Finite-time prescribed performance tracking control of nonlinear systems based on a Novel disturbance observer

For a class of strict-feedback nonlinear systems with external disturbances, the problem of finite-time prescribed performance tracking control is investigated based on a novel disturbance observer. For the first time, a novel neural network disturbance observer is proposed, which can precisely observe disturbances and limit the observation errors within an extremely small boundary. Second, under the framework of the backstepping method, combined with the finite-time prescribed performance function, a finite-time prescribed performance tracking controller is derived. This controller ensures that the output tracking error converges to the prescribed boundary range within a finite-time and all the signals in the closed-loop system remain bounded. Meanwhile, a command filter and a compensation mechanism are adopted to address the issues of “differential explosion” and filtering errors. Finally, the simulation examples verifiy the effectiveness of the design scheme.