Adaptive Fault-Tolerant Control for Nonlinear Systems With Multiple Sensor Faults and Unknown Control Directions

Abstract

This paper investigates the problem of adaptive fault-tolerant control for a class of nonlinear parametric strict-feedback systems with multiple unknown control directions. Multiple sensor faults are first considered such that all real state variables are unavailable. Then, a constructive design method for the problem is set up by exploiting a parameter separation and regrouping technique. To circumvent the main obstacle caused by the coupling effects of multiple unknown control directions and sensor faults, a region-dependent segmentation analysis method is proposed. It is proven that the closed-loop system is globally exponentially stable. Simulation results are presented to illustrate the effectiveness of the proposed scheme.

Global finite‐time output stabilization of nonlinear systems with unknown measurement sensitivity

“…In view of the accuracy of sensor measurements playing a crucial role in feedback control, a challenging issue on robust nonlinear control under imprecise sensor measurements naturally emerged. To surmount it, a series of innovative and effective approaches were proposed . A dual‐domination method was presented in the work of Chen et al to achieve global stabilization.…”

“…A suboptimal reliable mixed output‐feedback control law was developed by Wu and Zhang, which was further extended to guarantee asymptotic stability . Several adaptive compensation strategies were provided within the works of Zhai et al, Zhang and Yang, and Jin to accomplish stabilization.…”

“…It is unclear whether the methods proposed therein can be extended to nonlinear systems or not. Second, the derivative bound of the measurement sensitivity needs to be known in the work of Zhai et al Such prior knowledge, however, is difficult to be acquired in practical applications. Third, the partially known system nonlinear functions or their bounding functions were required in the works of Chen et al, Zhai et al, and Jin .…”

“…Second, the derivative bound of the measurement sensitivity needs to be known in the work of Zhai et al Such prior knowledge, however, is difficult to be acquired in practical applications. Third, the partially known system nonlinear functions or their bounding functions were required in the works of Chen et al, Zhai et al, and Jin . An intrinsic reason for the prohibition of completely unknown nonlinear dynamics is that the existing approximation‐based techniques are no longer feasible in the presence of measurement errors.…”

“…In a preliminary work, the constant measurement sensitivity was assumed such that fuzzy or neural systems are applicable, ie, where s = γ x denotes the sensor measurement of state x , and γ stands for the measurement sensitivity. γ is commonly time varying as discussed in other works …”