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

作者：Zhang, Xiuyu; Wang, Yue; Chen, Xinkai^*; Su, Chun-Yi; Li, Zhi; Wang, Chenliang; Peng, Yaxuan^*

来源：IEEE Transactions on Systems, Man, and Cybernetics: Systems , 2019, 49(12): 2424-2437.

DOI：10.1109/TSMC.2018.2827101

• Decentralized adaptive control
• dynamic surface approximated inverse control
• hysteresis
• L-infinity performance
• (1) large-scale system

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-infinity 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.

• 出版日期2019-12
• 单位东北电力大学; 北京航空航天大学