Adaptive Disturbance Rejection Sliding Mode Control for Robots via an Orthogonal Functions-Based Estimator

This paper presents an innovative adaptive sliding mode controller with disturbance rejection for robotic manipulators. The proposed approach employs orthogonal functions-based estimation to handle system uncertainties, while an adaptive mechanism is introduced to estimate the unknown upper bounds of external disturbances. Moreover, the dynamics of the robot actuators, namely the motors, are explicitly considered in the control law design. Three adaptive laws are proposed in this work. The first addresses the estimation of the parameters of orthogonal functions, the second deals with the approximation error, and the third concerns the estimation of the upper bound of external disturbances. Furthermore, a robust control term is proposed to compensate for the approximation error. Stability of the closed-loop system is ensured using Lyapunov theory. The performance of the proposed controller is evaluated through simulations on a SCARA robotic manipulator and compared with conventional and dynamic sliding mode control schemes in terms of tracking accuracy, control effort, and disturbance rejection.

کلیدواژه ها:

Uncertainty Estimation ، Orthogonal functions ، adaptive sliding mode control ، Trajectory tracking ، Robot Manipulators