Adaptive Neural Network Decentralized Backstepping Output-Feedback Control for Nonlinear Large-Scale Systems with Time Delays

作者：Tong Shao Cheng^*; Li Yong Ming; Zhang Hua Guang

来源：IEEE Transactions on Neural Networks, 2011, 22(7): 1073-1086.

DOI：10.1109/TNN.2011.2146274

• Adaptive decentralized control
• backstepping technique
• neural network
• nonlinear large-scale systems
• stability analysis
• state observer

In this paper, two adaptive neural network (NN) decentralized output feedback control approaches are proposed for a class of uncertain nonlinear large-scale systems with immeasurable states and unknown time delays. Using NNs to approximate the unknown nonlinear functions, an NN state observer is designed to estimate the immeasurable states. By combining the adaptive backstepping technique with decentralized control design principle, an adaptive NN decentralized output feedback control approach is developed. In order to overcome the problem of "explosion of complexity" inherent in the proposed control approach, the dynamic surface control (DSC) technique is introduced into the first adaptive NN decentralized control scheme, and a simplified adaptive NN decentralized output feedback DSC approach is developed. It is proved that the two proposed control approaches can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded, and the observer errors and the tracking errors converge to a small neighborhood of the origin. Simulation results are provided to show the effectiveness of the proposed approaches.

• 出版日期2011-7
• 单位辽宁工业大学