Decentralized Adaptive Dynamic Surface Control for Large-scale Multi-machine Power Systems with Unknown Time Delay

摘要

A decentralized adaptive quantized dynamic surface control scheme is proposed for the large scale multi-machine power systems with static var compensator (SVC) and the unknown time delays. The `explosion of complexity' problem in backstepping method, the uncertainties and complexities introduced by SVC are overcome. By estimating the weight vector norm of neural networks, the number of the parameters need to be estimated in each step is greatly reduces. It is proved that all the signals in the closed-loop system are ultimately uniformly bounded. Simulation results illustrate the validity of the proposed control scheme.