Development of a Genetic Algorithm Toolkit in LabVIEW

Abstract

It is a well known fact that LabVIEW is one of the finest tools for measurement and control applications. Requirement of intelligent controller tuning methods like Genetic Algorithm (GA) has been felt at times in the LabVIEW environment as there is no standard LabVIEW GA toolkit supplied with the package. In this paper, a GA Toolkit developed in LabVIEW environment, has been presented. The developed toolkit is used for optimizing the gains of the PID (Proportional plus Integral plus Derivative) controller for the given performance indices of a closed loop system. For the purpose of tuning, the algorithm mimics the biological evolution and is used to find the suitable values of PID gains in order to improve the response of the given system. An integrated performance index comprising of rise time, settling time, overshoot, integral absolute error (IAE), integral square error (ISE), integral time weighted absolute error (ITAE) or a combination of these forms the objective function for the optimization. In this toolkit four selection methods, three crossover methods and three mutation methods have been incorporated. To test the developed toolkit a simulation example is also performed and results have been presented.