参数不确定离散随机系统的加权多模型自适应控制

张维存

doi:10.16383/j.aas.2015.c140340

参数不确定离散随机系统的加权多模型自适应控制

doi: 10.16383/j.aas.2015.c140340

张维存^,

1.
北京科技大学自动化学院北京 100083

基金项目:

国家重点基础研究发展计划(973计划) (2012CB821200),国家高技术研究发展计划(863 计划) (2011AA060408)资助

详细信息

作者简介:
张维存博士, 北京科技大学自动化学院副教授.主要研究方向为自校正控制, 多模型自适应控制, 智能控制. E-mail: weicunzhang@ustb.edu.cn

通讯作者:
张维存博士, 北京科技大学自动化学院副教授.主要研究方向为自校正控制, 多模型自适应控制, 智能控制. E-mail: weicunzhang@ustb.edu.cn

计量
- 文章访问数: 1529
- HTML全文浏览量: 96
- PDF下载量: 889
- 被引次数: 0
出版历程
- 收稿日期: 2014-05-27
- 修回日期: 2014-09-11
- 刊出日期: 2015-03-20

Weighted Multiple Model Adaptive Control of Discrete-time Stochastic System with Uncertain Parameters

ZHANG Wei-Cun^,

1.
School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083

Funds:

Supported by National Basic Research Program of China (973 Program) (2012CB821200), and National High Technology Research and Development Program of China (863 Program) (2011AA060408)

摘要

摘要: 研究离散时间参数不确定的线性随机系统的加权多模型自适应控制(Weighted multiple model adaptive control, WMMAC)问题,采用一种改进的加权算法,在模型输出误差可分的情况下,可以保证其收敛性;然后在加权收敛的前提下, 借助虚拟等价系统的概念和方法证明了此类加权多模型自适应控制系统的稳定性和收敛性.本文所采用的分析方法和结论不依赖于局部控制策略和加权算法的具体形式, 而只取决于它们的某些属性.最后,基于Matlab对相应的加权多模型自适应控制系统进行了仿真,仿真结果验证了加权算法的收敛性和闭环控制系统的稳定性、收敛性.
- 加权算法 /
- 加权多模型自适应控制 /
- 稳定性 /
- 收敛性 /
- 虚拟等价系统
Abstract: This paper is concerned with the weighted multiple model adaptive control (WMMAC) of discrete-time linear stochastic system with uncertain parameters. Firstly, an improved weighting algorithm is adopted with convergence guaranteed under smooth conditions. Then based on virtual equivalent system methodology, the stability of resulting WMMAC systems for both linear time-invariant (LTI) and parameter jump plants is presented. The analysis method is independent of specific local control strategy and specific weighting algorithm. Finally, the theoretical results have been verified by simulation results using Matlab.
- Weighting algorithm /
- weighted multiple model adaptive control (WMMAC) /
- stability /
- convergence /
- virtual equivalent system

HTML全文

参考文献(34)

