Fuzzy Adaptive Sliding Mode Control of 6 DOF Parallel Manipulator with Electromechanical Actuators in Cartesian Space Coordinates

Abstract

This paper proposes a fuzzy adaptive sliding mode controller in Cartesian space coordinates for trajectory tracking of the 6 DOF parallel manipulator with considering dynamics of electromechanical actuators. The 6-DOF sensors, may be very expensive or impossible to find at the desired accuracies; and also, especially at constant speeds, will contain errors; therefore, it is better to use LVDT position sensors and then, solving the forward kinematics problem using an iterative artificial neural network strategy, Instead of using the Numerical methods such as the Newton-Raphson method, that heavy computational load imposes to the system. This controller consists of a sliding mode control and adaptive learning algorithms to adjust uncertain parameters of system, that relax the requirement of bounding parameter values and not depending upon any parameter initialization conditions, and fuzzy approximators to estimate the plant's unknown nonlinear functions, and robustifying control terms to compensate of approximation errors; so that closed-loop stability and finite-time convergence of tracking errors can be guaranteed. Simulation results demonstrate that the proposed control strategy can achieve favorable control performance with regard to uncertainties, nonlinearities and external disturbances.