11 citations · 15 across the 7 of their papers we have counts for
8 papers · 1 filter
Auto-Optimization with Active Learning in Uncertain Environment: A Predictive Control Approach
Yuan Tan, Jun Yang, Zhongguo Li +2
This paper presents an auto-optimal model predictive control (MPC) framework enhanced with active learning, designed to autonomously track optimal operational conditions in an unkn…
Auto-Optimized Maximum Torque Per Ampere Control of IPMSM Using Dual Control for Exploration and Exploitation
Yuefei Zuo, Yalei Yu, Jun Yang +1
In this paper, a maximum torque per ampere (MTPA) control strategy for the interior permanent magnet synchronous motor (IPMSM) using dual control for exploration and exploitation (…
An Exploration-Exploitation Approach to Anti-lock Brake Systems
Benjamin Sullivan, Jingjing Jiang, Georgios Mavros +1
Anti-lock Brake System (ABS) is a mandatory active safety feature on road vehicles with analogous systems for aircraft and locomotives. This feature aims to prevent locking of the…
Dual Control of Exploration and Exploitation for Auto-Optimisation Control with Active Learning
Zhongguo Li, Wen-Hua Chen, Jun Yang +1
The quest for optimal operation in environments with unknowns and uncertainties is highly desirable but critically challenging across numerous fields. This paper develops a dual co…
A distributionally robust optimization approach to two-sided chance constrained stochastic model predictive control with unknown noise distribution
Yuan Tan, Jun Yang, Wen-Hua Chen +1
In this work, we propose a distributionally robust stochastic model predictive control (DR-SMPC) algorithm to address the problem of two-sided chance constrained discrete-time line…
Multi-step dual control for exploration and exploitation in autonomous search with convergence guarantee
Yuan Tan, Jun Yang, Wen-Hua Chen +1
Motivated by the recently proposed dual control for exploration and exploitation (DCEE) concept, this paper presents a Multi-Step DCEE (MS-DCEE) framework with guaranteed convergen…