Abstract

Flexible manipulators have numerous advantages such as lightweight, high operation speed, and low power consumption. However, they suffer from link vibrations, especially when operated at high speeds followed by sudden stops. This limitation has been addressed using techniques such as adaptive filters, adaptive strain feedback gain, state feedback control, etc. This article presents a filtered inverse controller for the mitigation of link vibrations in a multi-link flexible manipulator. To this end, the plant model, developed and linearized in Maple/Maplesim was inverted in MATLAB. The internal dynamics of the inverse model were stabilized using the state feedback technique. For safe and high-speed operations, the inverse model was augmented with a low pass filter to form the filtered inverse which was used as feedforward controller. Practical experiments were carried out in the dSPACE environment. Results show that filtered inverse controller yield not only faster response but relatively minimal link vibration when compared with the manipulator without vibration controller.

Highlights

  • Flexible manipulators have become popular owing to their numerous advantages in comparison to the rigid manipulators such as light weight

  • We developed an inverse controller and proposed a controller to stabilize the internal dynamics of the otherwise unstable inverse model

  • The main difference between the proposed approach and input shaping is that whereas the trajectories are fixed in the latter method, different joint trajectories can be used with inverse controller

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Summary

Introduction

Flexible manipulators have become popular owing to their numerous advantages in comparison to the rigid manipulators such as light weight. One of the earliest technique of dealing with precise positioning of the end effector by damping out the link vibrations is the state feedback control. In [4], the application of state feedback on a two link, two joints system with distributed flexibility is presented. We developed an inverse controller and proposed a controller to stabilize the internal dynamics of the otherwise unstable inverse model.

Results
Conclusion
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