TY  - JOUR
T1  - Optimize and Control the Robot with Two Degrees of Freedom Using Scaling
Coefficients Set Membership Functions Using Genetic Algorithm
AU - Tajadini, Mohahammad Javad AU - Mohammadi, Majid 
JO  - International Journal of System Signal Control and Engineering Application
VL  - 9
IS  - 1
SP  - 1
EP  - 10
PY  - 2016
DA  - 2001/08/19
SN  - 1997-5422
DO  - ijssceapp.2016.1.10
UR  - https://makhillpublications.co/view-article.php?doi=ijssceapp.2016.1.10
KW  - Fuzzy control
KW  -Genetic algorithm
KW  -robot manipulator (arms)
KW  -degree
KW  -robot
AB  - 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.
ER  -