Adaptive neural network control of non-affine multi-agent systems with actuator fault and input saturation

An adaptive neural network fault-tolerant control method is proposed for the non-affine multi-agent systems with actuator failure and input saturation. Through the transformation of the original multi-agent systems, an equivalent model is proposed. Considering that the signal input of multi-agent systems is limited, this article will solve the input saturation problem. But in a real system, the actuator would probably fail. Therefore, a fault tolerant control algorithm is proposed to solve the fault problem in the systems. In this article, an adaptive distributed controller is designed to eliminate the uncertainty of the systems. At the same time, the integral barrier Lyapunov function is selected to verify the stability. Finally, a simulation example is given to demonstrate the effectiveness of the proposed method.