Distributed predictive control of continuous-time systems |
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| Affiliation: | 1. Department of Automation, School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China;2. National Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China;3. College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;1. State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, China;2. Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, United States;3. National Center for International Research on Quality-targeted Process Optimization and Control, China |
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| Abstract: | In the last years focus has been put in the development of distributed Model Predictive Control (MPC) algorithms. With a few exceptions, they have been mostly developed in the discrete-time framework. However, discretization of large-scale systems may destroy the sparsity of the original continuous-time models, making distributed control design and implementation more difficult. Also, more in general, discrete-time control of continuous-time systems does not allow to consider the process inter-sampling behavior. In this paper we present a novel non-cooperative distributed predictive control algorithm for continuous-time systems based on robust MPC concepts. The convergence properties of the proposed control scheme are stated, and its realizability is tested through a simulation case study. |
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| Keywords: | Distributed control Continuous-time systems Model predictive control Robust control |
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