LFC based adaptive PID controller using ANN and ANFIS techniques

Abstract

This paper presents an adaptive PID Load Frequency Control (LFC) for power systems using Neuro-Fuzzy Inference Systems (ANFIS) and Artificial Neural Networks (ANN) oriented by Genetic Algorithm (GA). PID controller parameters are tuned off-line by using GA to minimize integral error square over a wide-range of load variations. The values of PID controller parameters obtained from GA are used to train both ANFIS and ANN. Therefore, the two proposed techniques could, online, tune the PID controller parameters for optimal response at any other load point within the operating range. Testing of the developed techniques shows that the adaptive PID-LFC could preserve optimal performance over the whole loading range. Results signify superiority of ANFIS over ANN in terms of performance measures.