Abstract:
This thesis proposes a grey system theory based fuzzy PID controller that has a prediction capability. Although fuzzy control theory and grey system theory have completely different mathematical basics, both deal with uncertain information. In the thesis, a short description of both are given and their performance are compared on a non-linear liquid level control system. The grey model developed is examined under several different conditions and it is shown that the proposed grey fuzzy PID controller has better self-adapting characteristics. The simulation results indicate that the proposed controller has the ability to control the non-linear system accurately with a little amount of overshoot and with no steady-state error. It has, in these respects, better performance than the conventional controllers. The thesis is also intended to serve as a first reading on grey system theory and grey prediction based controllers. The fundamental concepts and mathematical basics of grey system theory are therefore explained in simple terms.
