Results 1  10
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24
Supervisory Control of Families of Linear SetPoint Controllers  Part 2: Robustness
 IEEE Trans. Automat. Contr
, 1998
"... A simplystructured highlevel controller called a `supervisor' has recently been proposed in [1] for the purpose of orchestrating the switching of a sequence of candidate setpoint controllers into feedback with an imprecisely modeled siso process so as to cause the output of the process to approac ..."
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Cited by 138 (24 self)
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A simplystructured highlevel controller called a `supervisor' has recently been proposed in [1] for the purpose of orchestrating the switching of a sequence of candidate setpoint controllers into feedback with an imprecisely modeled siso process so as to cause the output of the process to approach and track a constant reference input. The process is assumed to be modeled by a siso linear system whose transfer function is in the union of a number of subclasses, each subclass being small enough so that one of the candidate controllers would solve the setpoint tracking problem, were the process's transfer function to be one of the subclass's members. In [1] it is shown that in the absence of unmodelled process dynamics the proposed supervisor can successfully perform its function fi.e., achieve a zero steady state tracking errorg even if process disturbances are present, provided they are constant. This paper proves that without any further modification, the same supervisor can also perform this function in the face of normbounded unmodelled dynamics and moreover that none of the signals within the overall system can grow without bound in response to bounded disturbance and noise inputs, be they constant or not.
Control Using LogicBased Switching
 Trends in Control: A European Perspective
, 1998
"... this paper is to give a brief tutorial review of four different classes of hybrid systems of this type  each consists of a continuoustime process to be controlled, a parameterized family of candidate controllers, and an event driven switching logic. Three of the logics, called prerouted switching, ..."
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Cited by 67 (19 self)
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this paper is to give a brief tutorial review of four different classes of hybrid systems of this type  each consists of a continuoustime process to be controlled, a parameterized family of candidate controllers, and an event driven switching logic. Three of the logics, called prerouted switching, hysteresis switching and dwelltime switching respectively, are simple strategies capable of determining in real time which candidate controller should be put in feedback with a process in order to achieve desired closedloop performance. The fourth, called cyclic switching, has been devised to solve the longstanding stabilizability problem which arises in the synthesis of identifierbased adaptive controllers because of the existence of points in parameter space where the estimated model upon which certainty equivalence synthesis is based, loses stabilizability
Intelligent Control for Brake Systems
 IEEE Transactions on Control Systems Technology
, 1999
"... Abstract—There exist several problems in the control of brake systems including the development of control logic for antilock braking systems (ABS) and “basebraking. ” Here, we study the basebraking control problem where we seek to develop a controller that can ensure that the braking torque comma ..."
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Cited by 13 (4 self)
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Abstract—There exist several problems in the control of brake systems including the development of control logic for antilock braking systems (ABS) and “basebraking. ” Here, we study the basebraking control problem where we seek to develop a controller that can ensure that the braking torque commanded by the driver will be achieved. In particular, we develop a “fuzzy model reference learning controller, ” a “genetic model reference adaptive controller, ” and a “general genetic adaptive controller,” and investigate their ability to reduce the effects of variations in the process due to temperature. The results are compared to those found in previous research. Index Terms—Adaptive control, automotive, brakes, fuzzy control, genetic algorithms.
Design and analysis of a novel L1 adaptive control architeture with guaranteed transient performance
 IEEE Trans. on Auto. Control
, 2008
"... Conventional Model Reference Adaptive Controller (MRAC), while providing an architecture for control of systems in the presence of parametric uncertainties, offers no means for characterizing the system’s input/output performance during the transient phase. Application of adaptive controllers was th ..."
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Cited by 12 (0 self)
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Conventional Model Reference Adaptive Controller (MRAC), while providing an architecture for control of systems in the presence of parametric uncertainties, offers no means for characterizing the system’s input/output performance during the transient phase. Application of adaptive controllers was therefore largely restricted due to the fact that the system uncertainties during the transient have led to unpredictable/undesirebale situations, involving control signals of highfrequency or large amplitudes, large transient errors or slow convergence rate of tracking errors, to name a few. In this paper, we develop a novel adaptive control architecture that ensures that the input and the output of an uncertain linear system track the input and output of a desired linear system during the transient phase, in addition to the asymptotic tracking. This new architecture has a lowpass filter in the feedbackloop that enables to enforce the desired transient performance by increasing the adaptation gain. For the proof of asymptotic stability, the L1 gain of a cascaded system, comprised of this filter and the closedloop desired reference model, is required to be less than the inverse of the upper bound of the norm of unknown parameters used in projection
Improved Transient Performance of Nonlinear Adaptive Backstepping using Estimator Resetting based on Multiple Models
, 2002
"... It is proved that the transient performance of nonlinear adaptive backstepping can be improved by resetting the parameter estimator, without loss of stability. The estimator resetting algorithm is based on multiple model adaptivecontrol, where a number of models with fixed parameter vectors are moni ..."
