VPVC were within 6.5% of the total motion range, compared to 14% for FPVC. And the average dynamic errors of VPVC were within 1.5% of the total motion range. The experiment also showed that the VPVC brought a very quiet operating due to the minimum flow throttling and variable motor speed, which is another significant benefit of VPVC over FPVC.


      PubDate: 2016-01-02T10:39:12Z
       
  • Road profile estimation using an adaptive Youla–Kučera
           parametric observer: Comparison to real profilers
    • Abstract: Publication date: Available online 30 December 2015
      Source:Control Engineering Practice
      Author(s): M. Doumiati, J. Martinez, O. Sename, L. Dugard, D. Lechner
      Road profile acts as a disturbance input to the vehicle dynamics and results in undesirable vibrations affecting the vehicle stability. An accurate knowledge of this data is a key for a better understanding of the vehicle dynamics behavior and active vehicle control systems design. However, direct measurements of the road profile are not trivial for technical and economical reasons, and thus alternative solutions are needed. This paper develops a novel observer, known as a virtual sensor, suitable for real-time estimation of the road profile. The developed approach is built on a quarter-car model and uses measurements of the vehicle body. The road roughness is modeled as a sinusoidal disturbance signal acting on the vehicle system. Since this signal has unknown and time-varying characteristics, the proposed estimation method implements an adaptive control scheme based on the internal model principle and on the use of Youla–Kučera (YK) parameterization technique (also known as Q-parameterization). For performances assessment, estimations are comparatively evaluated with respect to measurements issued from Longitudinal Profile Analyzer (LPA) and Inertial Profiler (IP) instruments during experimental trials. The proposed method is also compared to the approach provided in Doumiati, Victorino, Charara, and Lechner (2011), where a stochastic Kalman filter is applied assuming a linear road model. Results show the effectiveness and pertinence of the present observation scheme.


      PubDate: 2016-01-02T10:39:12Z
       
  • Modeling, diagnosis and estimation of actuator faults in vehicle
           suspensions
    • Abstract: Publication date: Available online 31 December 2015
      Source:Control Engineering Practice
      Author(s): Diana Hernández-Alcántara, Juan C. Tudón-Martínez, Luis Amézquita-Brooks, Carlos A. Vivas-López, Rubén Morales-Menéndez
      This paper deals with the modeling, diagnosis and estimation of faults in automotive Semi-Active (SA) dampers, particularly oil leakages in the actuator. An experimental multiplicative fault model is proposed and statistically validated with an index error of 15% for damper leakage. The fault model is used as design basis for two Fault Detection and Isolation (FDI) frameworks. The Frequency-based Fault Estimator (FFE) is based on the effect of the damper fault in the frequency domain and the Robust Parity Space (RPS) consists in a residual generator sensitive to the fault in the time domain. The model-based FDI systems were experimentally validated in a 1:5 scaled vehicle, fully instrumented and equipped with SA dampers. The experimental results show that, while both approaches represent suitable options for commercial applications, the RPS estimator has the fastest detection time and proportionality to the fault level. In addition, the RPS approach has better robustness to vehicle mass uncertainties. On the other hand, the FFE presents lower sensitivity to road profile and semi-active damper input variations. Additionally, this estimator requires a lower number of sensors and has a lower computational overhead.


      PubDate: 2016-01-02T10:39:12Z
       
  • Parametric sensitivity and control of on-orbit manipulators during impacts
           using the Centre of Percussion concept
    • Abstract: Publication date: February 2016
      Source:Control Engineering Practice, Volume 47
      Author(s): Iosif S. Paraskevas, Evangelos G. Papadopoulos
      During capture of a free-flying object, a robotic servicer can be subject to impacts, which may separate it from the object or damage crucial subsystems. However, the reactions can be minimized using the Centre of Percussion (CoP) concept. Following a brief introduction of the two- and three-dimensional cases, the performance of a robot under impact is assessed when the CoP concept is employed. The effects of the parametric uncertainties on manipulator joint reactions are studied. Α control method to compensate for the reaction forces is proposed. Implementation guidelines are discussed. Simulations of a planar space robot validate the analysis.


