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Controller Parameters (controller + parameter)
Selected AbstractsTuning and parameter variation effects in MRAS based speed estimator for sensorless vector controlled induction motor drivesEUROPEAN TRANSACTIONS ON ELECTRICAL POWER, Issue 3 2002M. Wang A frequently applied method of speed-sensorless rotor flux oriented control of induction machines relies on utilisation of model reference adaptive system (MRAS) based speed estimation, where the outputs of the reference and the adjustable model are selected as rotor flux space phasors. Accuracy of the method heavily depends on correct setting of the machine parameters and adjustment of the filter and Pl controller parameters within the estimator. The paper at first describes tuning of various parameters of the estimator, using purely experimental data. The speed estimator is operated in parallel with a commercially available rotor flux oriented induction motor drive with speed sensor and sampled stator voltages and currents are used to tune induction motor parameters, various filters and the Pl controller within the estimator. The procedure is described and illustrated using a comparison between the measured actual speed response during acceleration transients and the corresponding speed estimate obtained from the speed estimator. In the second part of the paper, speed estimation error that will take place in the base speed region due to incorrect setting and/or variation of the parameters of the machine (stator resistance, rotor resistance and magnetising inductance) within the speed estimator is assessed using experimentally recorded data. The experimental results are found to be in very good agreement with previously published theoretical results. [source] Stability and accuracy analysis of a discrete model reference adaptive controller without and with time delayINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 9 2010Oreste S. Bursi Abstract Adaptive control techniques can be applied to dynamical systems whose parameters are unknown. We propose a technique based on control and numerical analysis approaches to the study of the stability and accuracy of adaptive control algorithms affected by time delay. In particular, we consider the adaptive minimal control synthesis (MCS) algorithm applied to linear time-invariant plants, due to which, the whole controlled system generated from state and control equations discretized by the zero-order-hold (ZOH) sampling is nonlinear. Hence, we propose two linearization procedures for it: the first is via what we term as physical insight and the second is via Taylor series expansion. The physical insight scheme results in useful methods for a priori selection of the controller parameters and of the discrete-time step. As there is an inherent sampling delay in the process, a fixed one-step delay in the discrete-time MCS controller is introduced. This results in a reduction of both the absolute stability regions and the controller performance. Owing to the shortcomings of ZOH sampling in coping with high-frequency disturbances, a linearly implicit L-stable integrator is also used within a two degree-of-freedom controlled system. The effectiveness of the methodology is confirmed both by simulations and by experimental tests. Copyright © 2009 John Wiley & Sons, Ltd. [source] Nonlinear reference tracking control of a gas turbine with load torque estimationINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 8 2008B. Pongrácz Abstract Input,output linearization-based adaptive reference tracking control of a low-power gas turbine model is presented in this paper. The gas turbine is described by a third-order nonlinear input-affine state-space model, where the manipulable input is the fuel mass flowrate and the controlled output is the rotational speed. The stability of the one-dimensional zero dynamics of the controlled plant is investigated via phase diagrams. The input,output linearizing feedback is extended with a load torque estimator algorithm resulting in an adaptive feedback scheme. The tuning of controller parameters is performed considering three main design goals: appropriate settling time, robustness against environmental disturbances and model parameter uncertainties, and avoiding the saturation of the actuator. Simulations show that the closed-loop system is robust with respect to the variations in uncertain model and environ-mental parameters and its performance satisfies the defined requirements. Copyright © 2007 John Wiley & Sons, Ltd. [source] Design of a near-optimal adaptive filter in digital signal processor for active noise controlINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 1 2008S. M. Yang Abstract Adaptive filter has been applied in adaptive feedback and feedforward control systems, where the filter dimension is often determined by trial-and-error. The controller design based on a near-optimal adaptive filter in digital signal processor (DSP) is developed in this paper for real-time applications. The design integrates the adaptive filter and the experimental design such that their advantages in stability and robustness can be combined. The near-optimal set of controller parameters, including the sampling rate, the dimension of system identification model, the dimension (order) of adaptive controller in the form of an FIR filter, and the convergence rate of adaptation is shown to achieve the best possible system performance. In addition, the sensitivity of each design parameter can be determined by analysis of means and analysis of variance. Effectiveness of the adaptive controller on a DSP is validated by an active noise control experiment. Copyright © 2007 John Wiley & Sons, Ltd. [source] Adaptive transfer function-based control of nonlinear process.INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 10 2007Case study: Control of temperature in industrial methane tank Abstract The state model-based transfer function models are applied for adaptation of linear controller and disturbance compensator in a feedback/feed-forward control system of nonlinear process. An advantage of the presented adaptation method is the avoidance of artificial disturbances or iterative identification procedures for on-line estimation of process dynamic parameters. The adaptation is based on linearization of the process model at each sampling time about the current state point, independent of the process being at steady-state or transient conditions. The linear time-varying dynamics model is updated on-line using measured values of process variables and reduced to the first-order plus time delay transfer function models in order to directly apply well-developed controller tuning rules. Computational aspects of the adaptation method are discussed and computation algorithms are presented. The adaptive feedback/feed-forward control system was applied for controlling temperature in industrial methane tank, dynamic parameters of which vary in a wide range due to variations of methane-tank process load and external conditions. The heat balance-based process state model is developed and validated using observation data of real plant. Computer simulation of the proposed control system performance under extreme operating conditions demonstrates fast adaptation of controller parameters, robust