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Cited by 5 (4 self)
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It is proved that the transient performance of nonlinear adaptive backstepping can be improved by resetting the parameter estimator, without loss of stability. The estimator resetting algorithm is based on multiple model adaptivecontrol, where a number of models with fixed parameter vectors are monitored online in order to detect parameter vectors that gives a negative jump in the control Lyapunov function when replacing the estimate provided by the standard adaptation law. Application to wheel slip control is studied. 1
Guaranteed transient performance with L1 adaptive controller for systems with unknown timevarying parameters
 Part I. Conf. on Decision and Control, Submitted
, 2006
"... This paper presents a novel adaptive control methodology for uncertain systems with timevarying unknown parameters and timevarying bounded disturbance. The adaptive controller ensures uniformly bounded transient and asymptotic tracking for system’s both signals, input and output, simultaneously. Th ..."
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Cited by 5 (2 self)
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This paper presents a novel adaptive control methodology for uncertain systems with timevarying unknown parameters and timevarying bounded disturbance. The adaptive controller ensures uniformly bounded transient and asymptotic tracking for system’s both signals, input and output, simultaneously. The performance bounds can be systematically improved by increasing the adaptation gain. Simulations of a robotic arm with timevarying friction verify the theoretical findings. 1
A MultiModel Algorithm for Parameter Estimation of Time Varying Nonlinear Systems
, 1998
"... We present a new online multimodel algorithm for parameter estimation of timevarying nonlinear systems. The timevariation is captured by assuming that the system parameters change according to a MarkovJan mechanism. The algorithm postulates a finite nmnber of possible values of the system paramet ..."
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Cited by 3 (0 self)
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We present a new online multimodel algorithm for parameter estimation of timevarying nonlinear systems. The timevariation is captured by assuming that the system parameters change according to a MarkovJan mechanism. The algorithm postulates a finite nmnber of possible values of the system parameter and computes recursively the credit function of each parameter value, according to its predictive accuracy. A convergence analysis of the algorithm is presented which indicates that the algorithm estimates correctly the parameter value, in the time intervals between source switchings. This conclusion is corroborated by numerical experiments.
Lyapunovbased Integrator Resetting with Application to Marine Thruster Control
"... This paper addresses the idea of improving transient behavior by internal state resetting of dynamic controllers, such as controllers with integral action or adaptation. The concept presented here assumes that for a given closed loop system with a dynamic controller, improved transient performance i ..."
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Cited by 2 (0 self)
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This paper addresses the idea of improving transient behavior by internal state resetting of dynamic controllers, such as controllers with integral action or adaptation. The concept presented here assumes that for a given closed loop system with a dynamic controller, improved transient performance is achieved when reset of controller states gives negative jumps in the Lyapunov function value. The Lyapunov function constitutes a part of the controller algorithm. By combining this with existing stability theory for switched systems, the stability analysis of the overall system follows directly. The framework assumes that a Lyapunov function is given, and that full state measurement is available for feedback. Moreover, an estimator is needed to give a coarse estimate of the system equilibrium point. An antispin feature in local thruster speed control on ships with electric propulsion is in this paper presented as an application for the given framework. Transients arise when the ship operates in extreme seas, where disturbances such as ventilation and inandout of water effects may give rise to loss in propeller thrust. A Lyapunov function is used to decide appropriate reset of the integrator state of a standard PIcontroller. The method is illustrated with experimental results.
Model predictive control of CSTR based on local model networks
 Proceedings of Irish Signals and Systems Conference
, 2002
"... Abstract A nonlinear predictive controller is presented. It judiciously combines predictive controllers with a local model network utilizing a neuralnetworklike gating system. It avoids the time consuming quadratic optimization calculation, which is normally necessary in nonlinear predictive c ..."
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Cited by 1 (1 self)
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Abstract A nonlinear predictive controller is presented. It judiciously combines predictive controllers with a local model network utilizing a neuralnetworklike gating system. It avoids the time consuming quadratic optimization calculation, which is normally necessary in nonlinear predictive control. A controller simulation on a Continuous Stirred Tank Reactor (CSTR) case study was shown to be satisfactory both in terms of set point tracking and regulation performance over the entire operating range. Moreover, the inherent integration action in the local predictive controller provides zero static offsets. Key words model predictive control, local model network, local controller network, nonlinearity, neural network. ____________________________________________________________________________________________ I.
On Transient Performance, Estimator Resetting and Filtering in Nonlinear Multiple Model Adaptive Backstepping Control
"... Multiple model adaptive control (MMAC) is a well established approach for implementing adaptive systems with fast transient response. This paper considers a recently developed MMAC method based on adaptive nonlinear backstepping control where the parameter estimate may be instantaneously reset based ..."
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Cited by 1 (1 self)
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Multiple model adaptive control (MMAC) is a well established approach for implementing adaptive systems with fast transient response. This paper considers a recently developed MMAC method based on adaptive nonlinear backstepping control where the parameter estimate may be instantaneously reset based on a criterion that requires a negative jump in the associated control Lyapunov function. Particular attention is paid to transient effects due to data filtering, which must be introduced in any practical implementation of the MMAC algorithm in order to reduce the sensitivity to noise, disturbances and model uncertainty. The main contribution of this paper is insight into the robust behavior of the adaptive system resulting from the filtering, and an investigation into the tradeoffs between high transient performance and robustness to uncertainty. We also suggest data filter tuning guidelines and illustrate the results using a simulation example.