Projeto de controle por modos deslizantes fuzzy adaptativo para robôs móveis com rodas na resolução do problema de rastreamento de trajetória
Ano de defesa: | 2016 |
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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 Estadual de Maringá
Brasil Departamento de Informática Programa de Pós-Graduação em Ciência da Computação UEM Maringá, PR Centro de Tecnologia |
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://repositorio.uem.br:8080/jspui/handle/1/2549 |
Resumo: | This paper proposes the use of an adaptive fuzzy sliding mode controller (kinematic control) integrated with an inverse dynamic control with proportional plus derivative control (dynamic control) applied to the trajectory tracking problem for a differential wheeled mobile robot, subject the uncertainties and disturbances. The sliding mode controller is a well known, proven control method, fit to deal with uncertainties and disturbances (e.g., structural and parameter uncertainties, external disturbances and operating limitations). To minimize the problems found in practical implementations of the classical sliding mode controller, a Mamdani type adaptive fuzzy logic controller replaces the discontinuous portion of the control signals present in classical forms, causing the loss of invariance, but still ensuring the robustness to uncertainties and disturbances without having any a priori knowledge of their boundaries, avoiding the chattering. Moreover, the adaptive fuzzy logic controller is a feasible tool to approximate any real continuous nonlinear system to arbitrary accuracy, and has a simple structure by using triangular membership functions, a low number of rules that must be evaluated, resulting in a lower computational load for execution, making it feasible for real time implementation. Stability analysis and the convergence of tracking errors as well as the adaptation laws are guaranteed with basis on the Lyapunov theory. Simulation and experimental results are explored as verification and validation of the proposed control strategy. |