QI-MPC: A Hybrid Quantum-Inspired Model Predictive Control for Learning Optimal Policies
QI-MPC: A Hybrid Quantum-Inspired Model Predictive Control for Learning Optimal Policies
In this paper, we present Quantum-Inspired Model Predictive Control (QIMPC), an approach that uses Variational Quantum Circuits (VQCs) to learn control polices in MPC problems. The viability of the approach is tested in five experiments: A target-tracking control strategy, energy-efficient building climate control, autonomous vehicular dynamics, the simple pendulum, and the compound pendulum. Three safety guarantees were established for the approach, and the experiments gave the motivation for two important theoretical results that, in essence, identify systems for which the approach works best.
Muhammad Al-Zafar Khan、Jamal Al-Karaki
自动化基础理论计算技术、计算机技术
Muhammad Al-Zafar Khan,Jamal Al-Karaki.QI-MPC: A Hybrid Quantum-Inspired Model Predictive Control for Learning Optimal Policies[EB/OL].(2025-04-17)[2025-05-28].https://arxiv.org/abs/2504.13041.点此复制
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