Event‐triggered model predictive control for multi‐vehicle systems with collision avoidance and obstacle avoidance
Hongjiu Yang, Qing Li, Zhiqiang Zuo, Hai Feng Zhao
Abstract
Abstract In this article, event‐triggered model predictive control is used for simultaneous tracking and formation of a multi‐vehicle system with collision avoidance and obstacle avoidance. An event‐triggered mechanism is established to reduce computational burden in the model predictive control strategy. A compatibility constraint is proposed to guarantee collision avoidance and convergence for the multi‐vehicle system by limiting an uncertainty deviation of each vehicle. Between each vehicle and obstacles, a safe distance is ensured by a robust obstacle avoidance constraint. Finally, effectiveness and advantages of the proposed strategy are shown by two simulation examples.
Topics & Concepts
Collision avoidanceObstacle avoidanceModel predictive controlControl theory (sociology)Computer scienceObstacleConstraint (computer-aided design)Event (particle physics)Collision avoidance systemControl (management)CollisionEngineeringArtificial intelligenceMobile robotMechanical engineeringPolitical scienceComputer securityQuantum mechanicsLawRobotPhysicsAdvanced Control Systems OptimizationRobotic Path Planning AlgorithmsVehicle Dynamics and Control Systems