4.8 Article

Null-Space-Based Time-Varying Formation Control of Uncertain Nonlinear Second-Order Multiagent Systems With Collision Avoidance

期刊

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
卷 70, 期 10, 页码 10476-10485

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2022.3217585

关键词

Task analysis; Collision avoidance; Trajectory; Time-varying systems; Stability analysis; Convergence; Behavioral sciences; Collision avoidance (CA); fixed-time control; multiagent systems (MASs); null-space-based behavioral (NSB) control; sliding mode controller; time-varying formation

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In this article, a novel and flexible time-varying formation task strategy is proposed for the time-varying formation control problem with collision avoidance in uncertain nonlinear second-order multiagent systems. The proposed method utilizes agent radius and a sine function to accurately describe collision risk. Two fixed-time sliding mode controllers with constant and variable exponent coefficients are also proposed to track the desired trajectory. Theoretical results for the task design and trajectory tracking are obtained using the Lyapunov stability theory.
In this article, the time-varying formation control problem with collision avoidance is addressed for uncertain nonlinear second-order multiagent systems in a null-space-based behavioral control architecture. To guarantee the tracking and coordination performance simultaneously, a novel and flexible time-varying formation task strategy is designed where only neighborhood information is necessary. Moreover, the agent radius and a sine function are introduced such that the collision avoidance task function describes collision risk more accurately in contrast to existing results. Then, two fixed-time sliding mode controllers with constant and variable exponent coefficients, respectively, are proposed to track the desired trajectory generated by null space projection. Also, the theoretical results for the task design and trajectory tracking are obtained by using the Lyapunov stability theory. Numerical simulation and practical experiments are finally conducted to illustrate the effectiveness and superiority of the proposed method.

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