Faster MPC by Banded Null-space Basis

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• Ling Keck Voon (NTU, Singapore)
• Friday 06 July 2018, 15:00-16:00
• Room 503, EEE.

If you have a question about this talk, please contact George A Constantinides.

System of linear equations of the saddle point type occur in many scientific and engineering applications. The focus of this talk is the saddle point system that arises in solving Model Predictive Control (MPC) problems. In particular, we exploit the structure in the equality constraint matrix and propose a null space method to accelerate the solution of MPC . The proposed algorithm is tested with a wide range of MPC benchmark problems, implemented an industrial embedded platform.

Brief Bio Keck-Voon Ling received the B.Eng. degree in electrical engineering from the National University of Singapore, and the D.Phil. degree in control engineering from Oxford University. He is currently an Associate Professor at the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. His research interests include model predictive control and moving horizon estimation, their embedded implementation, and applications.

This talk is part of the Featured talks series.

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