Statistical learning control of uncertain systems: Theory and algorithms

Applied Mathematics and Computation

Volumn 120, Issue 1-3, 2001, Pages 31-43

  Koltchinskii, V ^a   Abdallah, C T ^a   Ariola, M ^b   Dorato, P ^a  

^a UNIVERSITY OF NEW MEXICO   (United States)

^b UNIVERSITY OF NAPLES FEDERICO II   (Italy)

Author keywords

Empirical processes; Optimization; Robust control; Statistical learning

Indexed keywords

APPROXIMATION THEORY; COMPUTABILITY AND DECIDABILITY; COMPUTATIONAL COMPLEXITY; CONTROL SYSTEM ANALYSIS; CONTROL SYSTEM SYNTHESIS; LEARNING ALGORITHMS; LEARNING SYSTEMS; OPTIMAL CONTROL SYSTEMS; PROBLEM SOLVING; PROCESS CONTROL; ROBUSTNESS (CONTROL SYSTEMS); STATISTICAL METHODS; THEOREM PROVING; UNCERTAIN SYSTEMS;

STATISTICAL LEARNING CONTROL SYSTEMS;

ADAPTIVE CONTROL SYSTEMS;

EID: 0035837625     PISSN: 00963003     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0096-3003(99)00283-0     Document Type: Article

References (12)

1. Probabilistic robustness: A new line of research
2. A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations
3. Improved sample complexity estimates for statistical learning control of uncertain systems
4. A Monte Carlo approach to the analysis of control system robustness
5. The unfalsified control concept: A direct path from experiment to controller
6. Weak convergence of empirical processes
7. Statistical learning theory and its applications to randomized algorithms for robust controller synthesis
8. Statistical learning theory and randomized algorithms for control