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A Robust Adaptive Controller for Automated Guided Vehicle (AGV)
Van Vu
Division:
Mathematics and Sciences
Department:
Engineering
Mentor:
Angelo Esposito
Mentor's e-mail:
aesposito1@occ.cccd.edu
Author's e-mail:
vvu109@student.cccd.edu
Abstract:

In this research, an adaptive controller for an Automated Guided Vehicle (AGV) will be introduced. This controller is designed to make the AGV adapt to a variety of loads as it carries heavy objects and travels along an assembly line. Moreover, the controller robustness and simplicity allow the use of only one tracking device. The controller is separated into two levels: the first level receives a signal from the tracking device and creates a velocity profile for rectilinear and curvilinear paths based on the linearization of its kinematic equations. This velocity profile then becomes the input for the adaptive processor, the second level control, whose design is based on the Model Reference Adaptive Control (MRAC) method, and its goal is to obtain the controlling signal for the vehicle’s motors. The stability of the controller is evaluated based on Lyapunov’s test for nonlinear systems, and a program written in MATLAB language was used to simulate the activity of the AGV. In the simulation, the vehicle could not follow the assembly line layout with the required speed when the adaptive processor is disabled. When the adaptive control is applied, the vehicle follows exactly the assembly line while carrying goods, or machine parts, without any prior knowledge of the loads size and shape. Thus, this controller will allow the AGV to be more versatile, and enable it to carry also heavy components (e.g. vehicle chassis and engine) along the assembly line.

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