集值系统的辨识、控制及应用  

Identification,control and application of set-valued systems

作　　者：王婷[1] 赵延龙[1] 

机构地区：[1]中国科学院数学与系统科学研究院,北京100190

出　　处：《南京信息工程大学学报（自然科学版）》2017年第3期319-325,共7页Journal of Nanjing University of Information Science & Technology（Natural Science Edition）

基　　金：国家自然科学基金(61622309);国家重点基础研究发展计划(2014CB845301)

摘　　要：本文总结了近年来关于集值系统的研究工作:在辨识方面,从不同的系统结构、不同的噪声情况和不同的集值情形等方面进行了深入的研究,针对性地提出了参数解耦、比例满秩输入设计、联合可辨识、经验分布函数、递推投影辨识等有效的辨识方法,得到了一系列重要结果;在适应控制方面,都实现了一类集值增益系统的适应跟踪控制;在同步控制方面,提出了双时间尺度同步算法和递推投影同步算法,实现了二值量测下的多个体同步控制;在应用方面,分别将集值辨识应用到复杂疾病建模和雷达目标识别问题中,构造了新的、更为有效的统计验证方法,在低信噪比下将识别率提高了10%.This paper gives a summary of recent work on set-valued systems.On the identification side, for different model structures, different system noises and different set cases, some effective methods such as parameter decoupiing,full rank input design,joint identifiability,empirical measure method without truncation and recursive projection identification algorithm are introduced.Based on these methods, the results show that the accurate estimates of the parameters can be achieved even under set-valued information.On the adaptive control side, the asymptotically optimal adaptive control is designed for a class of gain systems with set-valued observations.On the consensus control side,the two-time scale consensus control and the recursive projection consensus control are designed.The multi-agent systems can achieve consensus control by any of the two consensus algorithms. On the application side, we apply set-valued identification methods to complex disease modeling and radar target recognition problems. A new and more effective statistical verification method is constructed.The recognition rate is improved by 10% under low signal-noise ratio.

关 键 词：集值系统 系统辨识 自适应控制 同步控制 复杂疾病建模 雷达目标识别 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]