Controle por modelo de referência de sistemas incertos baseado no algoritmo
Ano de defesa: | 2018 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal do Rio de Janeiro
Brasil Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia Programa de Pós-Graduação em Engenharia Elétrica UFRJ |
Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | http://hdl.handle.net/11422/11674 |
Resumo: | In this dissertation, a higher order sliding mode controller is proposed for uncertain and monovariable systems with relative degree one. The solution is based on the super-twisting algorithm and on the model reference adaptive control paradigm, considering only output-feedback. The control algorithm is implemented using variable gains to deal with a wide class of uncertainties/disturbances. First order approximation filters are used to enable a solution that do not depend on the availability of the system states for the control implementation. The proposed strategy guarantees exact tracking to a reference model with global convergence propoerties in finite time. Furthermore, this approach based on the model reference adaptive control provide a natural structure for the application of nominal values to uncertain parameters of the plant, providing a control effort reduction. Simulation results exemplify the effectivity of the proposed control strategy. In addition, a comparison to the recently proposed in the literature output-feedback variable gains super-twisting algorithm solution is made. In the latter, the control is obtained using the normal form of the system and estimating the norm of unmeasured states. |