Prescribed-Time Extended State Observer-Based Bipartite Formation Control of Vehicle Multi-Agent Systems
Yang Yang, Tianqi Yang, Shicai Zhou, Wei Sun, Defeng Wu
Abstract
Formation control is one of critical topics in cooperative control. In this paper, we design a prescribed-time bipartite formation control strategy for vehicle multi-agent systems with external disturbances and internal unknown dynamics. A prescribed-time extended state observer (PTESO) is developed to compensate for total disturbances in a prescribed time, and the convergence time can be set in advance for different initial conditions. In order to make the formation error converge in a prescribed time, two novel time functions are introduced and applied to the control strategy. A prescribed-time control strategy with PTESO is developed for bipartite vehicle formation, and the relationship of the convergence time between PTESO and formation error is illustrated. Stability analysis shows the observation error and bipartite formation error are steered to converge their prescribed time, respectively. Furthermore, simulations are conducted to demonstrate the effectiveness of the prescribed-time bipartite formation control strategy. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper presents a prescribed-time bipartite formation control strategy for vehicle multi-agent systems with external disturbances and internal unknown dynamics. The total disturbance of each agent is compensated by a prescribed-time extended state observer (PTESO). In this PTESO, the convergence time is adjustable in advance for different initial conditions, and the peak phenomenon, caused by large gains, is avoided owing to adjustable and smaller time-varying gains. Two novel prescribed-time functions are proposed for vehicle MASs. The proposed functions remove the requirement that calculating gains mathematically, and the issue of jumping variation, caused by modifying coefficients in traditional prescribed-time functions arbitrarily, is also addressed. This strategy provides a feasible strategy for industrial applications.