Abstract
The implementation of image-based phenotyping systems has become an important aspect of crop and plant science research which has shown tremendous growth over the years. Accurate determination of features using images requires stable imaging and very precise processing. By installing a camera on a mechanical arm driven by motor, the maintenance of accuracy and stability becomes non-trivial. As per the state-of-the-art, the issue of external camera shake incurred due to vibration is a great concern in capturing accurate images, which may be induced by the driving motor of the manipulator. So, there is a requirement for a stable active controller for sufficient vibration attenuation of the manipulator. However, there are very few reports in agricultural practices which use control algorithms. Although, many control strategies have been utilized to control the vibration in manipulators associated to various applications, no control strategy with validated stability has been provided to control the vibration in such envisioned agricultural manipulator with simple low-cost hardware devices with the compensation of non-linearities. So, in this work, the combination of proportional-integral-differential (PID) control with type-2 fuzzy logic (T2-F-PID) is implemented for vibration control. The validation of the controller stability using Lyapunov analysis is established. A torsional actuator (TA) is applied for mitigating torsional vibration, which is a new contribution in the area of agricultural manipulators. Also, to prove the effectiveness of the controller, the vibration attenuation results with T2-F-PID is compared with conventional PD/PID controllers, and a type-1 fuzzy PID (T1-F-PID) controller.
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The authors are thankful to Orebro University for reference of the logistics as a part of this study.
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Satyam Paul received the B. Eng. degree in mechanical engineering from National Institute of Technology, India in 2005. He received the M. Eng. degree in mechatronics from VIT University, India in 2009. He received the Ph.D. degree m automatic control from Department of Automatic Control, Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV-IPN), Mexico in 2017. From February 2018 to October 2018, he was a postdoctoral researcher at Tecnologico De Monterrey (ITESM), Mexico. From November 2018 to February 2020, he was a postdoctoral researcher at Department of Mechanical Engineering, Orebro University, Sweden. He has 5 years of teaching experience in the Department of Mechanical Engineering which includes universities from India and Sweden. Currently, he is a lecturer of mechatronics in Department of Engineering Design and in Mathematics, University of the West of England, UK.
His research interests include control systems, vibration control, stability analysis, fault detection and mechatronics.
Ajay Arunachalam received the M. Eng. degree in computer science & engineering from Anna University, India in 2009. He received the Ph.D. degree in computer science and information systems (CSIS) from National Institute of Development Administration (NIDA), Thailand in 2016, with specialization in distributed systems and wireless networks. Prior, to his current role, he was working as Data Scientist at True Corporation Public Company Ltd., Thailand, an Communications Conglomerate, working with Petabytes of data, building & deploying deep models in production. He is a researcher in artificial intelligence at Centre for Applied Autonomous Sensor Systems (AASS), School of Science and Technology, Orebro University, Sweden. Currently, he is a part of the Food & Health Program at the university to which he contributes with the research on Autonomous Precision Agricultural Robot. The goal is smart food production & logistics supported by artificial intelligence.
His research interests include opacity in artificial intelligence (AI) systems, machine learning, optimization, big data, algorithmic trading, natural language processing, and distributed systems & wireless networks.
Davood Khodadad received the B.Sc. degree in electrical engineering concentrating on biomedical imaging systems from Sahand University of Technology, Iran in 2008. He received the M. Sc. degree in bio-electronics from Tehran University of Medical Sciences, Iran in 2011. He received the Ph.D. degree m experimental mechanics from Lulea University of Technology, Sweden in 2016, where he focused on the development of multispectral and dual-polarization digital holography for three-dimensional imaging applied for geometry and quality control purposes. He was a post-doctoral research fellow in Waves, Signals and Systems Research Group, Linnaeus University, Sweden to focus on the development of electrical impedance tomography (EIT) and diffusion-based optical tomography to be applied in neonatal intensive care units (NICU) during the years 2016–2018. This background led to his employment at Orebro University as an associate senior lecturer until March 2020. At Orebro University, he worked on X-ray tomographic (CT) methods in order to improve image quality and apply micro CT scan for designing stronger internal structures in complex products as well as to non-destructive methods for verification of e.g., additively manufactured (AM) products. He left Orebro University when recruited to Umea University as an associate professor at the Department of Applied Physics and Electronics. Currently, he is an associate professor at Department of Applied Physics and Electronics, Umea University, Sweden.
His research interests include digital holography, imaging systems, speckle metrology and optical metrology.
Henrik Andreasson received the M. Sc. degree in mechatronics from the Royal Institute of Technology (KTH), Sweden in 2001, and the Ph.D. degree in computer science from Orebro University, Sweden in 2008. He is currently an associate professor with Center for Applied Autonomous Sensor Systems (AASS), School of Science and Technology, Orebro University, Sweden.
His research interests include mobile robotics, computer vision, and machine learning.
Olena Rubanenko received the B. Eng degree and the M. Sc. degrees in electrical systems and networks from Vinnytsia National Technical University, Ukraine in 2006 and 2007. She received the Ph. D. degree from Department of Electric Systems and Stations, Vinnitsya National Technical University, Ukraine in 2011. She is a researcher in Department of Electric Systems and Stations at the Vinnitsya National Technical University, Ukraine. After that, she was a doctoral student in electric stations, networks, and systems at Vinnytsia National Technical University, Ukraine. From April 2019 to December 2020, she was a postdoctoral researcher of a Regional Innovational Center, Faculty of Electrical Engineering, University of West Bohemia in Pilsen, Czech Republic. She has 9 years of teaching experience in Department of Electric Systems and Stations, Vinnitsya National Technical University, Ukraine.
Her research interests include renewable energy sources, power control, neuro fuzzy modeling and machine learning.
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Paul, S., Arunachalam, A., Khodadad, D. et al. Fuzzy Tuned PID Controller for Envisioned Agricultural Manipulator. Int. J. Autom. Comput. 18, 568–580 (2021). https://doi.org/10.1007/s11633-021-1280-5
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DOI: https://doi.org/10.1007/s11633-021-1280-5