Decentralized adaptive neural output feedback control of a class of large-scale time-delay systems with input saturation

作者：Yang Yang; Yue Dong^*; Xue Yusheng

来源：Journal of the Franklin Institute, 2015, 352(5): 2129-2151.

DOI：10.1016/j.jfranklin.2015.02.009

A decentralized adaptive neural output feedback control scheme is presented for a class of large-scale time-delay systems with saturating inputs. The observer is constructed to estimate the immeasurable states of the system and the auxiliary system is designed to compensate the nonsmooth nonlinearities of input saturation constraints. Also, the control strategy is developed by the backstepping recursive method combining with neural networks (NI Ts) for the approximation of the unknown functions and dynamic surface control (DSC) technique for the well known 'explosion of complexity' problem. The advantage of this scheme is that it only relies on the output information of the system and there is no requirement for exact priori knowledge about the system parameters. It is proved that the control approach guarantees all signals in the closed-loop system uniformly ultimately bounded. Simulation results are provided to demonstrate the effectiveness and usefulness of the proposed strategy.

• 出版日期2015-5
• 单位南京邮电大学; 国网电力科学研究院