Adaptive Fractional-Order Fault-Tolerant Coordinated Tracking Control of Heterogeneous Multiagent Systems Against Multiple Faults Under Deception Attacks

Abstract

This article addresses the issue of the adaptive fractional-order fault-tolerant coordinated tracking control (FO-FTCTC) for multiple unmanned aerial vehicles and unmanned ground vehicles with fixed-time prescribed performance subjected to actuator and sensor faults under deception attacks. Deception attacks disrupt the sensor network, making the output and state unavailable. To achieve the tracking control of the system, the coordinate transformation method is developed, in which the attack gains are considered and the compromised states are utilized to design a control scheme. Then, the fixed-time prescribed performance function (PPF) is illustrated to transform the coordinated tracking errors (CTEs) into another error variable so that the unconventional errors are limited to the prescribed range. Next, the sliding-mode surface is built by utilizing the errors and fractional calculus. In addition, the radial basis function neural network is utilized to deal with the unknown term. Based on the error, the adaptive FO-FTCTC scheme by utilizing the radial basis function neural network (RBFNN), fractional calculus, and fixed-time PPF with prescribed performance can be achieved, which can strengthen the system performance. Based on the Lyapunov function approach, all vehicles can coordinately track their desired references and CTEs can be bounded within the prescribed boundary. Finally, simulation studies are provided to verify the validity of the developed FO-FTCTC scheme.