Model Reference Adaptive Control and Fuzzy Neural Network Synchronous Motion Compensator for Gantry Robots

A model reference adaptive control and fuzzy neural network (FNN) synchronous motion compensator for a gantry robot is presented in this paper. This paper proposes the development and application of gantry robots with MRAC and FNN online compensators. First, we propose a model reference adaptive controller (MRAC) under the cascade control method to make the reference model close to the real model and reduce tracking errors for the single axis. Then, a fuzzy neural network compensator for the gantry robot is proposed to compensate for the synchronous errors between the dual servo motors to improve precise movement. In addition, an online parameter training method is proposed to adjust the parameters of the FNN. Finally, the experimental results show that the proposed method improves the synchronous errors of the gantry robot and demonstrates the methodology in this paper. This study also successfully integrates the hardware and successfully verifies the proposed methods.

Gantry Robot for Mobile Observation

A gantry robot consists of a manipulator mounted onto an overhead system that allows movement across a horizontal plane. Gantry robots are also called Cartesian or linear robots. They are usually large systems that perform pick and place applications, but they can also be used in welding and other applications like for observing the behavior of patient in hospital wards. Fast motion of a gantry robot is usually associated with undesirable induced oscillations of the suspended object. Because of these oscillations, gantry robot maneuvers are performed slowly contributing to low site efficiency and high transportation costs. These undesirable oscillations can be minimized at reasonably high travel speeds by designing effective controllers. To solve this problem precaution should also be considered as not to use unbalanced structure and also the most important was the mechanism of the robot. The robot structure requires high stability so that when the camera housing is positioned to the required locations it will not disturbed and ensure safety to the patient.