Metodos para Solução da Equação HJB-Riccati via Famíla de Estimadores Parametricos RLS Simplificados e Dependentes de Modelo.

• Ano de defesa: 2014
• Autor(a) principal: SANTOS, Watson Robert Macedo
• Orientador(a): SANTANA, Ewaldo Eder Carvalho
• Banca de defesa: SANTANA, Ewaldo Eder Carvalho, FONSECA NETO, João Viana da, PINTO, Vandilberto Pereira, FILHO, Allan Kardec Duailibe Barros
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Maranhão
• Programa de Pós-Graduação: PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA DE ELETRICIDADE/CCET
• Departamento: DEPARTAMENTO DE ENGENHARIA DA ELETRICIDADE/CCET
• País: Brasil
• Palavras-chave em Português: Teoria de Controle Otimo; Regulador Linear Quadrático Discreto; Equação Hamilton-Jacobi-Bellman; Programação Dinâmica Adaptativa; Modelos Multivariáveis
• Palavras-chave em Inglês: Optimal Control Theory; Discrete Linear Quadratic Regulator; Equation Hamilton-Jacobi-Bellman; Adaptive Dynamic Programming; Multivariable Models
• Área do conhecimento CNPq: Análise de Algoritmos e Complexidade de Computação.
• Link de acesso: http://tedebc.ufma.br:8080/jspui/handle/tede/1892

Due to the demand for high-performance equipments and the rising cost of energy, the industrial sector is developing equipments to attend minimization of the theirs operational costs. The implementation of these requirements generate a demand for projects and implementations of high-performance control systems. The optimal control theory is an alternative to solve this problem, because in its design considers the normative specifications of the system design, as well as those that are related to the operational costs. Motivated by these perspectives, it is presented the study of methods and the development of algorithms to the approximated solution of the Equation Hamilton-Jacobi-Bellman, in the form of discrete Riccati equation, model free and dependent of the dynamic system. The proposed solutions are developed in the context of adaptive dynamic programming that are based on the methods for online design of optimal control systems, Discrete Linear Quadratic Regulator type. The proposed approach is evaluated in multivariable models of the dynamic systems to evaluate the perspectives of the optimal control law for online implementations.