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Position control for planar four-link underactuated manipulator with a passive third joint.

Dong Liu1, Xuzhi Lai1, Yawu Wang1

  • 1School of Automation, China University of Geosciences, Wuhan, Hubei 430074, China; Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan, Hubei 430074, China.

ISA Transactions
|December 8, 2018
PubMed
Summary

This study introduces a novel position control strategy using the differential evolution (DE) algorithm for planar four-link underactuated manipulators (PFUMs). The method effectively guides the manipulator

Keywords:
Differential evolution algorithmModel reductionNonholonomic systemPlanar underactuated manipulatorPosition control

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Area of Science:

  • Robotics
  • Control Systems
  • Artificial Intelligence

Background:

  • Underactuated manipulators present significant control challenges due to fewer actuators than degrees of freedom.
  • Planar four-link underactuated manipulators (PFUMs) with passive joints require advanced control strategies for precise end-point positioning.
  • Existing control methods may struggle with the complex dynamics and angle constraints inherent in such systems.

Purpose of the Study:

  • To develop and validate a robust position control strategy for a planar four-link underactuated manipulator (PFUM).
  • To utilize the differential evolution (DE) algorithm for optimizing control objectives in reduced-order models of the PFUM.
  • To address the angle constraints in the planar Acrobot model during the control strategy development.

Main Methods:

  • A model reduction technique is applied to simplify the PFUM into a virtual three-link manipulator and a planar Acrobot.
  • The differential evolution (DE) algorithm is employed to optimize control objectives and find target angles for the reduced systems.
  • Simulations are conducted to evaluate the performance of the proposed control strategy.

Main Results:

  • The proposed DE-based control strategy successfully achieves end-point positioning for the PFUM.
  • Model reduction effectively simplifies the complex dynamics of the PFUM for control design.
  • The DE algorithm efficiently optimizes control parameters and resolves angle constraints in the Acrobot model.

Conclusions:

  • The differential evolution algorithm provides an effective approach for position control of planar four-link underactuated manipulators.
  • Model reduction combined with DE optimization offers a viable solution for controlling complex underactuated robotic systems.
  • The validated strategy demonstrates the potential for precise end-point trajectory control in PFUMs.