Work

Adaptive Neural Fault-Tolerant Control for a Class of Stochastic Switched Nonlinear Systems

Year: 2019

Type: article

Abstract: This paper addresses the adaptive neural fault-tolerant control (FTC) problem for a class of stochastic switched nonstrict-feedback nonlinear systems, which have actuator faults that incorporate loss of effectiveness, stuck, and outage. Based on the character of the Gaussian function, the problem of nonstrict-feedback form is solved well. In the process of designing the controller, neural networks (NNs) are utilized to estimate the unknown functions. The problem of actuator faults is handled by designing the FTC method that is obtained by introducing a smooth function and backstepping technique. Then, the control effect satisfies that all the signals in the resulting closed-loop system are bounded and the tracking error converges to a small neighborhood around the origin. To illustrate the high efficiency of the proposed control method, a vivid simulation example is given in the end.

Source: IEEE Access

DOI: 10.1109/access.2019.2927715

Authors: Di Cui, Ben Niu, Dong Yang, Tasawar Hayat, Fuad E. Alsaadi

Institutions: Bohai University, Shandong Normal University, Qufu Normal University, Quaid-i-Azam University, King Abdulaziz University

Language: English

Topic: Adaptive Control of Nonlinear Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,750

Funders: National Natural Science Foundation of China, Natural Science Foundation of Shandong Province