Um controlador Fuzzy-Adaptativo em cascata com Multi-Sensores para o aumento da exatidão na posição do AGV seguidor de linha

Abstract

Automated Guided Vehicles (AGVs) have been used in manufacturing environments for over five decades. The technologies applied to AGVs advanced along with electronics and computing technology progress, which increased vehicles' sensory and processing capacity. Currently, such vehicles are applied to internal logistics systems and industries' shop floor, but they are also used in different environments. As a guided system, position control is essential for the system. A good control system performance allows a safe application of AGV in the environment and impacts the performance of a production line, for example. Many solutions have been proposed in the literature. However, there are still factors that still need to be considered. Two of these factors are vehicle dynamics under different load conditions and the application of multiple measurements to reduce measurement uncertainties and improve controller performance. Since AGV is a complex system, several system variables can be measured, and the problem can be treated as a multivariable problem. In this condition, using multiple sensors allied with the controller's adaptive capacity following the load condition is expected to contribute positively to the control system's performance and increase its accuracy. Thus, this work aims to present the proposal of a cascaded and multi-sensors adaptive fuzzy controller for the AGVs position control problem. The proposed system aims to increase the accuracy of the AGV position.