# Decentralized Adaptive Neural Approximated Inverse Control for a Class of Large-Scale Nonlinear Hysteretic Systems with Time Delays

Xiuyu Zhang, Yue Wang, Xinkai Chen, Chun Yi Su, Zhi Li, Chenliang Wang, Yaxuan Peng

Research output: Contribution to journalArticlepeer-review

95 Citations (Scopus)

## Abstract

This paper proposes a decentralized neural adaptive dynamic surface approximated inverse control (DNADSAIC) scheme for a class of large-scale time-delay systems with hysteresis nonlinearities as input. The decentralized control problem under the case only the outputs are measurable is solved by utilizing the radial basis function neural networks approximator and the hysteresis approximated inverse compensator. Also, with the help of finite covering lemma, the traditional Krasovskii functionals are dropped when coping with the delays, leading to the removal of the assumptions on the functions with time-delay states and the acquisition of the arbitrarily small ${L}_{{\infty }}$ tracking performance of each hysteretic subsystem with time delays. The analysis of stabilities guarantees all the signals of the closed-loop systems are semiglobally uniformly ultimately bounded. Simulation results illustrate the efficiency of the proposed DNADSAIC scheme.

Original language English 8354937 2424-2437 14 IEEE Transactions on Systems, Man, and Cybernetics: Systems 49 12 https://doi.org/10.1109/TSMC.2018.2827101 Published - 2019 Dec

## Keywords

• dynamic surface approximated inverse control
• hysteresis
• large-scale system

## ASJC Scopus subject areas

• Software
• Control and Systems Engineering
• Human-Computer Interaction
• Computer Science Applications
• Electrical and Electronic Engineering

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