Y
Yugeng Xi
Researcher at Shanghai Jiao Tong University
Publications - 209
Citations - 3119
Yugeng Xi is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Model predictive control & Control theory. The author has an hindex of 24, co-authored 209 publications receiving 2558 citations. Previous affiliations of Yugeng Xi include Chinese Ministry of Education.
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Fast Model Predictive Control for Urban Road Networks via MILP
TL;DR: Simulation results show that the MILP-based MPC controllers can reach the same performance, but the time taken to solve the optimization becomes only a few seconds, which is a significant reduction, compared with the time required by the original MPC controller.
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Efficient network-wide model-based predictive control for urban traffic networks
TL;DR: Through reducing the prediction model, the corresponding MPC controller exhibits less on-line computational burden, and thus becomes more applicable in practice, and it becomes possible for the control system to deal with complex urban road networks more efficiently.
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Technical communique: A synthesis approach for output feedback robust constrained model predictive control
TL;DR: This paper addresses the synthesis approach for output feedback robust model predictive control for systems with polytopic description, bounded state disturbance and measurement noise by presenting a rigorous method to guarantee satisfaction of input/state constraints.
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Technical Communique: A synthesis approach of on-line constrained robust model predictive control
TL;DR: A new method to address constrained robust model predictive control for systems with polytopic description (RPC-SPD) is proposed and a parameter-dependent Lyapunov function is developed for establishing the closed-loop stability.
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A rolling horizon job shop rescheduling strategy in the dynamic environment
Jian Fang,Yugeng Xi +1 more
TL;DR: In this paper, a hybrid of genetic algorithms and dispatching rules was proposed for solving the job shop scheduling problem with sequence-dependent set-up time and due date constraints, which is more suitable for a dynamic job shop environment than the static scheduling strategy.