Abstract:

In this paper, a novel control method is proposed in order to control the trajectory of two link robotic manipulator. The model of the manipulator has some unknown parameters because of the elasticity of the used materials for robot manipulator. Besides the robotic manipulators are generally open for the external disturbances. Radial basis function neural networks are employed in order to model these unknown parameters. The controller structure for trajectory tracking for the robot manipulator is based on robust and adaptive Sliding Mode Control (SMC). The coefficients of the SMC is calculated by the help of evolutionary algorithm, namely genetic algorithm. The proposed algorithm guarantees that the tracking error converges to zero in a finite time. The stability of the closed loop system is ensured by Lyapunov Theory. Numerical simulations have been conducted in Matlab/Simulink environment to demonstrate the validity of the proposed controller. Moreover, effectiveness and validity of the proposed control method is confirmed by comparative simulation results. The conducted experiments are demonstrated that proposed controller has disturbance rejection, chattering free, robust and fast property when we compared with other approaches in the literature.

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