Abstract
Tuning the parameters of a PID controller is very important in PID control. Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of a PID controller. This tuning method is very simple, but cannot guarantee to be always effective. For this reason, this paper investigates the design of self tuning for a PID controller. The controller includes two parts: conventional PID controller and fuzzy logic control (FLC) part, which has self tuning capabilities in set point tracking performance. The proportional, integral and derivate (KP, KI, KD) gains in a system can be self-tuned on-line with the output of the system under control. The conventional PI controller (speed controller) in the Chopper-Fed DC Motor Drive is replaced by the self tuning PID controller, to make them more general and to achieve minimum steady-state error, also to improve the other dynamic behavior (overshoot). Computer Simulation is conducted to demonstrate its performance and results show that the proposed design is success over the conventional PID controller. Keywords: PID controller, Fuzzy logic control, Self tuning controller, Chopper fed-DC motor drive.
Highlights
Tuning the parameters of a PID controller is very important in PID control
The Fuzzy self tuning of a PID controller shown in fig.2 was designed and simulated for chopper fed-DC motor drive
By tuning the gains of the conventional PID controller and producing the optimum response using trial and error method, the simulation start with the best initial gains as the following: KP =25, KI =0.75, KD =0.5 and the scaling gain Ke=0.01, KΔe=0.05
Summary
The basic structure of the PID controller is first described in the flowing equations as well as fig.. This paper proposed two inputs-three outputs self tuning of a PID controller. The controller design used the error and change of error as inputs to the self tuning, and the gains (KP1, KI1, KD1) as outputs. The control action of the PID controller after self tuning can be describing as:. The seventh triangular input and output member ship functions of the fuzzy self tuning are shown in the figs. Tables (1), (2), and (3) show the control rules that used for fuzzy self tuning of PID controller [7]. J 1 for defuzzification [8]: Where u(uj) member ship grad of the element uj, u(nT) is the fuzzy control output, n is the number of discrete values on the universe of discourse
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