Adaptive event-triggered control for uncertain strict-feedback nonlinear systems with actuator faults: a fully actuated system approach

Within this study, an adaptive control strategy based on the fully actuated system approach is designed for strict-feedback nonlinear systems containing actuator faults. Firstly, to lower the complexity of the algorithm, we transform the studied strict-feedback nonlinear system into the fully actuated system form via state transformation. Then, radial basis function neural networks and adaptive estimation strategies are introduced to deal with unknown nonlinear functions and actuator fault parameters, which improves the fault tolerance of the system. Then, with the purpose of reducing the control cost, this paper adds the control method of handling event-triggered inputs to the control strategy. Furthermore, this paper extends the designed control strategy to strict-feedback nonlinear systems containing unknown coefficients. Finally, the effectiveness of the control strategies is demonstrated by the simulation of a chemical reaction system.