AN INTELLIGENT CONTROLLER USING FUZZY LOGIC AND ARTIFICIAL NEURAL NETWORK IN SHP

Abstract

Over the last decade an extensive research has been carried out in the areas of fuzzy logic and neural network. Fuzzy logic (FL) has emerged as a mathematical tool to deal with uncertainties in human perception and reasoning. It also provides a framework for an inference mechanism that allows for approximate human reasoning capabilities to be applied to knowledge-based systems. On the other hand, artificial neural networks (ANN) have emerged as fast computation tools with learning and adaptation capabilities. The hydraulic turbine speed is usually controlled by conventional Proportional-Integrative-Derivative (PID) controller and emerging technologies such as ANN and FL have received much attention in the control area in recent years. These techniques have been claimed to yield excellent results for some applications. An integrated model of a hydropower plant is used to study its dynamic response of wicket gate opening when having different types of hydraulic turbine's speed error. The emerging control technologies which utilize ANNs and FL are compared with conventional PID control for the speed control of hydraulic turbine. The performance of the control techniques is compared in terms of rise time, smoothness of response, settling time and overshoot in wicket gate opening with response to change in turbine speed.