Optimal positioning of piezoelectric actuators on a smart fin using bio-inspired algorithms |
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| Institution: | 1. Department of Biomedical Engineering, National University of Singapore, Singapore 117575, Singapore;2. School of Mechanical & Electrical Engineering, Zhongyuan University of Technology, Zhengzhou 450007, China;3. Department of Exercise and Sports Science, Zhejiang University, Hangzhou 310028, China;1. School of Computer and Information Science, Southwest University, Chongqing 400715, China;2. Department of Computing, Macquarie University, Sydney, NSW 2109, Australia;3. School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China;4. School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane, QLD 4000, Australia;5. Corporate Analytics, The Australian Taxation Office, Sydney NSW 2000, Australia;6. Provincial Key Laboratory for Network Based Intelligent Computing, University of Jinan, Jinan 250022, China;1. Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia;2. Department of Engineering, University of Cambridge, Trumpington Street, CB2 1PZ Cambridge, UK;1. University of Pittsburgh, Graduate School of Public Health, Department of Epidemiology, PA, USA;2. University of Pittsburgh, School of Medicine, Department of Psychiatry, PA, USA;3. Lupus Center of Excellence, Autoimmunity Institute, Department of Medicine, Allegheny Health Network, PA, USA;4. Department of Medicine, Los Angeles Biomedical Research Institute, Torrance, CA, USA;1. State Key Laboratory of Hybrid Process Industry Automation Systems and Equipment Technology, Automation Research and Design Institute of Metallurgical Industry, China Iron & Steel Research Institute Group, Bejing 100081, PR China;2. State Key Laboratory of Intelligence Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Bejing 100084, PR China |
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| Abstract: | In this paper a novel approach is developed for optimization of piezoelectric actuators in vibration suppression. A scaled model of a vertical tail of F/A-18 is developed in which piezoelectric actuators are bounded to the surface. The frequency response function (FRF) of the system is then recorded and maximization of the FRF peaks is considered as the objective function of the optimization algorithm to enhance the actuator authority on the mode, which assigns the optimal placement of the pair of piezoelectric actuators on the smart fin. Six multi-layer perceptron neural networks are employed to perform surface fitting to the discrete data generated by the finite element method (FEM). Invasive weed optimization (IWO), a novel numerical stochastic optimization algorithm, is then employed to maximize the FRF peak which in due reduces the vibration of the smart fin. Results indicated an accurate surface fitting for the FRF peak data as well as the optimal placement of the piezoelectric actuators for vibration suppression. |
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