Journal
AUTOMATICA
Volume 38, Issue 9, Pages 1591-1599Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S0005-1098(02)00046-8
Keywords
stochastic robustness; Monte Carlo simulation; input-to-state stability; genetic algorithm
Ask authors/readers for more resources
Probabilistic robustness analysis and synthesis for nonlinear systems with uncertain parameters are presented. Monte Carlo simulation is used to estimate the likelihood of system instability and violation of performance requirements subject to variations of the probabilistic system parameters. Stochastic robust control synthesis searches the controller design parameter space to minimize a cost that is a function of the probabilities that design criteria will not be satisfied. The robust control design approach is illustrated by a simple nonlinear example. A modified feedback linearization control is chosen as controller structure, and the design parameters are searched by a genetic algorithm to achieve the tradcoff between stability and performance robustness. (C) 2002 Elsevier Science Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available