[1]蒋 闻,李少远.预测控制器设定值柔化因子的在线调整[J].智能系统学报,2009,4(5):433-440.[doi:10.3969/j.issn.1673-4785.2009.05.008]
JIANG Wen,LI Shao-yuan.Real time tuning of the set-point softening factor for model predictive controllers[J].CAAI Transactions on Intelligent Systems,2009,4(5):433-440.[doi:10.3969/j.issn.1673-4785.2009.05.008]
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JIANG Wen,LI Shao-yuan.Real time tuning of the set-point softening factor for model predictive controllers[J].CAAI Transactions on Intelligent Systems,2009,4(5):433-440.[doi:10.3969/j.issn.1673-4785.2009.05.008]
预测控制器设定值柔化因子的在线调整
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
4
期数:
2009年第5期
页码:
433-440
栏目:
学术论文—智能系统
出版日期:
2009-10-25
- Title:
- Real time tuning of the set-point softening factor for model predictive controllers
- 文章编号:
- 1673-4785(2009)05-0433-08
- Keywords:
- model predictive control; condition number of system matrix; setpoint softening factor; online tuning
- 分类号:
- TP273
- 文献标志码:
- A
- 摘要:
- 预测控制中，对控制量/控制增量加权因子λ和设定值柔化因子α的调节影响到控制系统的性能.调整预测控制器中控制量/控制增量加权因子λ对调节系统上升时间和超调量的作用是相反的.而且λ影响系统矩阵的条件数，存在模型失配时，对系统鲁棒性有很大的影响.设定值柔化因子α对于系统的动态响应也有很大的影响，调整λ和α对于系统的动态响应有类似的效果.因此，为了使闭环系统具有更好的控制性能，将参数λ设计成满足系统矩阵条件数的要求，并通过在线调整α以获得满意的动态性能.仿真结果表明了该方法的有效性.
- Abstract:
- For predictive control, the tuning of weighting factor λ and set-point softening factor α greatly influences the performance of control systems. Tuning of? λ ?in a model predictive controller had negative effects on the regulation of overshoot and ascending time of the system. Moreover,? λ has an effect on the condition number of the system matrix. Thus, λ has a great effect on the robustness of the system when model mismatch occurs. Set-point softening factor?λ also has a large effect on the dynamic response of the control system. Tuning of both α and λ produces similar effects on the dynamic response of the control system. Hence, in order to achieve better control performance, λ was designed to satisfy the need of the condition number and α was assigned as an online tuning parameter. Simulations verified the effectiveness of this approach.
- 参考文献/References:
-
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备注/Memo
作者简介：
蒋 闻，男，1983年生，2009年6月在上海交通大学获得硕士学位，现在美国伊利诺斯大学电机与计算机工程系攻读博士学位，主要研究方向为工业系统约束预测控制器、智能控制.
李少远，男，1965年生，教授、博士生导师.主要研究方向为预测控制、自适应控制、模糊智能控制的理论和应用，主要提出了基于模糊模型的非线性系统的多模型预测控制和基于模糊目标的约束满意优化控制.承担了包括国家自然科学基金、国家“863”计划在内的国家级科研项目10余项.2006年获得上海市自然科学一等奖(第一完成人). 在国内外重要学术会议和期刊上发表学术论文200余篇，其中被SCI、EI收录150余篇，出版专著3部.
更新日期/Last Update:
2009-12-29