Probabilistic robust control design of polynomial vector fields

This paper presents a probabilistic approach to the design of robust controllers for nonlinear systems, in particular, polynomial vector fields in the presence of parametric uncertainty. The objective of the design is to minimize the system's probability of instability subject to the uncertaint...

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Vydáno v:42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475) Ročník 3; s. 2447 - 2452 Vol.3
Hlavní autor: Qian Wang
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 2003
Témata:
Control systems
Nonlinear control systems
Nonlinear systems
Polynomials
Probability
Robust control
Robust stability
Statistical distributions
Stochastic processes
Uncertainty
ISBN:9780780379244, 0780379241
ISSN:0191-2216
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Shrnutí:This paper presents a probabilistic approach to the design of robust controllers for nonlinear systems, in particular, polynomial vector fields in the presence of parametric uncertainty. The objective of the design is to minimize the system's probability of instability subject to the uncertainty described by statistical distributions. Based on the convexity property of a recently proposed stability criterion, which could be viewed as a dual to Lyapunov's second theorem, the probabilistic robust control problem for polynomial vector fields is formulated into a stochastic convex optimization problem. Stochastic gradient algorithms are used to search a generally parameterized nonlinear control law that minimizes the probability of instability.
ISBN:9780780379244
0780379241
ISSN:0191-2216
DOI:10.1109/CDC.2003.1272987