Nonlinear control system design using variable complexity modelling and multiobjective optimization



Título del documento: Nonlinear control system design using variable complexity modelling and multiobjective optimization
Revista: Controle & automacao
Base de datos: PERIÓDICA
Número de sistema: 000315449
ISSN: 0103-1759
Autores: 1
2
Instituciones: 1Universidade Federal de Sao Joao del Rei, Sao Joao del Rei, Minas Gerais. Brasil
2University of Sheffield, Sheffield, Yorkshire. Reino Unido
Año:
Periodo: Ene-Mar
Volumen: 17
Número: 1
Paginación: 24-31
País: Brasil
Idioma: Inglés
Tipo de documento: Artículo
Enfoque: Aplicado, descriptivo
Resumen en inglés To design controllers for complex non-linear systems usually involves the use of expensive computational models. A non-linear thermodynamic model of a gas turbine engine is used to evaluate a selection of designs for a multivariable PI controller configuration. An approach using variable complexity modelling (VCM) is introduced to allow more designs to be evaluated and also to speed up the design process. Response surface methodology (RSM) is a statistical technique in which smooth functions are used to model an objective function. RSM employs statistical methods to create functions, typically polynomials, to model the response or outcome of a numerical experiment in terms of several independent variables. Regression analysis is applied to fit polynomial models to this data for various control responses. These control responses models are evaluated by a multiobjective genetic algorithm to design the controller parameters. The final designs are checked using the original non-linear model
Disciplinas: Ingeniería
Palabras clave: Ingeniería de control,
Algoritmos genéticos,
Control multiobjetivo,
Optimización,
Sistemas no lineales,
Controladores,
Modelado
Keyword: Engineering,
Control engineering,
Genetic algorithms,
Multiobjective control,
Optimization,
Nonlinear systems,
Controllers,
Modelling
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