      PubDate: 2016-01-02T10:39:12Z
       
  • Integrated torque vectoring and power management framework for electric
           vehicles
    • Abstract: Publication date: March 2016
      Source:Control Engineering Practice, Volume 48
      Author(s): Andy Wong, Dhanaraja Kasinathan, Amir Khajepour, Shih-Ken Chen, Bakhtiar Litkouhi
      An integrated vehicle control framework is presented, which uses torque vectoring across independently driven wheels for control. The approach is general in nature, but is particularly well suited for electric vehicles due to increased control bandwidth. The novel algorithm optimizes wheel torque outputs in real time, constraining against power management, traction control, chassis configuration, actuator limits, and fault-case limitations. The structure is modular, and designed to adapt for differing vehicles with minimal re-tuning. Simulation and experimental results are provided for a modified electric SUV platform, under a range of dynamic maneuvers in 4WD, FWD, and RWD modes.


      PubDate: 2016-01-02T10:39:12Z
       
  • Least costly energy management for series hybrid electric vehicles
    • Abstract: Publication date: March 2016
      Source:Control Engineering Practice, Volume 48
      Author(s): Simone Formentin, Jacopo Guanetti, Sergio M. Savaresi
      Energy management of plug-in hybrid electric vehicles (HEVs) has different challenges from non-plug-in HEVs, due to bigger batteries and grid recharging. Instead of tackling it to pursue energetic efficiency, an approach minimizing the driving cost incurred by the user – the combined costs of fuel, grid energy and battery degradation – is here proposed. A real-time approximation of the resulting optimal policy is then provided, as well as some analytic insight into its dependence on the system parameters. The advantages of the proposed formulation and the effectiveness of the real-time strategy are shown by means of a thorough simulation campaign.


      PubDate: 2016-01-02T10:39:12Z
       
  • Decentralized voltage control of distributed generation using a
           distribution system structural MIMO model
    • Abstract: Publication date: Available online 28 December 2015
      Source:Control Engineering Practice
      Author(s): Anna Rita Di Fazio, Giuseppe Fusco, Mario Russo
      The voltage control problem in Low Voltage (LV) distribution systems is becoming increasingly important due to the presence of Distributed Generation (DG). Recently, DG units have been proposed to contribute to voltage control according to a Volt/Var law which does not realize regulation. Moreover, since the existing LV systems are operated in a decentralized way without communication links, the simultaneous response of the controllers of the DG units may result into operational conflicts and instability. To overcome these problems, the present paper illustrates a design methodology for decentralized voltage controllers that act on DG reactive power injections. The controllers are suitable for the LV systems since they ensure voltage regulation and stability by using only local measurements and without information exchanges. The design is based on a proposed structural MIMO model of the distribution system. Robust stability is also analyzed: changes in the operating conditions of the distribution system are modeled as unstructured additive uncertainties affecting the MIMO model. A case study gives evidence of the applicability of the proposed design; the performance of the controllers in terms of both stability and regulation of the nodal voltages of three DG units connected to a LV distribution feeder is tested by numerical simulations; finally, a comparison with a Volt/Var technique is performed.


      PubDate: 2015-12-29T10:33:48Z
       
  • Overshoot-free acceleration of aero-engines: An energy-based switching
           control method
    • Abstract: Publication date: February 2016
      Source:Control Engineering Practice, Volume 47
      Author(s): Xia Wang, Jun Zhao, Xi-Ming Sun
      A switched controller is proposed for a two-spool turbofan engine to achieve overshoot-free speed control. Instead of a mathematical engine model, the real time data provided by the component level model and the equilibrium manifold are used in the design process. Controllers and a switching law are proposed to ensure that the system energy will not surpass the energy of the target working point so that no speed overshoot will arise. Meanwhile, the engine works at its safety limits as much as possible during the acceleration process, which shortens the regulation time. The asymptotic regulation, the overshoot-free performance as well as the safety issues are guaranteed theoretically. Simulations of a two-spool turbofan engine testify the correctness of the proposed method.


