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arXiv · 2407.18825

Numerical Discrete-Time Implementation of Continuous-Time Linear-Quadratic Model Predictive Control

Zhanhao Zhang·Anders Hilmar Damm Christensen·Steen Hørsholt·John Bagterp Jørgensen
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Abstract

This study presents the design, discretization and implementation of the continuous-time linear-quadratic model predictive control (CT-LMPC). The control model of the CT-LMPC is parameterized as transfer functions with time delays, and they are separated into deterministic and stochastic parts for relevant control and filtering algorithms. We formulate time-delay, finite-horizon CT linear-quadratic optimal control problems (LQ-OCPs) for the CT-LMPC. By assuming piece-wise constant inputs and constraints, we present the numerical discretization of the proposed LQ-OCPs and show how to convert the discrete-time (DT) equivalent into a standard quadratic program. The performance of the CT-LMPC is compared with the conventional DT-LMPC algorithm. Our numerical experiments show that, under fixed tunning parameters, the CT-LMPC shows better closed-loop performance as the sampling time increases than the conventional DT-LMPC.

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Zhanhao Zhang, Anders Hilmar Damm Christensen, Steen Hørsholt, John Bagterp Jørgensen. 2024-07-26. Numerical Discrete-Time Implementation of Continuous-Time Linear-Quadratic Model Predictive Control. https://arxiv.org/abs/2407.18825

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