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arXiv · 2202.06012

Cloud-based computational model predictive control using a parallel multi-block ADMM approach

Yaling Ma·Runze Gao·Li Dai·Jinxian Wu·Yuanqing Xia
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Abstract

Heavy computational load for solving nonconvex problems for large-scale systems or systems with real-time demands at each sample step has been recognized as one of the reasons for preventing a wider application of nonlinear model predictive control (NMPC). To improve the real-time feasibility of NMPC with input nonlinearity, we devise an innovative scheme called cloud-based computational model predictive control (MPC) by using an elaborately designed parallel multi-block alternating direction method of multipliers (ADMM) algorithm. This novel parallel multi-block ADMM algorithm is tailored to tackle the computational issue of solving a nonconvex problem with nonlinear constraints.

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Yaling Ma, Runze Gao, Li Dai, Jinxian Wu, Yuanqing Xia. 2022-02-12. Cloud-based computational model predictive control using a parallel multi-block ADMM approach. https://arxiv.org/abs/2202.06012

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