Design of an Optimal Fuzzy LQR Controller Using Genetic Fuzzy Rule Set Selection for an Overhead Crane

Overhead crane is an industrial structure that used widely in many harbors and factories. It is usually operated manually or by some conventional control methods. In thispaper, a hybrid controller that includes both position regulation and anti-swing control is proposed. According to Takagi-Sugeno fuzzy model of an overhead crane and geneticalgorithm, a fuzzy controller is designed with parallel distributed compensation and Linear Quadratic Regulation.Using genetic algorithm (GA), the number of fuzzy rules and also design procedure computation are reduced. Further, in controller design procedure, it is tried to design the best LQR controller. The stability of the overhead crane with the parallel distributed fuzzy LQR controller is discussed. Thestability analysis and control design are reduced to linear matrix inequality (LMI) problems. Simulation results illustrated the validity of the parallel distributed fuzzy LQR control method

Design of an Optimal Fuzzy LQR Controller Using Genetic Fuzzy Rule Set Selection for an Overhead Crane Keywords:

parallel distributed compensation , Takagi_Sugeno fuzzy modeling , overhead crane , linearmatrix inequality , Linear Quadratic Regulation , Genetic algorithm