Laguerre Function-Based MPC for Target Interception of Multiagent Systems: A Self-Triggered Approach Using Lyapunov Function

This article addresses the intricate challenge associated with formation control of multiagent systems to achieve target interception employing Laguerre function-based model predictive controller (MPC). A virtual leader–follower approach is proposed, taking advantage of the concept of a virtual structure, to achieve this goal. Although MPC is an optimal controller, it suffers from increased energy consumption incurred due to repetitive computation at each time step. In an effort to resolve this issue and avoid continuous communication among agents, a self-triggered condition grounded on the Lyapunov stability criterion is proposed, in which each agent determines its own triggering instants. To ensure faster interception of the target, the notion of maximum allowable variation in the Lyapunov function is used to derive the self-triggered control condition. The proposed framework achieves reduction in control updates and interagent communication while exhibiting performance parity with existing approaches. The algorithm is validated through simulations of target interception and tracking of a multiagent system.