      PubDate: 2015-12-25T10:16:51Z
       
  • A methodology and a software tool for sensor data
           validation/reconstruction: Application to the Catalonia regional water
           network
    • Abstract: Publication date: Available online 21 December 2015
      Source:Control Engineering Practice
      Author(s): Miquel À. Cugueró-Escofet, Diego García, Joseba Quevedo, Vicenç Puig, Santiago Espin, Jaume Roquet
      In this paper, a sensor data validation/reconstruction methodology applicable to water networks and its implementation by means of a software tool are presented. The aim is to guarantee that the sensor data are reliable and complete in case that sensor faults occur. The availability of such dataset is of paramount importance in order to successfully use the sensor data for further tasks e.g. water billing, network efficiency assessment, leak localization and real-time operational control. The methodology presented here is based on a sequence of tests and on the combined use of spatial models (SM) and time series models (TSM) applied to the sensors used for real-time monitoring and control of the water network. Spatial models take advantage of the physical relations between different system variables (e.g. flow and level sensors in hydraulic systems) while time series models take advantage of the temporal redundancy of the measured variables (here by means of a Holt–Winters (HW) time series model). First, the data validation approach, based on several tests of different complexity, is described to detect potential invalid or missing data. Then, the reconstruction process is based on a set of spatial and time series models used to reconstruct the missing/invalid data with the model estimation providing the best fit. A software tool implementing the proposed data validation and reconstruction methodology is also described. Finally, results obtained applying the proposed methodology to a real case study based on the Catalonia regional water network is used to illustrate its performance.


      PubDate: 2015-12-25T10:16:51Z
       
  • A flywheel error compensation algorithm for engine misfire detection
    • Abstract: Publication date: February 2016
      Source:Control Engineering Practice, Volume 47
      Author(s): Daniel Jung, Erik Frisk, Mattias Krysander
      The crankshaft angular velocity measured at the flywheel is a commonly used signal for engine misfire detection. However, flywheel manufacturing errors result in vehicle-to-vehicle variations in the measurements and have a negative impact on the misfire detection performance. A misfire detection algorithm must be able to compensate for this type of vehicle-to-vehicle variations if it is to be used in production cars to assure that legislations are fulfilled. It is shown that flywheel angular variations between vehicles in the magnitude of 0.05° have a significant impact on the measured angular velocity and must be compensated for to make the misfire detection algorithm robust. A misfire detection algorithm is proposed with flywheel error adaptation in order to increase robustness and reduce the number of mis-classifications. Evaluations using measurements from a number of vehicles on the road are used to quantify the negative impact of the flywheel errors and show that the number of mis-classifications is significantly reduced when performing on-line flywheel error adaptation.


      PubDate: 2015-12-25T10:16:51Z
       
  • Robust fault estimation using an LPV reference model: ADDSAFE benchmark
           case study
    • Abstract: Publication date: Available online 24 December 2015
      Source:Control Engineering Practice
      Author(s): Lejun Chen, Ron Patton, Philippe Goupil
      This paper investigates a mixed H − / H ∞ linear parameter varying (LPV) fault estimator using an LPV reference estimator. LMIs are used to calculate the affine parameter-dependent gains of the LPV fault estimator. The design strategy is applied to a high fidelity nonlinear aircraft model provided by AIRBUS for use within the EU-FP7 project ADDSAFE, to estimate the yaw rate sensor faults in the Air Data Inertial Reference System in the presence of the parametric uncertainties. The fault detection performances in various flight conditions are evaluated using the parametric simulation.


      PubDate: 2015-12-25T10:16:51Z
       
  • Wheel loader operation—Optimal control compared to real drive
           experience
    • Abstract: Publication date: March 2016
      Source:Control Engineering Practice, Volume 48
      Author(s): V. Nezhadali, B. Frank, L. Eriksson
      Wheel loader trajectories between loading and unloading positions in a repetitive loading cycle are studied. A wheel loader model available in the literature is improved for better fuel estimation and optimal control problems are formulated and solved using it. The optimization results are analyzed in a side to side comparison with measurement data from a real world application. It is shown that the trajectory properties affect the operation productivity. However, efficient trajectories are not the only requirement for high productivity operation and all major power consuming sources such as vehicle dynamics, lifting and steering have to be included in the optimization for productivity analysis. The effect of operator steering capability is also analyzed showing that development of autonomous vehicles can be envisaged especially for repetitive cycles.


