哈尔滨工业大学（深圳）学术讲座

Speaker: 游科友（清华大学教授）

Title: Reliably Learn to Trim Multiparametric Quadratic Programs

Date: 2025-10-26（Sun.周日）  Time: 15:00～16:30

Venue: H412

Host: 许鋆

摘要：In a wide range of important applications, we are required to use limited resources to solve a sequence of convex multiparametric quadratic programs (mp-QPs) with many linear inequalities. This is nontrivial and has been a central topic for decades in control and optimization communities. Observe that it is usually very costly to handle inequality constraints, though the removal of their majority will not change the optimal solution. This work learns from the previously solved mp-QPs, based on which we propose an efficient algorithm to reliably remove redundant inequalities in the mp-QP with a new parameter vector, and thus its trimmed version can be much easier to solve. Then, we extend to solve the linear model predictive control (MPC) problem in the form of mp-QP. Importantly, the results of both historical mp-QPs in the closed-loop system and the offline mp-QPs are used to considerably remove redundant inequalities. We show that the number of linear inequalities remaining in the mp-QP decreases to zero in an explicit finite time-step, which can also be reduced by increasing offline computational load. Finally, numerical results are included to demonstrate the advantages of our learning method for constraint removal.

报告人简介: Keyou You received the B.S. degree in Statistical Science from Sun Yat-sen University, Guangzhou, China, in 2007 and the Ph.D. degree in Electrical and Electronic Engineering from Nanyang Technological University (NTU), Singapore, in 2012. After briefly working as a Research Fellow at NTU, he joined Tsinghua University in Beijing, China where he is now a Full Professor in the Department of Automation. He held visiting positions at Politecnico di Torino, Hong Kong University of Science and Technology, University of Melbourne and etc. Prof. You’s research interests focus on the intersections between control, optimization and learning as well as their applications in autonomous systems. He received the Guan Zhaozhi award at the 29th Chinese Control Conference in 2010 and the ACA (Asian Control Association) Temasek Young Educator Award in 2019. He received the National Science Funds for Excellent Young Scholars in 2017, and for Distinguished Young Scholars in 2023. He severs/severed as an Associate Editor for Automatica, IEEE Transactions on Control of Network Systems, IEEE Transactions on Cybernetics and etc.