Prof. Dr. Jiaojiao Ren

This paper investigates the exponential $H_{\infty } $ stability of switching fuzzy vehicle lateral dynamics using an event-triggered reinforcement learning control strategy, which is fundamental for improving the performance, safety, and efficiency of transportation systems. A newly constructed vehicle model is proposed to comprehensively reflect the vehicle’s operating environment. By combining an event-triggered mechanism with our previously published switching law, frequent switchings are achieved without the restrictive condition $\tau _{a} \gt T$ . Reinforcement learning further reduces event triggers, lowering communication costs while maintaining system performance. Moreover, the maximum–minimum dwell time method is used to derive a non-weighted $L_{2}$ norm constraint, preserving the original interpretation of the $L_{2}$ norm inequality. Finally, a numerical example demonstrates the effectiveness of the proposed approach.

About Me

No biography provided yet

Prof. Dr. Jiaojiao Ren

Prof. Dr. Jiaojiao Ren

Research Focus & Metrics

Academic Career Length

Publication Type Breakdown

Representative Publications

About Me