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Distributed predictive control of continuous-time systems

机译:连续时间系统的分布式预测控制

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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.
机译:在过去的几年中,重点一直放在分布式模型预测控制(MPC)算法的开发上。除少数例外,它们大多是在离散时间框架中开发的。但是,大规模系统的离散化可能会破坏原始连续时间模型的稀疏性,从而使分布式控制设计和实现更加困难。而且,更一般而言,连续时间系统的离散时间控制不允许考虑过程互采样行为。在本文中,我们提出了一种基于鲁棒MPC概念的连续时间系统的新型非合作式分布式预测控制算法。陈述了所提出控制方案的收敛性,并通过仿真案例研究了其可实现性。

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