Abstract
In this paper, a self-tuning rule-based position control algorithm is proposed for DC motors with system parameter estimation using the recursive least squares method. First, a mathematical model of the angular position control of a DC motor was derived. Next, the time-varying parameters including the rotational inertia in the model were estimated using the RLS method along with multiple forgetting factors without prior knowledge of the system. Based on the derived model and the parameter estimation, a sliding mode control algorithm was designed by applying a self-tuning rule that enables the magnitude of the voltage input to be adaptively adjusted for improvement of the energy efficiency. The performance of the designed control algorithm was then experimentally evaluated under several different load conditions. Finally, the evaluation results show that the designed controller achieves a satisfactory capability for a DC motor to deal with both tracking accuracy and energy efficiency without prior knowledge of the system.
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Abbreviations
- v m :
-
Input voltage of a DC motor
- R m :
-
Resistance of a DC motor
- i m :
-
Current of a DC motor
- L m :
-
Inductance of a DC motor
- ω m :
-
Angular velocity of a DC motor
- J :
-
Rotational inertia of a DC motor
- T m :
-
Motor torque
- θ :
-
Estimate of recursive least squares
- φ :
-
Regressor of recursive least squares
- v :
-
Injection term of sliding mode controller
- ρ :
-
Magnitude of Injection term
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Kwangseok Oh received a B.S. degree in Mechanical Engineering from Hanyang University, Seoul in 2009 and an M.S. degree and a Ph.D. in Mechanical and Aerospace Engineering from Seoul National University, Seoul in 2013 and 2016. From 2016 to 2017, he was an Assistant Professor in the Automotive Engineering Department at Honam University. Since 2017, he has been an Assistant Professor in the Mechanical Engineering Department of Hankyong National University, Anseong-Si, South Korea. His research interests include fail-safe systems for autonomous driving, adaptive and predictive control.
Jaho Seo received his B.S. degree in Agricultural Machinery and Process Engineering from Seoul National University, Seoul, Korea in 1999, his M.E. degree in Mechanical Engineering from University of Quebec (Ecole de Technologie Superieure), Montreal, Canada in 2006, and his Ph.D. in Mechanical Engineering from University of Waterloo, Waterloo, Canada in 2011. He was with the Department of Mechanical and Mechatronics Engineering of University of Waterloo as a postdoctoral fellow in 2011, the Department of System Reliability of Korea Institute of Machinery & Materials (KIMM) as a Senior Researcher during 2012–2016, and the Department of Biosystems Machinery Engineering of Chungnam National University, Korea as an Assistant Professor during 2016–2017. Since 2017, he has been an Assistant Professor at the Department of Automotive and Mechatronics Engineering, Ontario Tech University where he has been involved in research on the development of autonomous control systems for intelligent mobile machines.
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Oh, K., Seo, J. Recursive least squares based sliding mode approach for position control of DC motors with self-tuning rule. J Mech Sci Technol 34, 5223–5237 (2020). https://doi.org/10.1007/s12206-020-1124-1
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DOI: https://doi.org/10.1007/s12206-020-1124-1