一种基于模型参考自适应辨识的半自动模型预测控制方法
The Semi-automatic Model Predictive Control Method Based on Model Reference Adaptive Identification Algorithm
查看参考文献20篇
|
文摘
|
多变量预测控制在应用中经常会遇到模型失配的问题,最终导致控制器不能满足控制要求.本文提出了一种模型预测控制(model predictive control,MPC)架构,通过被控对象和预测模型的频率响应误差判断模型是否失配;当模型失配时,首先对被控对象叠加持续激励信号;然后,通过改进的模型自适应辨识方法辨识对象的传递函数模型;最后,经过拉氏逆变换,将传递函数模型转化为FSR(finite step response)模型,重新恢复多变量预测控制.该方法不需要进行离线辨识试验,实现了模型的多变量辨识;辨识的传递函数模型的动态特性更加清晰,便于分析和修改;经过拉氏逆变换得到的FSR模型更加平滑,能够消除因模型误差引起的静差.经过仿真实验,证明了该方法的有效性. |
|
其他语种文摘
|
The model mismatch problem appears in the application of multivariable predictive control algorithms that may lead a controller not to meet control requirements. We present a model predictive control (MPC) framework that uses the frequency response error between the controlled plant and the predictive model as the criterion to determine whether model mismatch exists. If model mismatch occurs, a persistent excitation signal is added to the controlled plant first,and then the transfer function model of the plant is identified by an improved model adaptive identification algorithm. Finally, the transfer function model is transformed into a finite step response (FSR) model via inverse Laplace transform, and multivariable predictive control is reactivated. Using this new method, an offline identification test becomes unnecessary, and multivariable identification can be achieved. The dynamic characteristics of the identified transfer function model are even clearer and more convenient for analysis and modification. After inverse Laplace transform,the FSR model runs more smoothly and can eliminate the offset caused by model errors. Simulation results show the effectiveness of the proposed method. |
|
来源
|
信息与控制
,2014,43(6):681-689,696 【核心库】
|
|
关键词
|
半自动模型预测控制
;
多变量辨识
;
模型失配
;
自适应辨识
;
频率响应
;
持续激励
|
|
地址
|
1.
东北大学, 流程工业综合自动化国家重点实验室, 辽宁, 沈阳, 110819
2.
中国科学院沈阳自动化研究所信息服务与智能控制技术研究室, 辽宁, 沈阳, 110016
|
|
语种
|
中文 |
|
文献类型
|
研究性论文 |
|
ISSN
|
1002-0411 |
|
学科
|
自动化技术、计算机技术 |
|
基金
|
国家自然科学基金资助项目
;
国家863计划
;
中科院重点部署项目
;
博士后基金资助项目
;
流程工业综合自动化国家重点实验室基础科研业务费资助项目
|
|
文献收藏号
|
CSCD:5330298
|
参考文献 共
20
共1页
|
|
1.
Qin S J. A survey of industrial model predictive control technology.
Control Engineering Practice,2003,11(7):733-764
|
被引
222
次
|
|
|
|
|
2.
Zhu Y C. Development and application of an integrated MPC technology.
Proceedings of the 17th IFAC World Congress,2008:6962-6967
|
被引
1
次
|
|
|
|
|
3.
Zhu Y C. Towards a low cost and high performance MPC : The role of system identification.
Computers & Chemical Engineering,2013,51(1):124-135
|
被引
8
次
|
|
|
|
|
4.
Richalet J. Industrial applications of model based predictive control.
Automatica,1993,29(5):1251-1274
|
被引
30
次
|
|
|
|
|
5.
Zhu Y C. Multivariable process identification for MPC : The asymptotic method and its applications.
Journal of Process Control,1998,8(2):101-115
|
被引
10
次
|
|
|
|
|
6.
王建国. 基于正交投影的滚动窗口递推闭环子空间辨识.
信息与控制,2014,43(1):56-62
|
被引
1
次
|
|
|
|
|
7.
李晓华. 基于ESN网络的连续搅拌反应釜(CSTR)辨识.
信息与控制,2014,43(2):223-228
|
被引
7
次
|
|
|
|
|
8.
Akpan V A. Nonlinear model identification and adaptive model predictive control using neural networks.
ISA Transactions,2011,50(2):177-194
|
被引
10
次
|
|
|
|
|
9.
Aggelogiannaki E. An adaptive model predictive control configuration for production-inventory systems.
International Journal of Production Economics,2008,114(1):165-178
|
被引
1
次
|
|
|
|
|
10.
Karra S. Adaptive model predictive control of multivariable time-varying systems.
Industrial and Engineering Chemistry Research,2008,47(8):2708-2720
|
被引
2
次
|
|
|
|
|
11.
Li T. Dynamic input signal design for the identification of constrained systems.
Journal of Process Control,2008,18(3/4):332-346
|
被引
2
次
|
|
|
|
|
12.
Ji G L. A method of MPC model error detection.
Journal of Process Control,2012,22(3):635-642
|
被引
2
次
|
|
|
|
|
13.
Kalafatis A. Multivariable step testing for MPC projects reduces crude unit testing time.
Hydrocarbon Processing,2006,85(2):93-100
|
被引
1
次
|
|
|
|
|
14.
Li S Y. Robust decentralized parameter identification for two-input two-output process from closed-loop step responses.
Control Engineering Practice,2005,13(4):519-531
|
被引
4
次
|
|
|
|
|
15.
Nandola N N. A multiple model approach for predictive control of nonlinear hybrid systems.
Journal of Process Control,2008,18(2):131-148
|
被引
10
次
|
|
|
|
|
16.
Wang Q G. Robust identification of continuous systems with dead-time from step responses.
Automatica,2001,37(3):377-390
|
被引
12
次
|
|
|
|
|
17.
薛振框. 基于模型有效匹配的多模型切换控制.
上海交通大学学报,2005,39(3):353-356
|
被引
3
次
|
|
|
|
|
18.
韩曾晋.
自适应控制,1995
|
被引
78
次
|
|
|
|
|
19.
朱豫才.
过程控制的多变量系统辨识,2005:34-35
|
被引
1
次
|
|
|
|
|
20.
Karra S. Alternative model structure with simplistic noise model to identify linear time invariant systems subjected to non-stationary disturbances.
Journal of Process Control,2009,19(6):964-977
|
被引
2
次
|
|
|
|
|
了解气象卫星更多信息，请访问