Event-Triggered Adaptive Optimal Control of Vehicular Platoons via Fuzzy ADP With Prescribed Performance

The control problem for connected vehicular platoons requires balancing control optimality, saving computational and communication resources, and ensuring security. In this paper, a fuzzy prescribed performance adaptive optimal control strategy is developed for platoon system, and a distributed event-triggered (ET) mechanism is introduced. The main contributions include: 1) A prescribed performance adaptive dynamic programming (ADP) control architecture under distributed event-triggering is developed. The designed control method not only ensures the safety distance requirements of the platoon, but also significantly reduces the computing and communication costs, while guaranteeing the control optimality under the above objectives; 2) The stability proof of the platoon system considering the above complex control objectives is completed. Stable convergence of fuzzy logic system (FLS) is ensured by designing an experience replay-based critic update rule; 3) Considering the practicability in real working conditions, the cost function of the ADP controller robust to actuator saturation and disturbance is designed. Compared with existing methods, our approach achieves optimal control, robustness, and enhanced communication efficiency. Finally, the effectiveness and applicability of the controller are verified by simulations.