Abstract
Electro-hydraulic servo systems (EHSSs) are nonlinear and uncertain due to their inappropriate fluid levels, air temperature, friction, and leakage. The finite-time tracking control is difficult with the use of a proportional, integral, and derivative (PID) controller, which no longer provides adequate and achievable control performance over the whole operating range. This has led to the idea of an iterative learning controller (ILC). An intelligent and memory-based learning control approach that attempts to imitate the human way of thinking. The proposed ILC has an additional learning gain, learning filter, and robustness filter to enhance the finite-time tracking performance and stability improvement. This study is focused on the design of the ILC to regulate the servo spool valve of an EHSS, which in turn controls the displacement of a hydraulic cylinder. In simulation and experimentation, vital parameters such as overshoot and settling time in the varieties of tests, the ILC has shown better results when compared to conventional PID controllers. In step input tracking at different operating points over 0-250 mm, the ILC has 40% less overshoot and settles 12-15 s faster than the PID controller. In sinewave tracking and disturbance rejection, the PID controller performs better than the ILC in integral square error and integral absolute error as the error indices are not considered as the objective function in the design of the controller. During a robustness test, the ILC rejects the uncertainty, which evidences the effectiveness of the proposed controller.
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No potential conflict of interest was reported by the authors.
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Notes on contributors
C. Naveen
Naveen C received his post graduate degree in mechatronics engineering from Anna University, Coimbatore, Tamil Nadu, India in 2011. He is working as an associate professor (senior grade) in mechatronics engineering at Kongu Engineering College since 2012. His research interests include nonlinear control and automation. Corresponding author. Email: [email protected]
B. Meenakshipriya
B Meenakshipriya received her PhD in mechanical engineering from Anna University, Chennai, Tamil Nadu, India in 2013. She is currently working as a professor and head of Mechatronics Engineering at Kongu Engineering College, Erode, Tamil Nadu, India since 2006. She has 16 years of teaching and research experience. Her research interests include mechatronics, robotics and control, and machine learning algorithms. He has supervised 2 doctoral students. Email: [email protected]
A. Tony Thomas
Tony Thomas A received his post graduate degree in mechatronics engineering from Anna University, Coimbatore, Tamil Nadu, India in 2009. He is working as an associate professor (senior grade) in Mechatronics Engineering at Kongu Engineering College since 2010. His research interests include EHSS, low-cost automation, and composite materials. He has supervised 4 post graduate students. Email: [email protected]
S. Sathiyavathi
S Sathiyavathi received her PhD degree in mechanical engineering from Anna University, Chennai, Tamil Nadu, India in 2014. She is currently working as an associate professor in Mechatronics Engineering at Kongu Engineering College, Erode, Tamil Nadu, India since 2008. She has 14 years of teaching and research experience. Her research interests include mechatronics and process control. He has supervised 1 doctoral student. Email: [email protected]
S. Sathishbabu
S Sathishbabu received his PhD in instrumentation from Annamalai University in 2013. He has nearly 16 years of teaching experience. His research interests are in the areas of process control, biomedical, and image processing. He is currently working as an associate professor in the Department of Electronics and Communication Engineering, Thanthai Periyar Government Institute of Technology, Vellore. Email: [email protected]