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| Author(s): |
Carlos Alexandre Silva
Total Authors: 1
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| Document type: | Doctoral Thesis |
| Press: | São Carlos. |
| Institution: | Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) |
| Defense date: | 2012-08-13 |
| Examining board members: |
Eduardo Fontoura Costa;
Marina Andretta;
Elias Salomão Helou Neto;
Geraldo Nunes Silva;
João Bosco Ribeiro do Val
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| Advisor: | Eduardo Fontoura Costa |
| Abstract | |
In this work we are interested in the optimal control for the long run average cost (LRAC) problem for linear systems with Markov jump parameters (LSMJP), using heuristic methods like first generation evolutionary algorithms - genetic algorithm (GA) - and second generation algorithms including UMDA (Univariate Marginal Distribution Algorithm) and BOA (Bayesian Optimization Algorithm). We have developed a scheme that employs different problems with intermediate levels of observation of the Markov chain, starting with complete observation and shifting to the partial observation problem. The aforementioned methods have been implemented using this scheme. Moreover, in order to compare the methods, we use an algorithm for generating a number of LSMJP and we present a basic statistical analysis of the results. Finally, we present some results on the LRAC with stabilizing control and some partial results on the uniqueness of the solution (AU) | |
| FAPESP's process: | 08/02035-8 - Control of Linear Systems with Markov Jump Parameters and Long Run Average Cost |
| Grantee: | Carlos Alexandre Silva |
| Support Opportunities: | Scholarships in Brazil - Doctorate |