Control of overhead crane by fuzzy-PID with genetic optimisation

Abstract

A fuzzy logic controller with the fuzzy knowledge base: scaling factors of the input/output variables, membership functions and the rules are optimized by the use of the genetic algorithms, is presented in this work, and its application in the highly nonlinear systems. The fuzzy structure is specified by a combination of the mixed Sugeno's and Mamdani's fuzzy reasoning. The mixed, binary-integer, coding is utilized to construct the chromosomes, which define the set of necessary prevailing parameters for the conception of the desired controller. This new controller stands out by a non standard gain (output scaling factor) which varies linearly with the fuzzy inputs. Under certain conditions, it becomes similar to the conventional PID controller with non-linearly variable coefficients. The results of simulation show, well, the efficiency of the proposed controller. © 2004 Springer Science + Business Media, Inc.