      PubDate: 2015-12-25T10:16:51Z
       
  • Model predictive load–frequency control taking into account
           imbalance uncertainty
    • Abstract: Publication date: Available online 19 December 2015
      Source:Control Engineering Practice
      Author(s): Anne Mai Ersdal, Lars Imsland, Kjetil Uhlen, Davide Fabozzi, Nina F. Thornhill
      Nonlinear model predictive control (NMPC) is investigated for load frequency control (LFC) of an interconnected power system which is exposed to increasing wind power penetration. The robustified NMPC (RNMPC) proposed here uses knowledge of the estimated worst-case deviation in wind-power production to make the NMPC more robust. The NMPC is based on a simplified system model that is updated using state- and parameter estimation by Kalman filters, and it takes into account limitations on among others tie-line power flow. Tests on a proxy of the Nordic power system show that the RNMPC is able to fulfill system constraints under worst-case deviations in wind-power production, where the nominal NMPC is not.


      PubDate: 2015-12-21T10:12:46Z
       
  • Optimizing fuel consumption and pollutant emissions of gasoline-HEV with
           catalytic converter
    • Abstract: Publication date: Available online 19 December 2015
      Source:Control Engineering Practice
      Author(s): Pierre Michel, Alain Charlet, Guillaume Colin, Yann Chamaillard, Gérard Bloch, Cédric Nouillant
      Because of more and more stringent vehicle emission standards, Hybrid Electric Vehicles (HEV) are developed. Gasoline-HEV are equipped with 3-Way Catalytic Converter (3WCC). So the energy management systems of such vehicles, which must reduce not only fuel consumption, but also vehicle pollutant emissions, have to consider the 3WCC heating. A pollutant constrained energy management strategy is presented. A 3WCC multi-0D model is built from physical equations, with a good complexity-performances compromise. An off-line optimal strategy allows the joint minimization of pollution and fuel consumption with only one parameter to tune, while considering all the standardized pollutant emissions. This strategy reduces significantly the vehicle emissions for a minor fuel consumption increase and leads to define 3WCC smart heating. Thus an on-line smart heating strategy is implemented in a HyHIL (Hybrid Hardware In the Loop) test bench, reducing the pollutant emissions of the classical charge sustaining strategy by 30% for CO and 10% for NO X .


      PubDate: 2015-12-21T10:12:46Z
       
  • Fault tolerant emergency control to preserve power system stability
    • Abstract: Publication date: Available online 10 December 2015
      Source:Control Engineering Practice
      Author(s): Andreas S. Pedersen, Jan H. Richter, Mojtaba Tabatabaeipour, Hjörtur Jóhannsson, Mogens Blanke
      This paper introduces a method for fault-masking and system reconfiguration in power transmission systems. The paper demonstrates how faults are handled by reconfiguring remaining controls through utilisation of wide-area measurement in real time. It is shown how reconfiguration can be obtained using a virtual actuator concept, which covers Lure-type systems. The paper shows the steps needed to calculate a virtual actuator, which relies on the solution of a linear matrix inequality. The solution is shown to work with existing controls by adding a compensation signal. Simulation results of a benchmark system show ability of the reconfiguration to maintain stability.


      PubDate: 2015-12-13T13:12:51Z
       
  • A novel approach for stability and transparency control of nonlinear
           bilateral teleoperation system with time delays
    • Abstract: Publication date: February 2016
      Source:Control Engineering Practice, Volume 47
      Author(s): Da Sun, Fazel Naghdy, Haiping Du
      In this paper, a novel control approach is presented to improve the stability and transparency of the nonlinear bilateral teleoperation system with time delays, where a four-channel (4-CH) architecture using modified wave reflection reduction transformation is explored in order to guarantee the passivity of the communication channels in the nonlinear bilateral teleoperation system; a sliding-mode controller is proposed to compensate for the dynamic uncertainties and enhance the system synchronization performance in finite time. The system stability has been analyzed using Lyapunov functions. The proposed method is validated through experimental work based on a 3-DOF bilateral teleoperation platform in the presence of time delays. The experimental results clearly demonstrate that the proposed control algorithm has superiority on system transparency over other wave-based systems.


