A Framework of Fixed‐Time Trajectory Tracking Control for Multi‐Mobile Robots Leader‐Follower Formation

ABSTRACT This article proposes a control method for multi‐mobile robot formation systems. First, a performance design framework is introduced to ensure that the formation system always meets the prescribed performance bounds (PPB) during operation and avoids constraint violations. Then, the radial basis function (RBF) neural network is employed to approximate the unknown external disturbances, improving the system's stability and performance. To further enhance the system's robustness, a controller based on a smooth switching mechanism is designed. This mechanism ensures efficient neural network approximation within the active domain while switching to a robust control strategy outside the active domain to suppress disturbances and improve fault tolerance. The proposed controller not only handles external disturbances but also guarantees the system state and error signals achieve fixed‐time stability, ensuring efficient control and coordinated motion of the multi‐mobile robots Leader‐Follower formation system. Finally, simulation examples validate the effectiveness and practicality of the proposed method, providing an effective solution to control problems in nonlinear systems with complex external disturbances.