Optimize and Control the Robot with Two Degrees of Freedom Using ScalingCoefficients Set Membership Functions Using Genetic Algorithm

摘要

The use of the optimization technologies for the two degree of freedom control for Robotmanipulators is a new idea and there have been applied various methods for controlling and optimizing robots.The general theorem in such optimization methods is the determination of the decision variables amounts formaximizing or minimizing the objective function and this is a very tedious task when the number of membershipfunctions is too many or the system dynamicity is very slow. In the present study, the optimized outputmembership functions have been identified through combining the genetic algorithm and fuzzy logic, based onthe input membership functions for two degrees of freedom control robot manipulators. The method has beenthe use of genetic algorithm for finding the optimum parameters in the Sugeno Fuzzy Logic Method. Theobjective function in such a problem is in the form of a system of various objectives and goals of two degreesof freedom controls for robot manipulators. The main objective of the current study is to make use of a Geneticalgorithm method to mechanize the design and reach to an optimum regulation of the membership functions andtherefore the scientific considerations regarding the regulation and design through the use of scalingcoefficients along with the fuzzy control for the two degrees of freedom controls for robot manipulators havebeen presented here.