Resilient distributed MPC for systems under synchronous round-robin scheduling |
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| Authors: | Jianhua Wang Yan Song Guoliang Wei Yuying Dong |
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| Institution: | 1. School of Engineering, Huzhou University, Huzhou 313000, Zhejiang, China;2. Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;3. College of Science, University of Shanghai for Science and Technology, Shanghai 200093, China;1. Communication Engineering at Al-Hussein bin Talal University, Ma’an, Jordan;2. Electrical Engineering at Jordan University of Science and Technology, Irbid, Jordan;1. School of Electronic and Electric Engineering, Shanghai University of Engineering Science, China;2. Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin 150001, China;3. School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, China;4. School of Physics and Electronic Engineering, Guangzhou University, Guangzhou, China;1. Automatic Laboratory of Setif, Department of Electrical Engineering, Setif 1 University, Maabouda, Street of Bejaia, Setif 19000, Algeria;2. Université de Rouen, IUT, Chemical Engineering Department, Rue Lavoisier, Mont-Saint-Aignan 76130, France;1. School of Information Engineering, Fuyang Normal University, Fuyang 236041, PR China;2. College of Mathematics and Statistics, Guangxi Normal University, Guilin 541006, PR China;3. School of Information Science and Engineering, Chengdu University, Chengdu 610106, PR China;4. School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004, PR China;5. School of Mathematics, Southeast University, Nanjing 211189, China;6. Yonsei Frontier Lab, Yonser University, Seoul 03722, Korea;1. College of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China;2. College of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China;1. School of Mechanical Engineering and Mechanics, Ningbo University, Ningbo 315211, Zhejiang, China;2. The State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, China;3. Zhejiang Provincial Key Laboratory of Part Rolling Technology, Ningbo 315211, Zhejiang, China;4. College of Information Engineering, Nanjing University of Finance and Economics, Nanjing 210023, Jiangsu, China;5. School of Engineering Technology, Purdue University, 610 Purdue Mall, West Lafayette, IN 47907, America |
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| Abstract: | This paper is concerned with the resilient dynamic output-feedback (DOF) distributed model predictive control (DMPC) problem for discrete-time polytopic uncertain systems under synchronous Round-Robin (RR) scheduling. In order to alleviate the computation burden and improve the system robustness against uncertainties, the global system is decomposed into several subsystems, where each subsystem under synchronous RR scheduling communicates with each other via a network. The RR scheduling is adopted to avoid data collisions, however the updating information at each time instant is unfortunately reduced, and the underlying RR scheduling of subsystems are deeply coupled. The main purpose of this paper is to design a set of resilient DOF-based DMPC controllers for systems under the consideration of polytopic uncertainties and synchronous RR scheduling, such that the desirable performance can be obtained at a low cost of computational time. A novel distributed performance index dependent of the synchronous RR scheduling is constructed, where the last iteration information from the neighbor subsystems is used to deal with various couplings. Then, by resorting to the distributed RR-dependent Lyapunov-like approach and inequality analysis technique, a certain upper bound of the objective is put forward to establish a solvable auxiliary optimization problem (AOP). Moreover, by using the Jacobi iteration algorithm to solve such a problem online, the distributed feedback gains are directly obtained to guarantee the convergence of system states. Finally, two examples including a distillation process example and a numerical example are employed to show the effectiveness of the proposed resilient DMPC strategy. |
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