PID controller tuning with genetic algorithms position control of planar mechanisms

Genetic Algorithms (GAs) are adaptive methods based on the genetic processes of biological organisms. GAs are included in family of computational models inspired by evolution. Three different phases of search happens in GA; an initial population is created, a fitness function is evaluated and a new population is produced. Three operators are available; reproduction, crossover, mutation.In this study, GAs are used to determine Proportional-Integral-Derivative (PID) controller parameters. The results are implemented to position control of planar mechanisms. MATLAB Genetic algorithm Toolbox is used during the study. Two example applications are performed; four bar mechanism (SISO) system and the hybrid actuator (MISO) system. Series of numerical simulations are carried out on the mathematical models inclusion of the actuator dynamics; Brushless dc servo motor (BLDC) and permanent magnet dc motor (PMDC) are taken in the application and satisfactory results are obtained in position control of Planar Mechanisms.