Fuzzy-Approximation Adaptive Fault Tolerant Control for Nonlinear Constraint Systems With Actuator and Sensor Faults

The key focus in this article is to develop an adaptive fuzzy function constraint control method for nonlinear systems with actuator and sensor faults. The effectiveness indicators of actuator and sensor are considered as the unknown functions with the bounded time-varying bias fault existing in actuator. Because system states are not applied to design controller, how to achieve constraints on the system states is a significant challenge. In order to cope with this challenge, the constraint target transformation is introduced to convert the constraints on real states to measurement variables. Then, the nonlinear state-dependence mapping is used to ensure tracking error and system states remain within the given function constrain ranges. In contrast to the existing time-dependence constraint methods, this article considers that the constraint boundaries are related to not only time but also state variables, which extend the application fields for practical systems. Moreover, the deferred transformation function is employed to remove the restrictive condition that the initial values of system states must be within the constraint regions. Finally, the effectiveness of the developed method is confirmed by two simulation examples including the numerical example and wastewater treatment process.