Neural networks L2-gain control for robot system

A new L₂-gain disturbance rejection controller and adaptive adjustment are combined into a hybrid robust control scheme, which is proposed for robot tracking control systems. The proposed controller deals mainly with external disturbances and nonlinear uncertainty in motion control. A neural network (NN) is used to approximate the uncertainties in a robotic system. Meanwhile, the approximating error of the NN is attenuated to a prescribed level by the adaptive robust controller. The adaptive techniques of NN will improve robustness with respect to uncertainty of system, as a result, improving the dynamic performance of robot system. A simulation example demonstrates the effectiveness of the proposed control strategy.