A robust neural controller for underwater robot manipulator

This paper presents a robust control scheme wing a multilayer neural network. The multilayer neural network acts as a compensator of the conventional sliding mode controller to maintain the control performance when the initial assumptions of uncertainty bounds are not valid. The proposed controller applies to control the robot manipulator operating under the sea which has large uncertainties such as the buoyancy and the added mass/moment of inertia. Computer simulation results show that the proposed control scheme gives an effective path way to cope with an unexpected large uncertainty.