A New Static Synchronous Series Compensator Control Strategy Based on RBF Neuro-Sliding Mode Technique for Power Flow Control and DC Voltage Regulation

Abstract

This paper presents a new hybrid approach which combines Radial Basis Function neural network with the sliding mode technique to design a Static Synchronous Series Compensator controller for power flow control and DC voltage regulation of an electric power transmission system. The proposed neuro-sliding mode control technique requires reduced number of hidden units and the weights are updated through on-line learning. The proposed technique is robust and does not need the knowledge of the perturbation bounds nor the full state of the nonlinear system (as opposed to existing methods based on Radial Basis Function neural networks). The performance of the proposed controller is validated on an IEEE 9 bus test system. Comparative results with another neural networks control and PI regulators show the effectiveness and satisfactory performance of the proposed controller in dealing with the perturbations considered.