Predefined-time collision avoidance adaptive leader-follower formation control for nonlinear multiagent systems

Dongyang Liu, Zhi Liu, Lei Yan, C. L. Philip Chen, Ci Chen

Abstract: This paper investigates predefined-time collision avoidance adaptive leader follower formation control for nonlinear multiagent systems (MASs) with unmeasurable states. The practical predefined-time stability (PPTS) criterion is employed to ensure that all system errors, including observer errors and filtering errors, converge within the specified time frame. Prescribed performance functions (PPFs) are implemented to prevent collisions by transforming and constraining errors appropriately, while simultaneously ensuring that the convergence of system errors is achieved within the specified range. System stability is evaluated by integrating the command filter and backstepping technique, preventing the need for repeated differentiation Then, a predefined-time adaptive formation controller with collision avoidance is designed, which also address situations involving unmeasurable states. Finally, simulations using a model of unmanned surface vehicles (USVs) are performed to validate the proposed method.