[1]	Wang Wei, Li Xiao-Li. Multiple Model Adaptive Control. Beijing: Science Press, 2001.(王伟, 李晓理. 多模型自适应控制. 北京: 科学出版社, 2001.)
[2]	[2] Narendra K S, Han Z. The changing face of adaptive control: the use of multiple models. Annual Reviews in Control, 2011, 35(1): 1-12
[3]	[3] Magill D T. Optimal adaptive estimation of sampled stochastic processes. IEEE Transactions on Automatic Control, 1965, 10(4): 434-439
[4]	[4] Lainiotis D G. Partitioning: a unifying framework for adaptive systems I: Estimation. Proceedings of the IEEE, 1976, 64(8): 1126-1143
[5]	[5] Lainiotis D G. Partitioning: a unifying framework for adaptive systems II: Control. Proceedings of the IEEE, 1976, 64(8): 1182-1198
[6]	[6] Athans M, Castanon D, Dunn K, Greene C, Lee W, Sandell N Jr, Willsky A S. The stochastic control of the F-8C aircraft using a multiple model adaptive control (MMAC) method Part I: Equilibrium flight. IEEE Transactions on Automatic Control, 1977, 22(5): 768-780
[7]	[7] Lane D W, Maybeck P S. Multiple model adaptive estimation applied to the Lambda URV for failure detection and identification. In: Proceedings of the 33rd IEEE Conference on Decision and Control. Lake Buena Vista, FL: IEEE 1994. 678-683
[8]	[8] Yu C, Roy R J, Kaufman H, Bequette B W. Multiple-model adaptive predictive control of mean arterial pressure and cardiac output. IEEE Transactions on Biomedical Engineering, 1992, 39(8): 765-778
[9]	[9] Moose R L, Vanlandingham H F, McCabe D H. Modeling and estimation for tracking maneuvering targets. IEEE Transactions on Aerospace and Electronic Systems, 1979, 15(3): 448-456
[10]	Li X R, Bar-Shalom Y. Design of an interacting multiple model algorithm for air traffic control tracking. IEEE Transactions on Control Systems Technology, 1993, 1(3): 186-194
[11]	Badr A, Binder Z, Rey D. Application of tracking multimodel control to a non-linear thermal process. International Journal of Systems Science, 1990, 21(9): 1795-1803
[12]	Badr A, Binder Z, Rey D. Weighted multi-model control. International Journal of Systems Science, 1992, 23(1): 145-149
[13]	Nagib G, Gharieb W, Binder Z. Qualitative multi-model control using a learning approach. International Journal of Systems Science, 1992, 23(6): 855-869
[14]	Aly A, Badr A, Binder Z. Multi-model control of MIMO systems: location and control algorithms. International Journal of Systems Science, 1988, 19(9): 1687-1698
[15]	Fekri S, Athans M, Pascoal A. Issues, progress and new results in robust adaptive control. International Journal of Adaptive Control and Signal Processing, 2006, 20(10): 519-579
[16]	Fekri S, Athans M, Pascoal A. Robust multiple model adaptive control (RMMAC): a case study. International Journal of Adaptive Control and Signal Processing, 2007, 21(1): 1-30
[17]	Aguiar A P, Hassani V, Pascoal A M, Athans M. Identification and convergence analysis of a class of continuous-time multiple-model adaptive estimators. In: Proceedings of the 17th IFAC World Congress. Seoul, Korea: IFAC, 2008. 8605-8610
[18]	Hassani V, Aguiar A P, Athans M, Pascoal A M. Multiple model adaptive estimation and model identification using a minimum energy criterion. In: Proceedings of the 2009 American Control Conference. St. Louis, USA: IEEE, 2009. 518-523
[19]	Hassani V, Athans M, Pascoal A M. An application of the RMMAC methodology to an unstable plant. In: Proceedings of the 17th Mediterranean Conference on Control and Automation. Thessaloniki, Greece: IEEE, 2009. 37-42
[20]	He Wen-Guang. Multiple model adaptive control for a category of systems with uncertain parameters. Acta Automatica Sinica, 1988, 14(3): 191-198(何文光. 一类不确定参数系统的多模型自适应控制. 自动化学报, 1988, 14(3): 191-198)
[21]	Zhao Zhi-Kui, Han Chong-Zhao, Wan Bai-Wu. Multiple-model adaptive control and applications to a three axis turning-table. Control and Decision, 1998, 13(3): 212-217(赵志魁, 韩崇昭, 万百五. 多模型自适应控制及其在三轴转台中的应用. 控制与决策, 1998, 13(3): 212-217)
[22]	Dong Zhi-Kun, Wang Xin, Wang Xiao-Bo, Li Shao-Yuan, Zheng Yi-Hui. Application of weighted multiple models adaptive controller in the plate cooling process. Acta Automatica Sinica, 2010, 36(8): 1144-1150(董志坤, 王昕, 王笑波, 李少远, 郑益慧. 多模型加权自适应控制在中厚板层流冷却系统中的应用. 自动化学报, 2010, 36(8): 1144-1150)
[23]	Baram Y, Sandell N R. An information theoretic approach to dynamical systems modeling and identification. IEEE Transactions on Automatic Control, 1978, 23(1): 61-66
[24]	Baram Y, Sandell N R. Consistent estimation on finite parameter sets with application to linear systems identification. IEEE Transactions on Automatic Control, 1978, 23(3): 451-454
[25]	Athanasios K. Convergence properties of the Lainiotis partition algorithm. Control and Computers, 1991, 19(1): 1-6
[26]	Kuipers M, Ioannou P. Multiple model adaptive control with mixing. IEEE Transactions on Automatic Control, 2010, 55(8): 1822-1836
[27]	Sadati N, Dumont G A, Mahdavian H. Robust multiple model adaptive control using fuzzy fusion. In: Proceedings of the 42nd Southeastern Symposium on System Theory. Tyler, TX: IEEE, 2010. 19-24
[28]	Hassani V, Hespanha J, Athans M, Pascoal A M. Stability analysis of robust multiple model adaptive control. In: Proceedings of the 18th IFAC World Congress. Milan, Italy: IFAC, 2011. 350-355
[29]	Zhang W C. Stable weighted multiple model adaptive control: discrete-time stochastic plant. International Journal of Adaptive Control and Signal Processing, 2013, 27(7): 562-581
[30]	Zhang W C. On the stability and convergence of self-tuning control-virtual equivalent system approach. International Journal of Control, 2010, 83(5): 879-896
[31]	Zhang W C, Chu T G, Wang L. A new theoretical framework for self-tuning control. International Journal of Information Technology, 2005, 11(11): 123-139
[32]	Zhang W C. Stable weighted multiple model adaptive control with improved convergence rate. In: Proceedings of the 7th IFAC Symposium on Robust Control Design. Aalborg, Denmark: IFAC, 2012. 570-575
[33]	Desoer C A, Vidyasagar M. Feedback Systems: Input-output Properties. New York: Academic Press, 1975.
[34]	Shorten R, Wirth F, Mason O, Wulff K, King C. Stability criteria for switched and hybrid systems. SIAM Review, 2007, 49(4): 545-592

