Robust Control of Stochastic Nonlinear Systems

The third topic studied involves the constrained minimax optimization problem for a class of stochastic nonlinear systems in strict-feedback form, where in addition to the standard Wiener process there is a norm-bounded unknown disturbance driving the system. The bound on the disturbance is a stochastic integral quadratic constraint, and it is also related to the constraint on the relative entropy between the uncertainty probability measure and the reference probability measure on the original probability space. Within this structure, by first converting the original constrained optimization problem into an unconstrained one (a stochastic differential game) and then making use of the duality relationship between stochastic games and risk-sensitive stochastic control, we obtain a minimax state-feedback control law that is both locally optimal and globally inverse optimal. Furthermore, the closed-loop system is absolutely stable in the presence of stochastic uncertainty disturbances.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Tang, Cheng

Contributors dc:contributor

• Basar, Tamer

• Engineering, Electronics and Electrical

Language dc:language

eng

Identifier

(MiAaPQ)AAI3086197

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/80825