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About

Peifen Lu is a leading researcher in the control and coordination of multi-robot systems, with a primary focus on nonholonomic mobile robots (NMRs). Her work addresses fundamental challenges in distributed formation control, consensus, and cooperative tracking under realistic constraints such as saturated inputs, uncertain dynamics, and external disturbances. Lu’s major contributions include the development of novel distributed estimators that enable follower robots to accurately estimate a leader’s states and disturbances, even when both leader and follower dynamics are non-ideal. Her 2020 paper on formation control using distributed estimators has garnered 27 citations, while her 2022 work on joint disturbance-and-leader estimation has received 24 citations, reflecting the community’s strong interest in her robust, scalable approaches. Notably, her 2019 study on leaderless consensus of ring-networked robots with saturated control (23 citations) and her 2020 neuro-adaptive method for cooperative tracking rendezvous (17 citations) demonstrate her versatility in tackling both theoretical and practical control problems. Lu’s research is distinguished by its rigorous Lyapunov-based analysis and hierarchical control frameworks, making her a key figure in advancing the reliability and autonomy of networked robotic systems.