Interval Type-2 Fuzzy Adaptive Sliding Mode Controller for 6-dof Parallel Manipulator In Cartesian Space Coordinates

this paper proposes an interval type-2 fuzzy adaptive sliding mode controller in Cartesian space Coordinates for trajectory tracking of 6-dof parallel manipulator. 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 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 Interval type-2 fuzzy approximators to estimate the plant’s unknown nonlinear functions, and robustifying control terms to compensate of approximation errors, so that semi-global stability and asymptotic convergence to zero of tracking errors can be guaranteed. Simulation results verify that the proposed control strategy can achieve favorable control performance with regard to uncertainties, nonlinearities and external disturbances.

Keywords:

Adaptive control , sliding mode control , Interval type-2 fuzzy set , 6-dof parallel manipulator