PD-Type Iterative Learning Control for Uncertain Spatially Interconnected Systems
Longhui Zhou,
Hongfeng Tao,
Wojciech Paszke,
Vladimir Stojanovic and
Huizhong Yang
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Longhui Zhou: Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, China
Hongfeng Tao: Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, China
Wojciech Paszke: Institute of Automation, Electronic and Electrical Engineering, University of Zielona Góra, 65-516 Zielona Góra, Poland
Vladimir Stojanovic: Faculty of Mechanical and Civil Engineering, Department of Automatic Control, Robotics and Fluid Technique, University of Kragujevac, 36000 Kraljevo, Serbia
Huizhong Yang: Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, China
Mathematics, 2020, vol. 8, issue 9, 1-18
Abstract:
This paper puts forward a PD-type iterative learning control algorithm for a class of discrete spatially interconnected systems with unstructured uncertainty. By lifting and changing the variable of discrete space model, the uncertain spatially interconnected systems is converted into equivalent singular system, and the general state space model is derived in view of singular system theory. Then, the state error and output error information are used to design the iterative learning control law, transforming the controlled system into an equivalent repetitive process model. Based on the stability theory of repetitive process, sufficient condition for the stability of the system along the trial is given in the form of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed algorithm is verified by the simulation of ladder circuits.
Keywords: iterative learning control; spatially interconnected systems; norm uncertainty; repetitive process; PD-type (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (4)
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