Self-tuning of PID-type fuzzy logic controller coefficients via relative rate observer

A New Method for Tuning PID-Type Fuzzy Controllers Using Particle Swarm Optimization

“…In this section, the considered PID-type FC structures are briefly described within the discrete-time framework based on [11,12,16,26,31].…”

“…Under these conditions, the equivalent proportional, integral and derivative control components of such a PID-type FC are given by αK e P + βK d D, βK e P,andαK d D, respectively, as shown in [16,26,31]. In these expressions, P and D represent relative coefficients, K e , K d , α and β denote the scaling factors associated to the inputs and output of the FC, as shown in Figure 1.…”

“…This work can be considered as an extension of the results given in [11,12,16,26,31]. The fuzzy control design is formulated as a constrained optimization problem which is efficiently solved based on a developed PSO algorithm.…”

“…The particular structure given by Qiao and Mizumoto in [26], namely PID-type FC, is especially established and improved within the practical framework in [11,16,31]. Such a FC structure, which retains the characteristics similar to the conventional PID controller, can be decomposed into the equivalent proportional, integral and derivative control components as shown in [26].…”

“…On the other hand, Woo et al [31] developed a method to tune the scaling factors related to integral and derivative components of the PID-type FC structure via two empirical functions and based on the system's error information. In [12,16], the authors proposed a technique that adjusts the scaling factors, corresponding to the derivative and integral components of the PID-type FC, using a fuzzy inference mechanism. However, the major drawback of all these PID-type FC structures is the difficult choice of their relative scaling factors.…”