most citedPerformance guaranteed MPC Policy Approximation via Cost Guided Learning

7 citations

5 papers

math.OC20262 cited

Generalized Global Self-Optimizing Control for Chemical Processes: Part II Objective-Guided Controlled Variable Learning Approach

Chenchen Zhou, Hongxin Su, Xinhui Tang +3

Self-optimizing control (SOC) aims to maintain near-optimal process operation by judiciously selecting controlled variables (CVs). In this series of work, the generalized global SO…

math.OC20267 cited

Global self-optimizing control of batch processes

Chenchen Zhou, Hongxin Su, Xinhui Tang +2

This work considers to achieve near-optimal operation for a class of batch processes by employing self-optimizing control (SOC). Comparing with a continuous one, a batch process ex…

math.OC20264 cited

Dynamic Controlled Variables Based Dynamic Self-Optimizing Control

Chenchen Zhou, Shaoqi Wang, Hongxin Su +3

Self-optimizing control is a strategy for selecting controlled variables, where the economic objective guides the selection and design of controlled variables, with the expectation…

math.OC20267 cited

Performance guaranteed MPC Policy Approximation via Cost Guided Learning

Chenchen Zhou, Yi Cao, Shuang-hua Yang

Model predictive control (MPC) is widely used in industries but implementing it poses challenges due to hardware or time constraints. A promising solution is to approximate the MPC…

gr-qc2026

Conformal symmetry in force-free electrodynamics

Huiquan Li, Jianyong Wang

It is shown that conformal symmetry exists in force-free electrodynamics (FFE) in Minkowski spacetime, a foundational framework for describing magnetospheres around astronomical ob…