Adaptive Control Design for Nonlinear Systems via Successive Approximations

The paper presents an approach to the Model Reference Adaptive Control (MRAC) design for nonlinear dynamical systems. A nonlinear reference system is considered such that its response is designed to be stable via Successive Approximation Approach (SAA). Having designed the stable reference model through the SAA, MRAC is then formulated for nonlinear plant dynamics with a new adaptation rule to guarantee the convergence of the nonlinear plant response to that of the response of the nonlinear reference model. The proposed design methodology is illustrated with examples for different case studies.

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Discrete-time model reference adaptive control of nonlinear dynamical systems using neural networks

International Journal of Control ◽

10.1080/00207179608921625 ◽

1996 ◽

Vol 64 (2) ◽

pp. 217-239 ◽

Cited By ~ 22

Author(s):

S. JAGANNATHAN ◽

F. L. LEWIS ◽

O. PASTRAVANU

Keyword(s):

Neural Networks ◽

Adaptive Control ◽

Dynamical Systems ◽

Discrete Time ◽

Nonlinear Dynamical Systems ◽

Model Reference Adaptive Control ◽

Time Model ◽

Nonlinear Dynamical ◽

Discrete Time Model ◽

Model Reference Adaptive

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Successive Approximations of Model Reference Adaptive Control Design for Nonlinear Systems

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2015.11.095 ◽

2015 ◽

Vol 48 (25) ◽

pp. 248-253 ◽

Cited By ~ 3

Author(s):

Fettah Kodalak ◽

Metin U. Salamci

Keyword(s):

Adaptive Control ◽

Nonlinear Systems ◽

Control Design ◽

Model Reference Adaptive Control ◽

Successive Approximations ◽

Model Reference ◽

Model Reference Adaptive

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Model reference adaptive control of nonlinear dynamical systems using multilayer neural networks

Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94) ◽

10.1109/icnn.1994.375046 ◽

2002 ◽

Cited By ~ 9

Author(s):

S. Jagannathan ◽

F.L. Lewis ◽

O. Pastravanu

Keyword(s):

Neural Networks ◽

Adaptive Control ◽

Dynamical Systems ◽

Nonlinear Dynamical Systems ◽

Model Reference Adaptive Control ◽

Model Reference ◽

Nonlinear Dynamical ◽

Multilayer Neural Networks ◽

Model Reference Adaptive

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Multimode Adaptive Control for Tank Gun Control System Based on Tracking Differentiator

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.383-390.79 ◽

2011 ◽

Vol 383-390 ◽

pp. 79-85

Author(s):

Dong Yuan ◽

Xiao Jun Ma ◽

Wei Wei

Keyword(s):

Adaptive Control ◽

Control System ◽

High Speed ◽

Control Method ◽

Reference Model ◽

Gun Control ◽

Math Model ◽

Tracking Differentiator ◽

Switch Control ◽

Model Reference Adaptive

Aiming at the problems such as switch impulsion, insurmountability for influence caused by nonlinearity in one tank gun control system which adopts double PID controller to realize the multimode switch control between high speed and low speed movement, the system math model is built up; And then, Model Reference Adaptive Control (MRAC) method based on nonroutine reference model is brought in and the adaptive gun controller is designed. Consequently, the compensation of nonlinearity and multimode control are implemented. Furthermore, the Tracking Differentiator (TD) is affiliated to the front of controller in order to restrain the impulsion caused by mode switch. Finally, the validity of control method in this paper is verified by simulation.

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Model reference adaptive control with a constrained linear reference model

49th IEEE Conference on Decision and Control (CDC) ◽

10.1109/cdc.2010.5717275 ◽

2010 ◽

Cited By ~ 5

Author(s):

Suresh K. Kannan ◽

Eric N. Johnson

Keyword(s):

Adaptive Control ◽

Reference Model ◽

Model Reference Adaptive Control ◽

Model Reference ◽

Model Reference Adaptive

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Enhanced Model Reference Adaptive Control Using Smith Predictor

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.367.363 ◽

2013 ◽

Vol 367 ◽

pp. 363-368

Author(s):

R. Karthikeyan ◽

C. Bhargav ◽

Karthik Koneru ◽

G. Syam ◽

Shikha Tripathi

Keyword(s):

Adaptive Control ◽

Fuzzy Logic Controller ◽

Dead Time ◽

Reference Model ◽

Model Reference Adaptive Control ◽

Vital Role ◽

Smith Predictor ◽

Model Reference ◽

Time Effects ◽

Model Reference Adaptive

The main aim of a control system is to repress the instabilities caused by nonlinearities of the system. Dead time is considered to be one of the most significant nonlinearities of a system. Dead time compensators play a vital role in reducing the dead time effects on the processes only to a minute extent. This paper proposes a method to overcome this problem by using Enhanced Model Reference Adaptive Control (MRAC) incorporating Smith Predictor. MRAC belongs to class of adaptive servo system in which desired performance is expressed with the help of a reference model. Enhanced MRAC consists of a fuzzy logic controller which provides adaptation gain to MRAC without human interference. A dead time compensator incorporated in the enhanced MRAC solves the problem of instabilities caused by dead time to a greater extent.

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Experimental Investigation of Adaptive Control Applied to HSFD Supported Rotors

Volume 4: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation; Education; IGTI Scholar Award; General ◽

10.1115/99-gt-176 ◽

1999 ◽

Cited By ~ 1

Author(s):

A. El-Shafei ◽

M. El-Hakim

Keyword(s):

Experimental Investigation ◽

Adaptive Control ◽

Reference Model ◽

Computer Control ◽

Adaptive Controller ◽

Superior Performance ◽

Order System ◽

Squeeze Film ◽

Run Up ◽

Model Reference Adaptive

This paper describes the experimental application of adaptive control to Hybrid Squeeze Film Damper (HSFD) supported rotors. The HSFD has been shown to be an adaptive damper capable of providing infinite damper configurations between short and long damper configurations. Previously, theoretical investigations of the adaptive control of HSFD concentrated on the development of the model reference adaptive control (MRAC) method, as well as development of a nonlinear reference model. Simulations of the performance of the adaptive controller during run-up and coast-down indicated the superior performance of the adaptive controller. In this paper, the adaptive controller is tested on a multi-mode rotor. A test rig is designed and developed using computer control. A simple reference model is investigated consisting of a second order system. Three forms for adaptation gain are studied. The results of the experimental investigation illustrated the performance capabilities of the adaptive controller applied to the HSFD, and moreover indicated the possibility of simple design for the adaptive controller.

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