非线性快速批次过程高效迭代学习预测函数控制
马乐乐， 刘向杰 - 自动化学报, 2022 - aas.net.cn
迭代学习模型预测控制(Iterative learning model predictive control, ILMPC)
具备较强的批次学习能力及突出的时域跟踪性能, 在批次过程控制中发挥了重要作用 …
具备较强的批次学习能力及突出的时域跟踪性能, 在批次过程控制中发挥了重要作用 …
Iterative learning model predictive control based on iterative data-driven modeling
L Ma, X Liu, X Kong, KY Lee - IEEE transactions on neural …, 2020 - ieeexplore.ieee.org
Iterative learning model predictive control (ILMPC) has been recognized as an effective
approach to realize high-precision tracking for batch processes with repetitive nature …
approach to realize high-precision tracking for batch processes with repetitive nature …
Dynamic neural network predictive compensation-based point-to-point iterative learning control with nonuniform batch length
R Hou, L Jia, X Bu, C Zhou - IEEE Transactions on Neural …, 2023 - ieeexplore.ieee.org
This article discusses the problem of nonuniform running length in incomplete tracking
control, which often occurs in industrial processes due to artificial or environmental changes …
control, which often occurs in industrial processes due to artificial or environmental changes …
An efficient iterative learning predictive functional control for nonlinear batch processes
X Liu, L Ma, X Kong, KY Lee - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Iterative learning model-predictive control (ILMPC) is very popular in controlling the batch
process since it possesses not only the learning ability along batches but also the strong …
process since it possesses not only the learning ability along batches but also the strong …
[PDF][PDF] 变参考轨迹下的鲁棒迭代学习模型预测控制
马乐乐， 刘向杰 - 自动化学报, 2019 - aas.net.cn
摘要迭代学习模型预测控制是针对间歇过程的先进控制方法. 它能通过迭代高精度跟踪给定参考
轨迹, 并保证时域上的闭环稳定性. 然而, 现有的迭代学习模型预测控制算法大多基于线性/线性 …
轨迹, 并保证时域上的闭环稳定性. 然而, 现有的迭代学习模型预测控制算法大多基于线性/线性 …
A two-stage robust iterative learning model predictive control for batch processes
C Zhou, L Jia, Y Zhou - ISA transactions, 2023 - Elsevier
Iterative learning model predictive control (ILMPC) has been considered as potential control
strategy for batch processes. ILMPC can converge to the desired reference trajectory with …
strategy for batch processes. ILMPC can converge to the desired reference trajectory with …
Event-based switching iterative learning model predictive control for batch processes with randomly varying trial lengths
Iterative learning model predictive control (ILMPC) has been recognized as an excellent
batch process control strategy for progressively improving tracking performance along trials …
batch process control strategy for progressively improving tracking performance along trials …
Synthesis of ILC–MPC controller with data-driven approach for constrained batch processes
The iterative learning control (ILC) combining with model predictive control (ILC-MPC) is an
effective control method for constrained batch processes. However, in real applications …
effective control method for constrained batch processes. However, in real applications …
Stochastic iterative learning model predictive control based on stochastic approximation
BJ Park, SK Oh, JM Lee - IFAC-PapersOnLine, 2019 - Elsevier
Iterative learning model predictive control (ILMPC) is an effective control technique for
improving the performance of a batch process under model uncertainty and rejecting real …
improving the performance of a batch process under model uncertainty and rejecting real …