施引文献

资源附件(0)

访问统计

计量

文章访问数: 1529
HTML全文浏览量: 96
PDF下载量: 889
被引次数: 0

姓名
邮箱
手机号码
标题
留言内容
验证码

留言板

参数不确定离散随机系统的加权多模型自适应控制

doi: 10.16383/j.aas.2015.c140340

作者简介:
张维存博士, 北京科技大学自动化学院副教授.主要研究方向为自校正控制, 多模型自适应控制, 智能控制. E-mail: weicunzhang@ustb.edu.cn

通讯作者:
张维存博士, 北京科技大学自动化学院副教授.主要研究方向为自校正控制, 多模型自适应控制, 智能控制. E-mail: weicunzhang@ustb.edu.cn

计量

Weighted Multiple Model Adaptive Control of Discrete-time Stochastic System with Uncertain Parameters

计量

目录

留言板

参数不确定离散随机系统的加权多模型自适应控制

doi: 10.16383/j.aas.2015.c140340

作者简介: 张维存 博士, 北京科技大学自动化学院副教授.主要研究方向为自校正控制, 多模型自适应控制, 智能控制. E-mail: weicunzhang@ustb.edu.cn

通讯作者: 张维存 博士, 北京科技大学自动化学院副教授.主要研究方向为自校正控制, 多模型自适应控制, 智能控制. E-mail: weicunzhang@ustb.edu.cn

计量

出版历程

Weighted Multiple Model Adaptive Control of Discrete-time Stochastic System with Uncertain Parameters

计量

出版历程

目录

作者简介:
张维存博士, 北京科技大学自动化学院副教授.主要研究方向为自校正控制, 多模型自适应控制, 智能控制. E-mail: weicunzhang@ustb.edu.cn

通讯作者:
张维存博士, 北京科技大学自动化学院副教授.主要研究方向为自校正控制, 多模型自适应控制, 智能控制. E-mail: weicunzhang@ustb.edu.cn