Análise de desempenho de trajetória de AGV seguidor de linha usando controle Fuzzy adaptativo

• Ano de defesa: 2017
• Autor(a) principal: Rodrigues Junior, Flavio Antonio
• Orientador(a): Morandin Júnior, Orides
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciência da Computação - PPGCC
• Palavras-chave em Português: AGV; Dinâmica; Desempenho; Sistemas de controle; Controle fuzzy adaptativo; PID; Acurácia; Precisão
• Palavras-chave em Inglês: Dynamics; Control performance; Control system; Adaptive fuzzy control; PID control; Position; Orientation; Accuracy; Precision
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA ELETRICA::ELETRONICA INDUSTRIAL, SISTEMAS E CONTROLES ELETRONICOS
• Link de acesso: https://repositorio.ufscar.br/handle/ufscar/10039

Dynamics of automatic vehicle movement (Automatic Guided Vehicle), its associated with your control system, and the adoption of traditional control techniques, whose parameter and tuning are performed based on linear gains constants of this systems, may presents satisfactory performance and results in linear moments. However, when considered moments, phenomenon of dynamic movement is present, control systems with linear characteristics are insufficient. With these problems, its necessary adoption of control systems able to adapt to these parameter variations. The object of study in this research is a AGV follow line with differential traction, using adaptive fuzzy control systems, whose aim to reduce errors in trajectory tracking, looking for results of accuracy and precision of the vehicle in the follow of trajectory. The adaptive fuzzy control technique applied to the phenomenon of vehicle movement, mapping it intuitively through linguistic variables. As a method of comparison, is applied classic control technique PID, and used to validation adaptive fuzzy control technique with comparison of results on test scenarios, with different roads proposed to vehicle associated with weight variation. It was possible to verify that the control results when applied to control orientation of AGV, vehicle achieves stability and keeps its errors close to the reference systems value, however in the PID control system the orientation errors are visible during the trajectory tracking and through graphical perspective analysis, showing that the PID control system is not adaptable to weight and track variations. Another point of feasibility of applying the adaptive fuzzy control system, within the application is the tuning of its parameters, which once adjusted were sensitive to the variation of load and trajectories managing to maintain rates of errors up to 80% smaller them to the PID control, validating the research and demonstrating the applicability of adaptive fuzzy control systems within the problem domain.