Adaptive Discrete-Time Quantized Control for Multi-machine Power System with SVC

In this paper, a discrete-time adaptive dynamic surface quantization control method has been proposed for a class of multi-machine power systems with Static Var Compensator (SVC). The strategy combines RBF neural network and discrete low-pass filter to solve the differential explosion problem in backstepping and simplify the control law. Chatter is also reduced by a modified hysteresis quantizer, and digital control is achieved. Ultimate uniformly bounded properties of closed-loop systems are proved by designing Lyapunov functions and the simulation results confirm the effectiveness of the method.