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Studies on Control Design Method based on On-line Modeling and Optimization

基于在线建模与优化的控制设计方法研究

基本信息

批准号：
13650498
负责人：
UCHIDA Kenko
金额：
$ 1.22万
依托单位：
Waseda University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2001
资助国家：
日本
起止时间：
2001 至 2002
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-13650498/
关键词：
online modeling LPV systems infinite-dimensional LMI local model gain scheduling information delay モデリングモデル予測制御

项目摘要

We investigated methods of updating the model adaptively based on online data in the control loop: a combination of an extension of LPV systems modeling and an extension of model predictive control scheme. On the basis of these discussions, we formulated control problems, and proposed solutions and algorithms for calculating the controls. In particular, we paid attention to the role of the information delay and the obstacles raised by the information delays.First, as controlled objectives, we focused electro-hydraulic servosystems, which contain nonlinear elements and uncertainties and are difficult to be modeled exactly. We constructed a linear local model in the neighborhood of each selected operating point of the electro-hydraulic system, and built an LPV global model by using load variations as a scheduling parameter. For the LPV systems, we derived the worst-case optimal control strategy, and demonstrated the effectiveness of the control strategy in the computer simulations and in the real plants. Second, as a typical difficulty in controlling the plant based on the local models, we focused the problem caused by information delays in the state, input and output. In particular, we investigate how to conquer the input and output delays in controlling the plant. The worst-case optimal control scheme was proposed; the finite-dimensional algorithm for constructing the control scheme was derived, the predictor-observer structure of the control scheme was clarified, and the illustrative numerical simulations were reported.

我们研究了基于控制回路中在线数据自适应更新模型的方法：LPV 系统建模的扩展和模型预测控制方案的扩展的组合。在这些讨论的基础上，我们提出了控制问题，并提出了计算控制的解决方案和算法。我们特别关注了信息延迟的作用以及信息延迟带来的障碍。首先，作为控制目标，我们关注电液伺服系统，该系统包含非线性因素和不确定性，难以精确建模。我们在电液系统每个选定工作点的邻域内构建了线性局部模型，并使用负载变化作为调度参数构建了 LPV 全局模型。对于LPV系统，我们推导了最坏情况下的最优控制策略，并在计算机模拟和实际电站中证明了该控制策略的有效性。其次，作为基于局部模型控制被控对象的典型困难，我们重点关注由状态、输入和输出中的信息延迟引起的问题。特别是，我们研究了如何克服控制设备时的输入和输出延迟。提出了最坏情况最优控制方案；推导了构造控制方案的有限维算法，阐明了控制方案的预测器-观测器结构，并报告了说明性数值模拟。