      PubDate: 2015-12-09T12:57:55Z
       
  • IFC - Editorial Board / Funding body / agreements policies
    • Abstract: Publication date: December 2015
      Source:Control Engineering Practice, Volume 45




      PubDate: 2015-12-09T12:57:55Z
       
  • Nonlinear internal model controller design for wastegate control of a
           turbocharged gasoline engine
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Zeng Qiu, Jing Sun, Mrdjan Jankovic, Mario Santillo
      Internal Model Control (IMC) has a great appeal for automotive powertrain control in reducing the control design and calibration effort. Motivated by its success in several automotive applications, this work investigates the design of nonlinear IMC for wastegate control of a turbocharged gasoline engine. The IMC design for linear time-invariant (LTI) systems is extended to nonlinear systems. To leverage the available tools for LTI IMC design, the quasi-linear parameter-varying (quasi-LPV) models are explored. IMC design through transfer function inverse of the quasi-LPV model is ruled out due to parameter variability. A new approach for nonlinear inversion, referred to as the structured quasi-LPV model inverse, is developed and validated. A fourth-order nonlinear model which sufficiently describes the dynamic behavior of the turbocharged engine is used as the design model in the IMC structure. The controller based on structured quasi-LPV model inverse is designed to achieve boost-pressure tracking. Finally, simulations on a validated high-fidelity model are carried out to show the feasibility of the proposed IMC. Its closed-loop performances are compared with a well-tuned PI controller with extensive feedforward and anti-windup built in. Robustness of the nonlinear IMC design is analyzed using simulations.


      PubDate: 2015-12-05T06:21:35Z
       
  • IFC - Editorial Board / Funding body / agreements policies
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46




      PubDate: 2015-12-05T06:21:35Z
       
  • Nonsmooth H∞ synthesis of non-minimum-phase servo-systems with
           backlash
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Israel U. Ponce, Yury Orlov, Luis T. Aguilar, Joaquín Álvarez
      The nonsmooth phenomena such as backlash and Coulomb friction, often occurring in mechanical systems, typically produce undesired inaccuracies, oscillations and instability thereby degrading the system performance. The present paper addresses these phenomena in a benchmark two-mass system composed of motor and load subsystems joined by an elastic shaft. Only partial measurements of the motor position are assumed to be available. The H ∞ synthesis is then developed for a class of nonsmooth systems with backlash. The effectiveness of the proposed synthesis and its robustness features in the presence of friction forces and backlash effects are supported by an experimental study made for an industrial emulator.


      PubDate: 2015-12-05T06:21:35Z
       
  • Energy-efficient operation of diesel–electric locomotives using
           ahead path data
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): M. Saadat, M. Esfahanian, M.H. Saket
      Diesel–electric locomotives have significant fuel consumption. In this study, fuzzy look-ahead control is considered as an online approach for fuel consumption optimization. A fuzzy controller will modify the desired speed profile by accounting for the gradient and speed limits of the path ahead. Journey time increment is used as an optimization constraint. The existing models for train motion simulation are calculating the fuel consumption by an indirect index. A new model for train-movement simulation is proposed to calculate fuel consumption more accurately. This model considers the locomotive subsystems and satisfies the experimental fuel consumption data specified in the locomotive's catalog. Simulation of a train with a GM Sd40-2 on three local tracks showed considerable reduction in fuel consumption along with an acceptable journey time increment. Simulation results also showed that fuzzy look-ahead controller has very faster calculations in comparison with the controller based on the dynamic programming method.


      PubDate: 2015-12-05T06:21:35Z
       
  • Use of a quantile regression based echo state network ensemble for
           construction of prediction Intervals of gas flow in a blast furnace
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Zheng Lv, Jun Zhao, Ying Liu, Wei Wang
      The usual huge fluctuations in the blast furnace gas (BFG) generation make the scheduling of the gas system become a difficult problem. Considering that there are high level noises and outliers mixed in original industrial data, a quantile regression-based echo state network ensemble (QR-ESNE) is modeled to construct the prediction intervals (PIs) of the BFG generation. In the process of network training, a linear regression model of the output matrix is reported by the proposed quantile regression to improve the generalization ability. Then, in view of the practical demands on reliability and further improving the prediction accuracy, a bootstrap strategy based on QR-ESN is designed to construct the confidence intervals and the prediction ones via combining with the regression models of various quantiles. To verify the performance of the proposed method, the practical data coming from a steel plant are employed, and the results indicate that the proposed method exhibits high accuracy and reliability for the industrial data. Furthermore, an application software system based on the proposed method is developed and applied to the practice of this plant.


