Neuro-sliding mode control of robotic manipulators

In this paper, a synergistic combination of neural networks with sliding mode control (SMC) is proposed. As a result, the chattering is eliminated and error performance of SMC is improved. In such an approach, two parallel NNs are proposed to realize SMC. The equivalent control and the corrective term of SMC are the outputs of the NNs. The gradient descent method is used for the weight adaptation. This novel approach is applied to control of a SCARA type robot manipulator and simulation results are given.