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This study presents a new adaptive synchronized computed torque control algorithm based on neural networks for three degree-of-freedom planar parallel manipulators. The basic idea of the proposed control algorithm is to use the incorporation of cross-coupling errors of active joints with the adaptive computed torque control algorithm, online self-tuned neural networks, and error compensators. The key to the success of the proposed approach is to improve the trajectory tracking accuracy of the parallel manipulator’s end-effector while driving the synchronization errors among active joints to zero. The uncertainties of the control system such as modeling errors, frictional terms, and external disturbances are adaptively compensated online during the trajectory tracking of the parallel manipulator. Using the Lyapunov theory, it is proved that the tracking errors and error rates of the overall system asymptotically converge to zero. To demonstrate the effectiveness of the proposed control algorithm, compared simulations are conducted using MATLAB/Simulink [version 2013a] combined with Solidworks 2014.

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.