earticle

영어

This paper examines secure uncertain robot which performance is improved secure by artificial intelligence based on-line tuning method. Computed like torque (CLT) methodology is selected as a framework to construct the control law and address the better performance and reduce the error in presence of uncertainty in any trajectory. The main goal in security in any industrial factory is to guarantee acceptable trajectories tracking between the robot arm actual output and the desired input in presence of uncertainty and external disturbance. The proposed approach effectively combines the design technique from computed torque methodology is based on nonlinear stable system and fuzzy estimator to estimate the nonlinearity of undefined system dynamic in uncertain robot. The input represents the function between error and the rate of error. The outputs represent actual trajectory to improve the security, respectively. The fuzzy partly sliding switching methodology is on-line tune the computed torque like method based on adaptive methodology. The performance of the computed torque like method which controller coefficient is on-line tuned by fuzzy partly sliding switching algorithm (ACTLM) is validated the security through comparison with computed torque like methodology (CTLM). Simulation results signify good performance of trajectory in presence of uncertainty and external disturbance; it is used to show guarantee the security.