Reinforcement learning for batch process control: Review and perspectives
Batch or semi-batch processing is becoming more prevalent in industrial chemical
manufacturing but it has not benefited from advanced control technologies to a same degree …
manufacturing but it has not benefited from advanced control technologies to a same degree …
Enhanced P-type control: Indirect adaptive learning from set-point updates
In this article, an indirect adaptive iterative learning control (iAILC) scheme is proposed for
both linear and nonlinear systems to enhance the P-type controller by learning from set …
both linear and nonlinear systems to enhance the P-type controller by learning from set …
Maximization of gain/phase margins by PID control
Proportional-integral-derivative (PID) control has been the workhorse of control technology
for about a century. Yet to this day, designing and tuning PID controllers relies mostly on …
for about a century. Yet to this day, designing and tuning PID controllers relies mostly on …
An optimal approach to online tuning method for PID type iterative learning control
F Memon, C Shao - International Journal of Control, Automation and …, 2020 - Springer
The proportional-integral-derivative (PID) controller is widely used in process control
engineering. However, the parameter updating of PID controller has been a challenging …
engineering. However, the parameter updating of PID controller has been a challenging …
Extended state observer based indirect-type ILC for single-input single-output batch processes with time-and batch-varying uncertainties
In this paper, a set-point related indirect-type iterative learning control (ILC) design is
proposed for industrial batch processes with time-varying uncertainties and external …
proposed for industrial batch processes with time-varying uncertainties and external …
A 2D-FM model-based robust iterative learning model predictive control for batch processes
The work deals with composite iterative learning model predictive control (CILMPC) for
uncertain batch processes via a two dimensional Fornasini–Marchesini (2D-FM) model. A …
uncertain batch processes via a two dimensional Fornasini–Marchesini (2D-FM) model. A …
Thermal management-oriented multivariable robust control of a kW-scale solid oxide fuel cell stand-alone system
H Cao, X Li - IEEE Transactions on Energy Conversion, 2016 - ieeexplore.ieee.org
The aim of this paper is to develop an effective control system for a kW-scale solid oxide fuel
cell (SOFC) stand-alone system based on our previous studies, where the dynamic model …
cell (SOFC) stand-alone system based on our previous studies, where the dynamic model …
Robust iterative learning control for batch processes with input delay subject to time‐varying uncertainties
A robust iterative learning control (ILC) method is proposed for industrial batch processes
with input delay subject to time‐varying uncertainties, based on a two‐dimensional (2D) …
with input delay subject to time‐varying uncertainties, based on a two‐dimensional (2D) …
A transfer predictive control method based on inter-domain map** learning with application to industrial roasting process
H Liang, C Yang, K Huang, D Wu, W Gui - ISA transactions, 2023 - Elsevier
As a critical variable in the roasting process, the roasting temperature has a significant
influence on operating conditions. Model predictive control (MPC) provides a path to …
influence on operating conditions. Model predictive control (MPC) provides a path to …
Data-driven indirect iterative learning control
R Chi, H Li, N Lin, B Huang - IEEE Transactions on Cybernetics, 2023 - ieeexplore.ieee.org
In this work, a data-driven indirect iterative learning control (DD-iILC) is presented for a
repetitive nonlinear system by taking a proportional-integral-derivative (PID) feedback …
repetitive nonlinear system by taking a proportional-integral-derivative (PID) feedback …