Simulation and Stability Analysis of Neural Network Based Control Scheme for Switched Linear Systems

The post Simulation and Stability Analysis of Neural Network Based Control Scheme for Switched Linear Systems first appeared on the ISA Interchange blog site.

This post is an excerpt from the journal ISA Transactions. All ISA Transactions articles are free to ISA members, or can be purchased from Elsevier Press.

Abstract: This paper proposes a new adaptive neural network based control scheme for switched linear systems with parametric uncertainty and external disturbance. A key feature of this scheme is that the prior information of the possible upper bound of the uncertainty is not required. A feedforward neural network is employed to learn this upper bound. The adaptive learning algorithm is derived from Lyapunov stability analysis so that the system response under arbitrary switching laws is guaranteed uniformly ultimately bounded. A comparative simulation study with robust controller given in [Zhang L, Lu Y, Chen Y, Mastorakis NE. Robust uniformly ultimate boundedness control for uncertain switched linear systems. Computers and Mathematics with Applications 2008; 56: 1709–14] is presented.

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Source: ISA News