The Entropy Penalized Minimum Energy Estimator

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2009

Autores

Sergio Pequito (Autor) Outra; Pedro Aguiar, AP (Autor) Outra; Diogo A Gomes (Autor) Outra

Ata de Conferência Internacional

Título: PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009)

Páginas: 1285-1290

Joint 48th IEEE Conference on Decision and Control (CDC) / 28th Chinese Control Conference (CCC)

Shanghai, PEOPLES R CHINA, DEC 15-18, 2009

Indexação

ISI Web of Knowledge - 1 Citação

Scopus - 1 Citação

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

Outras Informações

ID Authenticus: P-007-SY0

DOI: 10.1109/cdc.2009.5400482

Abstract (EN): This paper addresses the state estimation problem of nonlinear systems. We formulate the problem using a minimum energy estimator (MEE) approach and propose an entropy penalized scheme to approximate the viscosity solution of the Hamilton-Jacobi equation that follows from the MEE formulation. We derive an explicit observer algorithm that is iterative and filtering-like, which continuously improves the state estimation as more measurements arise. In addition, we propose a computationally efficient procedure to estimate the state by performing an approximation of the nonlinear system along the trajectory of the estimate. In this case, for the first and second order approximations of the state equation, we derive a closed-form (iterative) solution for the Hessian of the entropy-like version of the optimal cost function of the MEE. We illustrate and contrast the performance of our algorithms with the extended Kalman filter (EKF) using specific nonlinear examples with the feature that the EKF do not converge to the correct value.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6