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This study investigates the fixed-time and prescribed-time optimal formation control strategies for heterogeneous multiagent systems composed of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) unde actuator faults. In the proposed control framework, the critic-actor framework is designed to finish the optimization tracking. Radial basis function neural network (RBFNN) is implemented to derive the tracking control, in which the actor RBFNN is utilized to make up for the actuator faults and generate the formation control action, and the critic RBFNN is utilized to evaluate the execution cost. Then, a Lyapunov-based tracking technique is designed to ensure the fixed-time stability of the tracking error. Since the adaptive updating protocols are developed by deriving the gradient descent of the cost function, the optimized control algorithm can be obtained. In addition, a prescribed-time fault-tolerant optimal controller is further proposed, which renders the convergence time fully independent of any other parameter and the initial states, thus the convergence time can be uniformly prespecified. Finally, the validity of the proposed algorithms are demonstrated via the simulation experiments. Note to Practitioners—Actuator faults often occur in the operation of industrial automation equipment. Hence, it is of great practical significance for control systems to have faster fault-tolerant performance. In addition, the optimization effect of performance indicator often denotes the quality of the expected task completion. Therefore, this study proposes a faster optimal fault-tolerant formation strategy for heterogeneous unmanned formation system based on fixed-time and prescribed-time theorems under actuator faults. The effectiveness of the developed control approach is verified by designed simulation.

In this article, the distributed adaptive fixed-time output time-varying formation tracking issue of heterogeneous multiagent systems (MASs) with actuator faults is addressed, in which the followers suffer from loss-of-effectiveness actuator faults, and the leader has unknown bounded input. To solve the above issue, a distributed fixed-time observer is constructed with the leader’s unknown input, by which each follower can obtain the leader’s states in a predesigned time. Then, based on the observer and the desired formation vector, a local adaptive fixed-time fault-tolerant formation control algorithm is proposed for each follower with the help of time-varying gains to make up for the influence of actuator faults. Furthermore, it is proven that the designed controller can satisfactorily accomplish the considered task of the heterogeneous MASs by using the Lyapunov stability theory. Specifically, the obtained upper bound of the convergence time only depends on a few controller parameters. Finally, a simulation example is implemented to validate the efficiency of the analytical results.