Adaptive tracking control of high-order MIMO nonlinear systems with prescribed performance

In this paper,an observer-based adaptive prescribed performance tracking control scheme is developed for a class of uncertain multi-input multi-output nonlinear systems with or without input saturation.A novel finite-time neural network disturbance observer is constructed to estimate the system uncertainties and external disturbances.To guarantee the prescribed performance,an error transformation is applied to transfer the time-varying constraints into a constant constraint.Then,by employing a barrier Lyapunov function and the backstepping technique,an observer-based tracking control strategy is presented.It is proven that using the proposed algorithm,all the closedloop signals are bounded,and the tracking errors satisfy the predefined time-varying performance requirements.Finally,simulation results on a quadrotor system are given to illustrate the effectiveness of the proposed control scheme.