Statistical learning control of uncertain systems: theory and algorithms

被引:9
|
作者
Koltchinskii, V [1 ]
Abdallah, CT
Ariola, M
Dorato, P
机构
[1] Univ New Mexico, Dept Math & Stat, Albuquerque, NM 87131 USA
[2] Univ New Mexico, Dept EECE, Albuquerque, NM 87131 USA
[3] Univ Naples Federico II, Dipartimento Informat & Sistemist, Naples, Italy
基金
美国国家科学基金会;
关键词
empirical processes; statistical learning; robust control; optimization;
D O I
10.1016/S0096-3003(99)00283-0
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
It has recently become clear that many control problems are too difficult to admit analytic solutions. New results have also emerged to show that the computational complexity of some "solved" control problems is prohibitive, Many of these control problems can be reduced to decidability problems or to optimization questions. Even though such questions may be too difficult to answer analytically, or may not be answered exactly given a reasonable amount of computational resources, researchers have shown that we can "approximately'' answer these questions "most of the time", and have "high confidence" in the correctness of the answers. (C) 2001 Elsevier Science Inc. All rights reserved.
引用
收藏
页码:31 / 43
页数:13
相关论文
共 50 条
  • [1] Statistical learning theory and randomized algorithms for control
    Vidyasagar, M
    [J]. IEEE CONTROL SYSTEMS MAGAZINE, 1998, 18 (06): : 69 - 85
  • [2] Uncertain variables and learning algorithms in knowledge-based control systems
    Z. Bubnicki
    [J]. Artificial Life and Robotics, 1999, 3 (3) : 155 - 159
  • [3] Robust learning control algorithms for uncertain time-varying systems
    Liu, Li
    Sun, Ming-Xuan
    [J]. Kongzhi Lilun Yu Yingyong/Control Theory and Applications, 2010, 27 (03): : 323 - 328
  • [4] Improved sample complexity estimates for statistical learning control of uncertain systems
    Koltchinskii, V
    Abdallah, CT
    Ariola, M
    Dorato, P
    Panchenko, D
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2000, 45 (12) : 2383 - 2388
  • [5] CONTROL OF UNCERTAIN PROCESSES - APPLIED THEORY AND ALGORITHMS
    PETERKA, V
    [J]. KYBERNETIKA, 1986, 22 (03) : A1 - A24
  • [6] Randomized algorithms for analysis and control of uncertain systems: An overview
    Tempo, R
    Dabbene, F
    [J]. PERSPECTIVES IN ROBUST CONTROL, 2001, 268 : 347 - 362
  • [7] Revisiting statistical learning theory for uncertain feasibility and optimization problems
    Alamo, T.
    Tempo, R.
    Camacho, E. F.
    [J]. PROCEEDINGS OF THE 46TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-14, 2007, : 3776 - +
  • [8] STATISTICAL THEORY OF AUTOMATIC LEARNING SYSTEMS
    PUGACHEV, VS
    [J]. ENGINEERING CYBERNETICS, 1967, (06): : 24 - &
  • [9] Statistical learning in control and matrix theory
    Vidyasagar, M
    [J]. NONLINEAR MODELING: ADVANCED BLACK-BOX TECHNIQUES, 1998, : 177 - 207
  • [10] Adaptive learning control of uncertain robotic systems
    Park, BH
    Kuc, TY
    Lee, JS
    [J]. INTERNATIONAL JOURNAL OF CONTROL, 1996, 65 (05) : 725 - 744