Hybrid Fuzzy FED PID Control of Nonlinear Systems

Abstract

PID control is widely used in industrial applications although it is a simple control method. Stability of PID controller can be guaranteed theoretically, and zero steady-state tracking error can be achieved for linear plant in steady-state phase. Computer simulations of PID control algorithm have revealed that the tracking error is quite often oscillatory, however, with large amplitudes during the transient phase. To improve the performance of the PID controllers, several strategies have been proposed, such as adaptive and supervising techniques. Fuzzy control methodology is considered as an effective method to deal with disturbances and uncertainties in terms of ambiguity. Fuzzy PID controller combining fuzzy technology with traditional PID control algorithm to become more effective in artificial intelligence control [1],[2]. The most common problem resulted early depending on the complexity of Fuzzy Logic Control (FLC) is the tuning problem. It is hard to design and tune FLCs manually for the most machine problems especially used in industries like nonlinear systems. For alleviation of difficulties in constructing the fuzzy rule base, there is the conventional nonlinear design method [3] which was inherited in the fuzzy control area, such as fuzzy sliding control, fuzzy scheduling [4],[5], and adaptive fuzzy control [6],[7]. The error signal for most control systems is available to the controller if the reference input is continuous. The analytical calculations present two-inputs FLC employing proportional error signal and velocity error signal. PID controller is the most common controller used in industries, most of development of fuzzy controllers revolve around …