Journal Press India^®

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As the number of connections and the complexity of the manipulator system rose, it became more difficult for the control engineers to manage such a manipulator system, requiring the employment of a separate control system to govern the manipulator's position and velocity. Using different mathematical equations, this work investigates a self-tuned fuzzy PID (STFPID) controller that is capable of following trajectories and suppressing noise. A dynamic model for a two-link stiff robotic manipulator has been built in Simulink and used to drive the plant, and the STFPID controller is being used to do so. Genetic Algorithm is being used to tune the controller and we are using IAE (integral absolute errors) as an objective function in order to obtain the least amount of error and we have determined that STFPID has the least value of error as compared to the other three controllers. A fuzzy logic controller's ability to manage uncertainty is facilitated by its ability to climb in time quickly and to minimize overshoot.

Keywords

Self Tunned Controller; Objective Function; Integral Absolute Error; Dynamic Modelling; Genetic Algorithm

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