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| Author(s): |
Larissa Tebaldi de Oliveira
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | São Carlos. |
| Institution: | Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) |
| Defense date: | 2014-06-11 |
| Examining board members: |
Eduardo Fontoura Costa;
Elias Salomão Helou Neto;
Adriano Almeida Gonçalves Siqueira
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| Advisor: | Eduardo Fontoura Costa |
| Abstract | |
This work addresses a control problem arising in linear systems with Markov jumps without observation of the jump variable and advances in three different aspects. First, it is presented a counterexample to the conjecture that states about the uniqueness of local minimum. Second, the intermediary optimization problem, which sets all the variables of the problem except two arrays of gains, was studied and the results suggested that a slight modification in the formulation makes the intermediary problem a biquadratic one. Finally, new algorithms were developed based on a method available in the literature, which is frequently referred to as the Variational method, adapting it to update the gains in pairs, leading to biquadratic intermediary problems. Three methods were implemented to solve these intermediary problems: two classical descent methods, Newton and Gradient, and an adaptation of the Variational method. To evaluate the performance of the proposed methods, randomly generated examples were used and the Variational method was set as reference for comparing the results (AU) | |
| FAPESP's process: | 12/14085-5 - A numerical method for the long-term average cost problem for linear systems with jumping parameters and partial observation of the Markov chain |
| Grantee: | Larissa Tebaldi de Oliveira |
| Support Opportunities: | Scholarships in Brazil - Master |