Uso de redes neurais com adaptação de pesos por modos deslizantes para controle de sistemas e aplicações em máquinas elétricas

Detalhes bibliográficos
Ano de defesa: 2015
Autor(a) principal: Rodrigues, Fernando Barros [UNESP]
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Estadual Paulista (Unesp)
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/11449/123817
http://www.athena.biblioteca.unesp.br/exlibris/bd/cathedra/21-05-2015/000829984.pdf
Resumo: This thesis investigates the ability of an Artificial Neural Network (ANN), with real-time adjustable weights, to execute the control systems through a tracking structure for signals in three applications: in a series of linear and non-linear systems; to control systems subject to parametric uncertainties; and to control electrical machines that may be subject to linear and nonlinear disturbances and uncertainties. In the first application of ANN, it is verified the per- formance of tracking signals in systems of 1 st , 2 nd and 3 rd order through computer simulations results. In this regard, it estimates a performance index using the Integral of the Absolute va- lue of the Error (IAE), which indicates the difference between the system real output and the reference signal value. The proposed structure with the neural network is able to work with clas- sical compensators, the proportional, integral and derivative (PID) controller. Evaluation tests are performed using controllers with variable structure and sliding mode. This strategies pre- sents robustness to a class of parametric uncertainties, called matched parametric uncertainty. However, this technique is not robust related to unmatched uncertainty class. Thus, in this paper a control strategy is proposed based on ANN through sliding mode control technique to mini- mize the uncertainties and disturbances effects. In order to show the effectiveness of proposed method, simulation results are performed using a lateral axis model of an L-1011 in cruise flight conditions subject to the uncertainties and external disturbances. Initially, it is accompli- shed of direct current (DC) motors, and after that, the technique is applied to alternating current (AC) motors (three-phase induction). Through the combination of PID controller and ANN, some evaluations tests are performed in DC motors. The performance of induction motor has been addressed ...