behaviour and significant improvement in the controllers' performance compared to that of fixed-gain controllers. Copyright © 2007 John Wiley & Sons, Ltd. [source] Output-feedback co-ordinated decentralized adaptive tracking: The case of MIMO subsystems with delayed interconnectionsINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 8 2005Boris M. Mirkin Abstract Exact decentralized output-feedback Lyapunov-based designs of direct model reference adaptive control (MRAC) for linear interconnected delay systems with MIMO subsystems are introduced. The design process uses a co-ordinated decentralized structure of adaptive control with reference model co-ordination which requires an exchange of signals between the different reference models. It is shown that in the framework of the reference model co-ordination zero residual tracking error is possible, exactly as in the case with SISO subsystems. We develop decentralized MRAC on the base of a priori information about only the local subsystems gain frequency matrices without additional a priori knowledge about the full system gain frequency matrix. To achieve a better adaptation performance we propose proportional, integral time-delayed adaptation laws. The appropriate Lyapunov,Krasovskii type functional is suggested to design the update mechanism for the controller parameters, and in order to prove stability. Two different adaptive DMRAC schemes are proposed, being the first asymptotic exact zero tracking results for linear interconnected delay systems with MIMO subsystems. Copyright © 2005 John Wiley & Sons, Ltd. [source] Iterative correlation-based controller tuningINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 8 2004A. Karimi Abstract This paper gives an overview on the theoretical results of recently developed algorithms for iterative controller tuning based on the correlation approach. The basic idea is to decorrelate the output error between the achieved and designed closed-loop systems by iteratively tuning the controller parameters. Two different approaches are investigated. In the first one, a correlation equation involving a vector of instrumental variables is solved using the stochastic approximation method. It is shown that, with an appropriate choice of instrumental variables and a finite number of data at each iteration, the algorithm converges to the solution of the correlation equation. The convergence conditions are derived and the accuracy of the estimates are studied. The second approach is based on the minimization of a correlation criterion. The frequency analysis of the criterion shows that the two norm of the error between the desired and achieved closed-loop transfer functions is minimized independent of the noise characteristics. This analysis leads to the definition of a generalized correlation criterion which allows the mixed sensitivity problem to be handled in two norm. Copyright © 2004 John Wiley & Sons, Ltd. [source] Experimental modelling and intelligent control of a wood-drying kilnINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 8 2001Givon Chuen Kee Yan Abstract Proper control of the wood-drying kiln is crucial in ensuring satisfactory quality of dried wood and in minimizing drying time. This paper presents the development, implementation, and evaluation of a control system for a lumber drying kiln process incorporating sensory feedback from in-wood moisture content sensors and intelligent control such that the moisture content of lumber will reach and stabilize at the desired set point without operator interference. The drying process is difficult to model and control due to complex dynamic nonlinearities, coupling effects among key variables, and process disturbances caused by the variation of lumber sizes, species, and environmental factors. Through system identification scheme using experimental data and recursive least-squares algorithm for parameter estimation, appropriate models are developed for simulation purpose and controller design. Two different control methodologies are employed and compared: a conventional proportional-integral-derivative (PID) controller and a direct fuzzy logic controller (FLC), and system performance is evaluated through simulations. The developed control system is then implemented in a downscaled industrial kiln located at the Innovation Centre of National Research Council (NRC) of Canada. This experimental set-up is equipped with a variety of sensors, including thermocouples for temperature feedback, an air velocity transmitter for measuring airflow speed in the plenum, relative humidity sensors for measuring the relative humidity inside the kiln, and in-wood moisture content sensors for measuring the moisture content of the wood pieces. For comparison, extensive experimental studies are carried out on-line using the two controllers, and the results are evaluated to tune the controller parameters to achieve good performance in the wood-drying kiln. The combination of conventional control with the intelligent control promises improved performance. The control system developed in this study may be applied in industrial wood-drying kilns, with a clear potential for improved quality and increased speed of drying. Copyright © 2001 John Wiley & Sons, Ltd. [source] Design of fault-tolerant control for MTTFINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 16 2008Hongbin Li Abstract Mean time to failure (MTTF) is an important reliability index of fault-tolerant control systems, which is chosen as a design objective in this paper. However, it is usually evaluated from stochastic reliability models, and no analytical expression is available to relate MTTF to controller parameters. To overcome this difficulty, a two-stage design scheme is proposed in this paper: A gradient-based search is firstly carried out on probabilistic H, performance characteristics for MTTF requirement; a sequential randomized algorithm with a weighted violation function is then developed for a controller design to satisfy the required H, performance, and its convergence is guaranteed with probability 1. Two iterative algorithms are carried out alternately to implement this scheme, and a controller can be designed for MTTF requirement. Copyright © 2008 John Wiley & Sons, Ltd. [source] Generalized homogeneous quasi-continuous controllersINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 4-5 2008Arie Levant Abstract A new class of arbitrary-order homogeneous quasi-continuous sliding-mode controllers containing numerous functional parameters is proposed. All the controllers also have robust output-feedback versions. A numerical procedure is established for the first time for setting the controller parameters. A finite-time stable 5-sliding mode is demonstrated for the first time. Copyright © 2007 John Wiley & Sons, Ltd. [source] A Synthesis Method For Robust Pid Controllers For A Class Of Uncertain SystemsASIAN JOURNAL OF CONTROL, Issue 4 2002Stefan Solyom ABSTRACT PID controller design is considered where optimal controller parameters are found with constraint on maximum sensitivity and robustness with regard to a cone bounded static nonlinearity acting in feedback with part of the plant. The design procedure has been successfully applied in the synthesis of a controller for an Anti-lock Braking System (ABS). [source] | ||||||||||