Solving a reliability-performance balancing problem for control systems with degrading actuators under model predictive control framework |
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| Institution: | 1. Hangzhou Innovation Institute, Beihang University, Zhejiang 310052, China;2. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China;1. Business School, University of Shanghai for Science and Technology, Shanghai 200093, China;2. The Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment, Ministry of Education, and School of Mathematics–Physics and Finance, Anhui Polytechnic University, Wuhu, 241000, China;3. Department of Mathematics and Statistics, University of Strathclyde, Glasgow G1 1XH, UK;4. Department of Statistics, College of Science, Donghua University, Shanghai 201620, China;1. The Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, Zhejiang, 310027, China;2. The School of Mathematics and Informational Science, Yantai University, Yantai, Shandong, 264005, China;3. The Institute for Advanced Study, Chengdu University, Chengdu, Sichuan, 610106, China;1. School of Mathematics and Computer Science, Yunnan Minzu University, Kunming 650504, China;2. School of Mathematics, Southeast University, Nanjing 210096, China;3. Yonsei Frontier Lab, Yonsei University, Seoul 03722, South Korea;4. Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia;1. School of Information Engineering, Henan University of Science and Technology, Luoyang 471023, PR China;2. Department of Automatic Control, Robotics and Fluid Technique, Faculty of Mechanical and Civil Engineering, University of Kragujevac, Kraljevo 36000, Serbia |
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| Abstract: | In this paper, we formulate and study a reliability-performance balancing problem (RPBP) for long-term operational and unattended control systems with degrading actuators. It preliminarily explores a new type of autonomous maintenance method to extend the useful lifetime of the control system. The actuator, as the crucial component of a control system, executes calculated control actions and thereby is often exposed to the high-load working environment. As the actuator degrades, the control action will gradually alter with increasing magnitude to maintain the desired control performance, but this will accelerate the actuator degradation and thus reduce the useful lifetime (use reliability) of the control system. Therefore, conditionally balancing the control performance and use reliability is meaningful, for which a novel dynamic regulation strategy under the model predictive control (MPC) framework is proposed. Specifically, we model the actuator degradation using a diffusion Wiener process coupled with the control action or system state, and the corresponding actuator reliability is derived. By fusing the degradation model and system dynamics, a degradation-incorporated state space (DISS) model is formulated, in which the basic idea is to consider the actuator degradation as an extended state variable and to control it accordingly. Based on the DISS model, a mixed-index nonlinear MPC integrated with a weight tuning strategy is proposed to achieve a satisfactory balance between control performance and use reliability in the presence of actuator degradation. Further, the reference curve and the upper bound of actuator degradation are given for constructing the objective function and the constraint in the MPC optimization problem. An illustrative example is presented to demonstrate the availability of the proposed method. |
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