Neural sliding mode controller of uncertain robot manipulators using H∞ method

An adaptive neural robust controller based on H_∞ method is presented for trajectory of uncertain robot manipulators. An RBF neural network is used to compensate the plant parameter uncertainties, in addition, sliding-mode control action is included to eliminate the effect of approximation error via neural network approximation and the H_∞ tracking performance ensures the robust stability that under a prescribed attenuation level for external disturbance. The simulation shows that the control law can guarantee fast convergence of trajectory tracking error as well as robustness for parameter uncertainties and external disturbances.