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Improved data-driven optimal TILC using time-varying input signals
Affiliation:1. School of Automation & Electronics Engineering, Qingdao University of Science & Technology, Qingdao 266042, PR China;2. Advanced Control Systems Lab, School of Electronics & Information Engineering, Beijing Jiaotong University, Beijing 100044, PR China;3. EXQUISITUS, Centre for E-City, School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore;1. Institute of Cyber-Systems and Control, National Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, 310027 Zhejiang, China;2. Department of Chemical Engineering, Chung-Yuan Christian University, Chung-Li 320, Taiwan, ROC;1. ISCPIF, LIP6, France;2. LIP6, IRSTEA, France;3. IRSTEA, France;4. ISCPIF, France;5. INRA, UMR 782 GMPA génie Microbiologique des Procédés alimentaires, France;1. Department of Electrical Engineering, University of South Carolina, Columbia SC, USA;2. College of Automation Engineering, Nanhang University, Nanjing, Jiangsu, China;3. Department of Electrical and Computer Engineering, University of Canterbury, New Zealand;4. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;1. The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;2. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China;3. School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
Abstract:A new improved data-driven optimal TILC (DDOTILC) is proposed for a class of nonlinear discrete-time systems by using time-varying control input signals to enhance control performance. An equivalent dynamical linear presentation is developed in the iteration domain for the repeatable nonlinear system, where the time-varying partial derivatives of the system with respect to the time-varying control inputs reflect the dynamical characters of the plant. Both the time-varying input signals and time-varying partial derivatives over the entire finite time interval are updated in batches, respectively. The proposed approach is a data-driven control scheme and only the boundedness of the partial derivatives is needed for control system design and analysis. Both rigorous mathematical analysis and the simulation results are provide to verify the applicability and effectiveness of the proposed approach further.
Keywords:Data-driven control  Optimal terminal ILC  Time-varying input signals  Multiple time-varying partial derivatives  Nonlinear discrete-time systems
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