Constrained off-line synthesis approach of model predictive control for networked control systems with network-induced delays |
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| Affiliation: | 1. Key Laboratory of Industrial Internet of Things & Networked Control, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing 400065, PR China;2. College of Automation, Chongqing University, Chongqing 400044, PR China;1. College of Mechanical Engineering, Taiyuan University of Technology, Taiyuan, Shanxi 030024, PR China;2. School of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK;3. Signal Processing and Algorithms Group, School of Engineering, Manchester Metropolitan University, All Saints Building, All Saints, Manchester M15 6BH, UK;4. College of Mechanical Engineering, Taiyuan University of Science and Technology, Taiyuan, Shanxi 030024, PR China;1. Electrical Engineering Department, National School of Engineering of Monastir (ENIM), Av Ibn Al Jazzar, Monastir 5019, Tunisia;2. Electrical Engineering Department, High Institute of Applied Science and Technology (ISSAT), Cité Ibn Khaldoun, Sousse 4003, Tunisia;1. Chemical Engineering Sciences Division Indian Institute of Chemical Technology Hyderabad 500 007, India;2. Anurag group of Institutions Hyderabad 501301, India;3. Chemical Engineering Department Padmasri Dr BV Raju Institute of Technology Narsapur 502313, India |
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| Abstract: | This paper investigates the off-line synthesis approach of model predictive control (MPC) for a class of networked control systems (NCSs) with network-induced delays. A new augmented model which can be readily applied to time-varying control law, is proposed to describe the NCS where bounded deterministic network-induced delays may occur in both sensor to controller (S–A) and controller to actuator (C–A) links. Based on this augmented model, a sufficient condition of the closed-loop stability is derived by applying the Lyapunov method. The off-line synthesis approach of model predictive control is addressed using the stability results of the system, which explicitly considers the satisfaction of input and state constraints. Numerical example is given to illustrate the effectiveness of the proposed method. |
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| Keywords: | Model predictive control Networked control systems Robust control Lyapunov method Network-induced delays |
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