Análise de desempenho de trajetória de AGV seguidor de linha usando controle Fuzzy adaptativo
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2017-08-17Autor
Rodrigues Junior, Flavio Antonio
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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.
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