This paper comes up with a novel Fast Terminal Sliding Mode Control (FTSMC) for robot manipulators. First, to enhance the response, fast convergence time, against uncertainties, and accuracy of the tracking position, the novel Fast Terminal Sliding Mode Manifold (FTSMM) is developed. Then, a Supper-Twisting Control Law (STCL) is applied to combat the unknown nonlinear functions in the control system. By using this technique, the exterior disturbances and uncertain dynamics are compensated more rapidly and more correctly with the smooth control torque. Finally, the proposed controller is launched from the proposed sliding mode manifold and the STCL to provide the desired performance. Consequently, the stabilization and robustness criteria are guaranteed in the designed system with high-performance and limited chattering. The proposed controller runs without a precise dynamic model, even in the presence of uncertain components. The numerical examples are simulated to evaluate the effectiveness of the proposed control method for trajectory tracking control of a 3-Degrees of Freedom (DOF) robotic manipulator.

The control of a parallel robotic manipulator with uncertain dynamics is a noteworthy challenge due to the complicated dynamic model; multi-closed-loop chains; and singularities. This study develops a Synchronization Full-Order Terminal Sliding Mode Control (S-FOTSMC) for a 3-DOF planar parallel robotic manipulator with uncertain dynamics. First, to achieve faster convergence of position error and synchronization error variables with minimum values at the same time, a Synchronization Full-Order Terminal Sliding Mode Surface (S-FOTSMS) is constructed in the cross-coupling error’s state space. Next; an integral of the switching control term is applied; that means, a continuous control term is extended for rejecting the effects of chattering. Finally, an SFOTSMC is designed to guarantee that sliding mode motion will occur. Consequently, the stability and the robustness of the proposed method are secured with high-performance irrespective of the influences of uncertain terms in the robot system. The simulation performances show the effectiveness of our proposed system for position tracking control of a 3-DOF planar parallel robotic manipulator.

This paper proposes a novel chattering free neuro-sliding mode controller for the trajectory tracking control of two degrees of freedom (DOF) parallel manipulators which have a complicated dynamic model, including modelling uncertainties, frictional uncertainties and external disturbances. A feedforward neural network (NN) is combined with an error estimator to completely compensate the large nonlinear uncertainties and external disturbances of the parallel manipulators. The online weight tuning algorithms of the NN and the structure of the error estimator are derived with the strict theoretical stability proof of the Lyapunov theorem. The upper bound of uncertainties and the upper bound of the approximation errors are not required to be known in advance in order to guarantee the stability of the closed-loop system. The example simulation results show the effectiveness of the proposed control strategy for the tracking control of a 2-DOF parallel manipulator. It results in its being chattering-free, very small tracking errors and its robustness against uncertainties and external disturbances.

The objective of this article is to present a method to model the mechanics of robot manipulators. A complete description of the procedure to model and control a two-link planar robot arm is detailed and simulated using Matlab/Simulink from the generation of a mechanical model in SimMechanics Toolbox. One of the simplest position controllers for robot manipulators is the PD control with desired gravity compensation. The implementation of this method was verified on this model. The results of simulation show that SimMechanics can be used to model the mechanics of robot and the better performance can be obtained with the online gravity compensation method as compared to the case of constant gravity compensation method.