Robust adaptive fault-tolerant tracking for uncertain output-constrained nonlinear systems with unknown time-varying powers and application to the reduced-order dynamical model of a boiler-turbine unit

This paper devotes to proposing a robust adaptive fault-tolerant tracking control scheme for a class of output-constrained uncertain nonlinear systems with unknown time-varying powers. The motivation is to enable the tracking accuracy and the settling time to be arbitrarily prescribed while constructing a compact set large enough in which the approximation of any unknown continuous function by neural networks (NNs) is effective. Using a serial of time-varying gain filters and scaling time-varying functions, an exquisite controller is constructed by integrating NNs approximation and the dynamic surface control (DSC) technology. The designed controller is not only strongly robust to compensate external disturbances and actuator faults, but also drives the tracking error to enter a prescribed neighborhood of the origin within an arbitrarily prescribed time while satisfying the prescribed time-varying output constraint without constructing the barrier functions. Finally, two practical examples are provided to demonstrate the application of the proposed strategy.