      PubDate: 2015-12-05T06:21:35Z
       
  • OBC - Autogenerate contents and barcode
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46




      PubDate: 2015-12-05T06:21:35Z
       
  • Unbalance compensation for AMB systems with input delay: An output
           regulation approach
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Se Young Yoon, Long Di, Zongli Lin
      Unbalance compensation is an important technique for reducing rotor vibration in high speed rotating machines caused by residual rotor unbalance. As rotating machines in remote applications aim for higher speeds to gain efficiency and to reduce footprint, there is a need to extend the unbalance compensation techniques to active magnetic bearing (AMB) systems with delays in the control loop. This paper investigates the unbalance compensation problem for AMB systems with input delays. An unbalance compensation method is developed based on a solution to the output regulator problem for systems with input delay. The proposed unbalance compensation method is verified through simulation, and experimentally validated on an AMB test rig.


      PubDate: 2015-12-05T06:21:35Z
       
  • Distributed MPC for frequency regulation in multi-terminal HVDC grids
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Paul Mc Namara, Rudy R. Negenborn, Bart De Schutter, Gordon Lightbody, Seán McLoone
      Multi-Terminal high voltage Direct Current (MTDC) transmission lines enable radial or meshed DC grid configurations to be used in electrical power networks, and in turn allow for significant flexibility in the development of future DC power networks. In this paper distributed MPC is proposed for providing Automatic Generation Control (AGC) in Alternating Current (AC) areas connected to MTDC grids. Additionally, a novel modal analysis technique is derived for the distributed MPC algorithm, which in turn can be used to determine the convergence and stability properties of the closed-loop system.


      PubDate: 2015-12-05T06:21:35Z
       
  • Repetitive process based design and experimental verification of a dynamic
           iterative learning control law
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Lukasz Hladowski, Krzysztof Galkowski, Weronika Nowicka, Eric Rogers
      This paper gives new results on iterative learning control (ILC) design and experimental verification using the stability theory of linear repetitive processes. Using this theory a control law can be designed in one step to force error convergence and produce acceptable transient dynamics. Previous research developed algorithms for the design of a static control law with supporting experimental verification. Should a static law not give the required levels of performance one option is to allow the control law to have internal dynamics. This paper develops a procedure for the design of such a control law with supporting experimental verification on a gantry robot, including a comparative performance against a static law applied to the same robot. The resulting ILC design is an efficient combination of linear matrix inequalities and optimization algorithms.


      PubDate: 2015-12-05T06:21:35Z
       
  • Implicit discrete-time twisting controller without numerical chattering:
           Analysis and experimental results
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Olivier Huber, Vincent Acary, Bernard Brogliato, Franck Plestan
      In this paper, we present an implementation of the sliding mode twisting controller on an electropneumatic plant for a tracking control problem. To this end, implicitly and explicitly discretized twisting controllers are considered. We discuss their structure, properties and implementations, as well as the experimental results. The analysis of the performance sustains the theoretical superiority of the implicitly discretized version, as shown in previous works. The main advantages of the implicit method are better tracking performance and drastic reduction in the input and output chattering. This is achieved without modifying the structure of the controller compared to its continuous-time version. The tracking error cannot be used as the sliding variable: it has a relative degree 3 w.r.t. the control input. The tuning of the sliding surface has well as some other parameters in the control loop was instrumental in achieving good performance. We detail the selection procedure of those parameters and their influence on the closed-loop behavior. Finally we also present some results with an implicitly discretized EBC-SMC controller.


      PubDate: 2015-12-05T06:21:35Z
       
  • The optimal design of industrial alarm systems based on evidence theory
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Xiaobin Xu, Shibao Li, Xiaojing Song, Chenglin Wen, Dongling Xu
      This paper presents a procedure for the optimal design of industrial alarm systems based on evidence theory to deal with epistemic and aleatory uncertainties of the monitored process variable. First, the upper and lower fuzzy thresholds are designed, and then the sampled value of the process variable is transformed into a piece of alarm evidence to measure the degrees of uncertainty about whether an alarm should be triggered or not by the sampled value. Second, a linear updating rule of evidence is recursively applied to combine the updated alarm evidence at t−1 step with the incoming alarm evidence at t step to generate the updated alarm evidence at t step. In the process of evidence updating, the weights of evidence for linear combination can be obtained by dynamically minimizing the distance between the updated alarm evidence and the true mode (i.e., “alarm” or “no-alarm”). An alarm decision can then be made according to a pignistic probability transformed from the updated alarm evidence at each time step. Finally, numerical experiments and an industrial case are given to show that the proposed procedure has a better performance than the classical design methods.


