Event-Triggered Interval Type-2 Fuzzy Consensus Control of Full-Vehicle Suspension Systems Using a Leader-Following Approach

This paper proposes an innovative event-triggered interval type-2 (IT-2) fuzzy consensus control method for agent-based full-vehicle suspension systems (FSSs) using a leader-following approach. By developing a novel IT-2 Takagi-Sugeno (T-S) fuzzy model, the amalgamation of heterogeneous agent-based FSSs into a cohesive homogeneous multi-agent framework becomes feasible, thereby reducing control complexity and effectively dealing with system uncertainty. Within the proposed agent-based architecture, a virtual leader is designed at the core of the agent-based FSS, and the four interconnected quarter-vehicle suspension systems are construed as the following agents. To optimize network bandwidth between the agents, a new event-triggered mechanism (ETM) is established, which is sensitive to significant state changes, particularly when deviations from consensus among the following agents arise abruptly. Sufficient conditions are derived to ensure both the optimal attitude performance and ride comfort of FSSs. Finally, a simulation example of agent-based FSSs is presented to validate the advantages of the proposed approach in optimizing ride comfort and system robustness.