Adaptive Neural Fault-Tolerant Control for Nonlinear Fractional-Order Systems with Positive Odd Rational Powers

Abstract

In this paper, the problem of adaptive neural fault-tolerant control (FTC) for the fractional-order nonlinear systems (FNSs) with positive odd rational powers (PORPs) is considered. By using the radial basis function neural networks (RBF NNs), the unknown nonlinear functions from the controlled system can be approximated. With the help of an adaptive control ideology, the unknown control rate of the actuator fault can be handled. In particular, the FNSs subject to high-order terms are studied for the first time. In addition, the designed controller can ensure the boundedness of all the signals of the closed-loop control system, and the tracking error can tend to a small neighborhood of zero in the end. Finally, the illustrative examples are shown to validate the effectiveness of the developed method.

Fixed-Time Group Consensus Control of Multi-Agent Systems With Actuator Faults Based on Dynamic Event Triggering

“…In this case, how to maintain the normal operation of the system became an important research direction. In [17], Yang et al designed an adaptive fault-tolerant control protocol to eliminate the impact of actuator faults on the system by adjusting coupling gain online through an adaptive mechanism. By constructing a distributed adaptive fault-tolerant controller in the physical layer and a distributed pulse controller in the communication layer, Zhao et al dealt with the effects of actuator faults and spoofing faults on the system in [18].…”