Adaptive vibration control of a flexible structure based on hybrid learning controlled active mass damping |
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| Institution: | 1. School of Artificial Intelligence, Anhui University, Hefei 230601, China;2. School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China;3. School of Automation, Southeast University, Nanjing 210096, China;1. Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China;2. School of Automation Science and Electrical Engineering, Beihang University, Beijing, China;3. School of Mathematics and Statistics, Shandong University of Technology, Zibo, China;1. University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan, Guangdong 528402, China;2. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China;3. School of Automation, Guangdong University of Technology, Guangzhou, Guangdong 510006, China;1. School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, 215009, PR China;2. Department of Mechanical Engineering, Politecnico di Milano, Milan, 20156, Italy;3. Guangxi Key Lab of Multi-Source Information Mining and Security, Guangxi Normal University, Guilin, 541004, PR China;1. Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, PR China;2. The School of Cyber Science and Technology, Beihang University, Beijing 100191, PR China;1. School of Information and Automation, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China;2. College of Information Science and Technology, Donghua University, Shanghai 201620, China;1. School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110809, China;2. Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China;3. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China;4. Department of Electromechanical Engineering, University of Macau, Taipa 999078, Macao;5. Tianjin Tanhas Group Corporation, Tianjin 301600, China |
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| Abstract: | Natural disasters such as earthquakes and strong winds will lead to vibrations in ultra-high or high-rise buildings and even the damages of the structures. The traditional approaches resist the destructive effects of natural disasters through enhancing the performance of the structure itself. However, due to the unpredictability of the disaster strength, the traditional approaches are no longer appropriate for earthquake mitigation in building structures. Therefore, designing an effective intelligent control method for suppressing vibrations of the flexible buildings is significant in practice. This paper focuses on a single-floor building-like structure with an active mass damper (AMD) and proposes a hybrid learning control strategy to suppress vibrations caused by unknown time-varying disturbances (earthquake, strong wind, etc.). As the flexible building structure is a distributed parameter system, a novel finite dimension dynamic model is firstly constructed by assumed mode method (AMM) to effectively analyze the complex dynamics of the flexible building stucture. Secondly, an adaptive hybrid learning control based on full-order state observer is designed through back-stepping method for dealing with system uncertainties, unknown disturbances and immeasurable states. Thirdly, semi-globally uniformly ultimate boundedness (SGUUB) of the closed-loop system is guaranteed via Lyapunov’s stability theory. Finally, the experimental investigation on Quanser Active Mass Damper demonstrates the effectiveness of the presented control approach in the field of vibration suppression. The research results will bring new ideas and methods to the field of disaster reduction for the engineering development. |
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