Regular Papers

International Journal of Control, Automation and Systems 2017; 15(3): 1425-1433

Published online May 22, 2017

https://doi.org/10.1007/s12555-016-0339-5

© The International Journal of Control, Automation, and Systems

Adaptive Neural Network Tracking of a Class of Switched Nonlinear Systems with Time-varying Output Constraints

Seung Woo Lee, Hyoung Oh Kim, and Sung Jin Yoo*

Chung-Ang University

Abstract

An approximation-based adaptive design problem for output-constrained tracking of a class of switched pure-feedback nonlinear systems is investigated under arbitrary switchings. All switched nonlinearities are assumed to be unknown. Contrary to the existing control results for uncertain switched pure-feedback nonlinear systems where the number of the used function approximators should be equal to the order of the systems, an adaptive control scheme based on only two neural networks is designed by using a system transformation and the common Lyapunov function method, regardless of the order of the system. In the proposed controller, the output constraints are used to establish designable time-varying bounds on the tracking performance. The stability and the constraint satisfaction of the resulting closed-loop system are shown in the sense of Lyapunov stability criterion. Finally, simulation examples are provided to illustrate the effectiveness of the proposed methodology."

Keywords Switched nonlinear systems, neural networks, time-varying output constraints, arbitrary switching.

Article

Regular Papers

International Journal of Control, Automation and Systems 2017; 15(3): 1425-1433

Published online June 1, 2017 https://doi.org/10.1007/s12555-016-0339-5

Copyright © The International Journal of Control, Automation, and Systems.

Adaptive Neural Network Tracking of a Class of Switched Nonlinear Systems with Time-varying Output Constraints

Seung Woo Lee, Hyoung Oh Kim, and Sung Jin Yoo*

Chung-Ang University

Abstract

An approximation-based adaptive design problem for output-constrained tracking of a class of switched pure-feedback nonlinear systems is investigated under arbitrary switchings. All switched nonlinearities are assumed to be unknown. Contrary to the existing control results for uncertain switched pure-feedback nonlinear systems where the number of the used function approximators should be equal to the order of the systems, an adaptive control scheme based on only two neural networks is designed by using a system transformation and the common Lyapunov function method, regardless of the order of the system. In the proposed controller, the output constraints are used to establish designable time-varying bounds on the tracking performance. The stability and the constraint satisfaction of the resulting closed-loop system are shown in the sense of Lyapunov stability criterion. Finally, simulation examples are provided to illustrate the effectiveness of the proposed methodology."

Keywords: Switched nonlinear systems, neural networks, time-varying output constraints, arbitrary switching.

IJCAS
May 2024

Vol. 22, No. 5, pp. 1461~1759

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