Authors : Mohahammad Javad Tajadini and Majid Mohammadi
Abstract: The use of the optimization technologies for the two degree of freedom control for Robot manipulators 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 for maximizing or minimizing the objective function and this is a very tedious task when the number of membership functions is too many or the system dynamicity is very slow. In the present study, the optimized output membership functions have been identified through combining the genetic algorithm and fuzzy logic, based on the input membership functions for two degrees of freedom control robot manipulators. The method has been the use of genetic algorithm for finding the optimum parameters in the Sugeno Fuzzy Logic Method. The objective function in such a problem is in the form of a system of various objectives and goals of two degrees of freedom controls for robot manipulators. The main objective of the current study is to make use of a Genetic algorithm method to mechanize the design and reach to an optimum regulation of the membership functions and therefore the scientific considerations regarding the regulation and design through the use of scaling coefficients along with the fuzzy control for the two degrees of freedom controls for robot manipulators have been presented here.
Mohahammad Javad Tajadini and Majid Mohammadi, 2016. Optimize and Control the Robot with Two Degrees of Freedom Using Scaling Coefficients Set Membership Functions Using Genetic Algorithm. International Journal of Signal System Control and Engineering Application, 9: 1-10.