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Content Provider | IEEE Xplore Digital Library |
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Author | Ren, X.M. Rad, A.B. Chan, P.T. Wai Lun Lo |
Copyright Year | 1982 |
Abstract | In this paper, we present an algorithm for the online identification and adaptive control of a class of continuous-time nonlinear systems via dynamic neural networks. The plant considered is an unknown multi-input/multi-output continuous-time higher order nonlinear system. The control scheme includes two parts: a dynamic neural network is employed to perform system identification and a controller based on the proposed dynamic neural network is developed to track a reference trajectory. Stability analysis for the identification and the tracking errors is performed by means of Lyapunov stability criterion. Finally, we illustrate the effectiveness of these methods by computer simulations of the Duffing chaotic system and one-link rigid robot manipulator. The simulation results demonstrate that the model-based dynamic neural network control scheme is appropriate for control of unknown continuous-time nonlinear systems with output disturbance noise. |
Sponsorship | IEEE Industrial Electronics Society |
Starting Page | 478 |
Ending Page | 486 |
Page Count | 9 |
File Size | 694291 |
File Format | |
ISSN | 02780046 |
Volume Number | 50 |
Issue Number | 3 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2003-06-01 |
Publisher Place | U.S.A. |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Nonlinear control systems Control systems Nonlinear systems Neural networks Nonlinear dynamical systems Adaptive control System identification Trajectory Stability analysis Computer errors |
Content Type | Text |
Resource Type | Article |
Subject | Control and Systems Engineering Electrical and Electronic Engineering Computer Science Applications |
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