In the presence of external disturbances, a backstepping control scheme based a genetic algorithm (GA) is built with the objective of tracking a desired trajectory of robot manipulators. The nonlinear-coupled higher order dynamic model of an n-link robot manipulator is first briefly presented. Then, a traditional backstepping control system (BSC) creates a two-link robotic manipulator position tracking control. Furthermore, a mix of nonlinear control and artificial intelligence is suggested for manipulator robot control. To determine the optimal control parameters, the backstepping controller is combined with the genetic algorithm, a metaheuristics-based optimization technique. The effectiveness of the suggested optimal control strategy based on backstepping approach and GA in trajectory tracking problems, such as a good angle tracking and a good disturbance rejection capability, is demonstrated by numerical simulations using the dynamic model of a two-link planar rigid robot manipulator.
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