NEURAL NETWORK-BASED ADAPTIVE PI BACKSTEPPING CONTROL FOR FRACTIONAL-ORDER CHAOTIC SYSTEMS WITH STATES CONSTRAINTS

Chunzhi Yang and Yong Chen
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Chunzhi Yang: School of Computer, Sichuan Technology and Business University, Chengdu 611745, P. R. China2School of Mathematical Sciences, Guangxi Minzu University, Nanning 530006, P. R. China
Yong Chen: School of Computer, Sichuan Technology and Business University, Chengdu 611745, P. R. China

FRACTALS (fractals), 2025, vol. 33, issue 04, 1-11

Abstract: In this paper, for a class of uncertain fractional-order chaotic systems with state constraints, an adaptive PI synchronization control algorithm based on neural networks is proposed, in which the neural network is used to approximate the unknown function. A PI-based regulator with proportional-integral is introduced to participate in the controller adjustment process and a special generalized error variable is proposed in this process. In order to avoid the state crossing the boundary, a logarithmic barrier function is proposed in time to manage the state of the system. Moreover, the proposed PI-based backstepping synchronous controller can ensure the stability of the closed-loop system and the error converges to a particularly small domain from the origin. Simulation experiments verify the practicability and effectiveness of this method.

Keywords: Adaptive Neural Network Control; PI Backstepping Control; Fractional-order Chaotic System; States Constraint (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1142/S0218348X25400766

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