Adaptive Fuzzy Consistent Pseudoinverse Control for a Class of Constrained Nonlinear Multiagent Systems and Its Application

Abstract

This article focuses on a type of hysteretic nonlinear multiagent system with state constraints. It introduces an adaptive consensus pseudoinverse control scheme based on fuzzy logic systems and barrier Lyapunov functions (BLFs), ensuring that all states of the closed-loop system are strictly confined within predefined constraints. The main features of this study are as follows. First, in order to cope with the hysteresis nonlinearity present in the actuators of multiagent systems, a pseudoinverse control algorithm has been proposed. This approach avoids the direct construction of a hysteresis inverse model. It achieves control by searching for actual control signals in temporary control laws, and it does not rely on the precise model of the system. Therefore, it can adapt more flexibly to the uncertainties in the system. Second, within the framework of this control strategy, the seamless integration of fuzzy control, BLFs, and the hysteresis pseudoinverse algorithm effectively addresses the full-state constraint control issue in the Preisach hysteresis model. The control signals are elegantly represented in the form of a double-integral function, offering a potent solution to the constraints inherent in the Preisach hysteresis model. Third, a multiagent collaborative control experimental platform was established, incorporating quadcopter autonomous aerial vehicles and ground mobile robots. Experimental validation of the proposed control scheme against traditional control approaches demonstrated the effectiveness of the proposed control strategy in practical applications.