Model predictive control (MPC) has demonstrated exceptional success for the high-
performance control of complex systems. The conceptual simplicity of MPC as well as its …

In the past ten years many Stochastic Model Predictive Control (SMPC) algorithms have
been developed for systems subject to stochastic disturbances and model uncertainties …

摘要30 多年来, 模型预测控制(Model predictive control, MPC) 的理论和技术得到了长足的发展,
但面对经济社会迅速发展对约束优化控制提出的不断增长的要求, 现有的模型预测控制理论和 …

Gaussian process (GP) regression has been widely used in supervised machine learning
due to its flexibility and inherent ability to describe uncertainty in function estimation. In the …

One of the motivations behind this book was to collect together the many results of the
Oxford University predictive control group. For this reason we have, rather unashamedly …

Two stochastic model predictive control algorithms, which are referred to as distributionally
robust model predictive control algorithms, are proposed in this article for a class of discrete …

Advances in optical manipulation and observation of neural activity have set the stage for
widespread implementation of closed-loop and activity-guided optical control of neural …

Agriculture plays a decisive role in the survival of humankind. The efficient and precise
regulation of agriculture will ensure the welfare of people throughout the world. However …

Many practical applications in control require that constraints on the inputs and states of the
system are respected, while some performance criterion is optimized. In the presence of …

This paper presents a stochastic model predictive control (SMPC) approach to building
heating, ventilation, and air conditioning (HVAC) systems. The building HVAC system is …