      PubDate: 2015-12-05T06:21:35Z
       
  • Process monitoring of iron-making process in a blast furnace with
           PCA-based methods
    • Abstract: Publication date: February 2016
      Source:Control Engineering Practice, Volume 47
      Author(s): Bo Zhou, Hao Ye, Haifeng Zhang, Mingliang Li
      Incidents happening in the blast furnace will strongly affect the stability and smoothness of the iron-making process. Thus far, diagnosis of abnormalities in furnaces still mainly relies on the personal experiences of individual workers in many iron works. In this paper, principal component analysis (PCA)-based algorithms are developed to monitor the iron-making process and achieve early abnormality detection. Because the process exhibits a non-normal distribution and a time-varying nature in the measurement data, a static convex hull-based PCA algorithm (SCHPCA) which replaces the traditional T 2-based abnormality detection logic with the convex hull-based abnormality detection logic, and its moving window version, called the moving window convex hull-based PCA algorithm (MWCHPCA) are proposed, respectively. These two algorithms are tested on the real process data to verify their effectiveness in the early abnormality detection of iron-making process.


      PubDate: 2015-12-05T06:21:35Z
       
  • Speed-sensorless control of SR motors based on GPI observers
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): A. De La Guerra, Marco A. Arteaga-Pérez, Alejandro Gutiérrez-Giles, P. Maya-Ortiz
      This paper presents a robust speed-sensorless controller based on Generalized Proportional Integral (GPI) Observers for Switched Reluctance Motors. It compensates the unknown load torque while naturally estimates the output phase variables, making unnecessary to directly measure the angular velocity. An experimental comparison of the proposed controller with two other well-known similar schemes, carried out on a three phase 12/8 SR motor, shows the good performance of the proposed scheme.


      PubDate: 2015-12-05T06:21:35Z
       
  • Optimal control strategy of working condition transition for copper flash
           smelting process
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Yong-fang Xie, Jian-hua Liu, De-gang Xu, Wei-hua Gui, Chun-hua Yang
      Because there are large state fluctuation of working conditions, excessive energy consumption caused by manual operation in the dynamic transient procedure for copper flash smelting process. Working conditions of copper flash smelting process must be adjusted to the complex and variable copper concentrate feeding to satisfy the smelting performance. Optimal control strategy based adjustment cost for copper flash smelting working condition transition is proposed, which can achieve the expected working condition by following the optimal working condition transition path. The Cauchy–Schwarz inequality-based two-level matching method is developed to set the expected working condition. Then with minimizing adjustment cost and restricting operation domain to optimize smelting performance indicators, the optimal control problem of working condition transition is converted into a multi-constraints optimization problem with two fixed ends. A Legendre pseudospectral-based optimization method is also presented to obtain the path of optimal working condition transition. The simulation results of actual production data collected are given to verify the effectiveness and feasibility of the proposed strategy.


      PubDate: 2015-10-30T14:46:59Z
       
  • An adaptive observer framework for accurate feature depth estimation using
           an uncalibrated monocular camera
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Jishnu Keshavan, Hector Escobar-Alvarez, J. Sean Humbert
      This paper presents a novel solution to the problem of depth estimation using a monocular camera undergoing known motion. Such problems arise in machine vision where the position of an object moving in three-dimensional space has to be identified by tracking motion of its projected feature on the two-dimensional image plane. The camera is assumed to be uncalibrated, and an adaptive observer yielding asymptotic estimates of focal length and feature depth is developed that precludes prior knowledge of scene geometry and is simpler than alternative designs. Experimental results using real camera imagery are obtained with the current scheme as well as the extended Kalman filter, and performance of the proposed observer is shown to be better than the extended Kalman filter-based framework.


