TY  - CHAP
A1  - Heemels, W.P.M.H.
A1  - Bemporad, Alberto
T2  - Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC)
Y1  - 2011/12//
SP  - 2871 
SN  - 978-1-61284-800-6
EP  - 2876
PB  - IEEE
N2  - In this paper we study a class of stochastic design problems formulated in terms of general inequality conditions on expectations. These inequalities can be used to express various mean square or almost sure stabilization conditions for stochastic systems. In contrast with existing probabilistic methods that only solve such problems with a certain probability (degree of confidence), we propose a novel method that provides a full guarantee that the constructed solution truly solves the original problem. The main idea of our method is based on overapproximating the expectations by suitably constructed upper Riemann-Stieltjes sums and imposing the inequalities on these sums instead. Next to the full guarantee on the constructed solution, the method offers three other advantages. First, it applies to arbitrary probability distributions. Second, under rather mild conditions we can derive a #x201C;converse theorem #x201D; that states that if the original problem is solvable, our method will find a solution by sufficiently refining the upper Riemann-Stieltjes sums. Finally, we will show that convexity of the function used in the expectation can be exploited to obtain convex design conditions in our approach.
KW  - Approximation methods
KW  -  Probabilistic logic
KW  -  Probability density function
KW  -  Random variables
KW  -  Stability analysis
KW  -  Stochastic processes
KW  -  Vectors 
UR  - http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6160820&isnumber=6159299
ID  - eprints1256
TI  - An upper Riemann-Stieltjes approach to stochastic design problems
AV  - none
ER  -