Robust Control Design Based on Randomized Algorithms

Abstract:

This paper combines learning theory with robust control and discusses robust control design problems involving real parameter uncertainty in control systems based on randomized algorithms. It is shown that randomized algorithms can decrease the computational complexity dramatically instead of seeking worst case guarantees. In addition, examples in this paper show that employing randomized algorithms is very efficient and has obvious advantages especially when uncertain interval parameters appear multilinearly or nonlinearly in the characteristic polynomial coefficients.

Key words:

randomized algorithms; learning theory; robust control

To Total contents......To Contents(Mechanics)