      PubDate: 2015-10-30T14:46:59Z
       
  • Vehicle tractive force prediction with robust and windup-stable Kalman
           filters
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Stephan Rhode, Sanghyun Hong, J. Karl Hedrick, Frank Gauterin
      Vehicle control systems need to prognosticate future vehicle states in order to improve energy efficiency. This paper compares four approaches that are used to identify the parameters of a longitudinal vehicle dynamics model used for the prediction of vehicle tractive forces. All of the identification approaches build on a standard Kalman filter. Measurement signals are processed using the polynomial function approximation technique to remove noise and compute smooth derivative values of the signals. Experimental results illustrate that the approach using multiple Stenlund–Gustafsson M-Kalman filters (multiple robust and windup-stable Kalman filters) reaches the best performance and robustness in predicting the vehicle tractive forces.


      PubDate: 2015-10-26T14:40:12Z
       
  • Canonical correlation analysis-based fault detection methods with
           application to alumina evaporation process
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Zhiwen Chen, Steven X. Ding, Kai Zhang, Zhebin Li, Zhikun Hu
      In this paper, canonical correlation analysis (CCA)-based fault detection methods are proposed for both static and dynamic processes. Different from the well-established process monitoring and fault diagnosis systems based on multivariate analysis techniques like principal component analysis and partial least squares, the core of the proposed methods is to build residual signals by means of the CCA technique for the fault detection purpose. The proposed methods are applied to an alumina evaporation process, and the achieved results show that both methods are applicable for fault detection, while the dynamic one delivers better detection performance.


      PubDate: 2015-10-26T14:40:12Z
       
  • Time-varying formation control for unmanned aerial vehicles with switching
           interaction topologies
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Xiwang Dong, Yan Zhou, Zhang Ren, Yisheng Zhong
      Time-varying formation control problems for unmanned aerial vehicle (UAV) swarm systems with switching interaction topologies are studied. Necessary and sufficient conditions for UAV swarm systems with switching interaction topologies to achieve predefined time-varying formations are proposed. Based on the common Lyapunov functional approach and algebraic Riccati equation technique, an approach to design the formation protocol is presented. An explicit expression of the formation reference function is derived to describe the macroscopic movement of the whole UAV formation. A quadrotor formation platform consisting of four quadrotors is introduced. Outdoor experiments are performed to demonstrate the effectiveness of the theoretical results.


      PubDate: 2015-10-26T14:40:12Z
       
  • Additive requirement ratio prediction using trend distribution features
           for hydrometallurgical purification processes
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Bin Zhang, Chunhua Yang, Yonggang Li, Xiaoli Wang, Hongqiu Zhu, Weihua Gui
      A purification process is to remove impurities through a series of reactors with additives. The theoretical calculated amount of additive does not fulfill actual requirements due to variations in the reaction environment. An additive requirement ratio is thus defined to measure the disparity between theoretical calculation and actual requirements. Considering the influence of the process underlying variations, a novel ratio prediction strategy, case-based prediction with trend distribution feature (CBP-TDF), is developed. In the strategy, the trend distribution features are firstly extracted to describe the underlying variations, and an improved case-based prediction algorithm is proposed where the similarity between these features is computed based on Kullback–Leibler divergence. The proposed strategy is applied to a copper removal process of zinc hydrometallurgy. The experiments indicate the accuracy of the ratio prediction, and the industrial application shows its effectiveness in the control of the purification process.


      PubDate: 2015-10-26T14:40:12Z
       
  • Adaptive fuzzy predictive controller for anesthesia delivery
    • Abstract: Publication date: January 2016
      Source:Control Engineering Practice, Volume 46
      Author(s): Juan A. Méndez, Ayoze Marrero, Jose A. Reboso, Ana León
      The problem of automating the infusion of anesthesia using fuzzy predictive control techniques is afforded. The control objective is to keep the hypnosis level of the patient in a proper and safe value. To provide accurate predictions, an adaptive model based on fuzzy logic and genetic algorithms is included. Thus, the drug infusion is adapted to the real needs of the patient and, consequently, the performance compared to other approaches is improved. The controller was evaluated both in simulation and in the operating room with patients undergoing surgery. Results obtained attest for the efficiency of the proposed method.


      PubDate: 2015-10-26T14:40:12Z
       
 
 
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