Event-Triggered Consensus Control of Agent-Based Full-Vehicle Suspension Systems

This article studies the event-triggered consensus control of agent-based active full-vehicle suspension systems (AFSSs). A novel agent-based AFSS model is put forward, by regarding four quarter-vehicle suspension systems (QVSSs) agents with connections. To better utilize cloud technology and improve control performance, a virtual leader is designed at the center of AFSS. The road information stored in the cloud is used as the virtual leader's input to simulate the optimal driving situation of the actual vehicle. Meanwhile, an event-triggered control method for agent-based AFSSs is presented to save communication resources between agents. By utilizing the Lyapunov-Krasovskill functional approach, sufficient conditions are driven to guarantee satisfactory performance of AFSSs. The performance of AFSSs under road disturbances, such as pitch and roll acceleration, can be improved by implementing a consensus control method under the agent-based AFSS model. Finally, the effectiveness of the proposed approach is validated by a real numerical example of AFSSs.