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Controller tuning based on optimization algorithms of a novel spherical rolling robot

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Abstract

This study presents the construction process of a novel spherical rolling robot and control strategies that are used to improve robot locomotion. The proposed robot drive mechanism is constructed based on a combination of the pendulum and wheel drive mechanisms. The control model of the proposed robot is developed, and the state space model is calculated based on the obtained control model. Two control strategies are defined to improve the synchronization performance of the proposed robot motors. The proportional-derivative and proportional-integral-derivative controllers are designed based on the pole placement method. The proportional-integral-derivative controller leads to a better step response than the proportional-derivative controller. The controller parameters are tuned with genetic and differential evaluation algorithms. The proportional-integral-derivative controller which is tuned based on the differential evaluation algorithm leads to a better step response than the proportional-integral-derivative controller that is tuned based on genetic algorithm. Fuzzy logics are used to reduce the robot drive mechanism motors synchronizing process time to the end of achieving a high-performance controller. The experimental implementation results of fuzzy-proportional-integral-derivative on the proposed spherical rolling robot resulted in a desirable synchronizing performance in a short time.

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Authors and Affiliations

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Correspondence to Mehdi Tale Masouleh.

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Recommended by Associate Editor Kyoungchul Kong

Rasoul Sadeghian obtained a B.Sc. in Applied Mathematics from the Vli-E Asr University of Rafsanjan, Kerman, Iran. He obtained an M.Sc. in Mechatronics Engineering from the Islamic Azad University Qazvin, Iran. His thesis was titled “Design, Analysis, and Development of a Spherical Mobile Robot and Path Planning Based on Visual Servoing Concepts”. He has been a member of Human-Robot Interaction Laboratory (known as TaarLab for its Persian abbreviation) since January 2013. His research interests include the kinematics, dynamics and control of mobile robots.

Mehdi Tale Masouleh obtained a B.Eng., M.Sc. and Ph.D. in Mechanical Engineering (Robotics) from Laval University, Québec, Canada, in 2006, 2007 and 2010, respectively. He is currently a faculty member of the Faculty of New Sciences and Technology of the University of Tehran. He is the Director of the Human-Robot Interaction Laboratory (known as TaarLab for its Persian abbreviation). His research interests include the kinematics, dynamics, and design of serial and parallel robotic systems, as well as humanoids, mobile robots, and optimization techniques (i.e., interval analysis and convex optimization) for robotic applications. He is also the Director of a national- level project for a haptic dental simulator.

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Sadeghian, R., Masouleh, M.T. Controller tuning based on optimization algorithms of a novel spherical rolling robot. J Mech Sci Technol 30, 5207–5216 (2016). https://doi.org/10.1007/s12206-016-1038-0

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  • DOI: https://doi.org/10.1007/s12206-016-1038-0

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