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Distributed Model Predictive Control Design for Parameter-Invariant and Parameter-Varying Spatially-Distributed Systems in Input/Output Form

输入/输出形式的参数不变和参数变化的空间分布式系统的分布式模型预测控制设计

基本信息

批准号：
280664448
负责人：
Dr.-Ing. Qin Liu
金额：
--
依托单位：
Complex Systems Control Laboratory
依托单位国家：
德国
项目类别：
Research Fellowships
财政年份：
2015
资助国家：
德国
起止时间：
2014-12-31 至 2015-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/280664448?language=en
关键词：
Distributed Model Predictive Control Design

项目摘要

Distributed model predictive control (MPC) design has become an active research area in the last decade to deal with large, networked systems by explicitly taking input, output and state constraints into account with certain performance criterion satisfied. The networked systems can either be physically coupled, e.g. distributed parameter systems, or comprised of several independent subsystems coupled via constraints or a common objective, e.g. multi-agent systems. Centralized control often fails to realize an effective control due to high level of connectivity and computational burden. The distributed framework that handles a complex and large-scale system on a single subsystem of small order is appealing in terms of synthesis and implementation. Among the published works on distributed MPC design, the vast majority of them relies on state-space representation of system dynamics, and develops analysis and synthesis conditions in state-space form. In this project, distributed MPC design for spatially-distributed systems in input/output form will be studied. The importance of input/output design is related to the fact that experimentally identified models are in input/output form. It is then natural to solve for controllers based on input/output dynamics and implement designed controllers digitally in practice. Furthermore, distributed control design with fixed structure (of predefined temporal and spatial orders) is explored here to be implemented as a local control law. Compared to the state-space full-order control design, the distributed fixed-structure controller in input/output form of smaller order alleviates extensive on-line calculation between two sampling instants in MPC.Knowing that spatially-distributed systems can be treated as the interconnection of an array of subsystems, considered here are distributed MPC design for both parameter-invariant systems, whose subsystems exhibit identical dynamics, and distributed systems which consist of time/space varying subsystems and can be characterized as temporal/spatial linear parameter-varying (LPV) models. The distributed MPC design is studied in this project to address the regulator problem, which can be easily extended later to solve the set point tracking problem. With the use of a finite prediction horizon, asymptotic stability and performance specifications will be addressed in the derivation of distributed MPC design conditions, which can be cast into linear matrix inequality (LMI) constraints to render the problems implementable and numerically tractable. The proposed methods on distributed MPC design for both parameter-invariant and -varying spatially-distributed systems will be tested and evaluated on PDE governed spatially-distributed systems.

分布式模型预测控制（MPC）设计在过去十年中已经成为一个活跃的研究领域，以处理大型，网络化系统，明确考虑输入，输出和状态约束，满足一定的性能标准。网络化系统可以是物理耦合的，例如分布参数系统，或者由通过约束或共同目标耦合的几个独立子系统组成，例如多智能体系统。集中式控制往往由于高水平的连接性和计算负担而无法实现有效的控制。分布式框架，处理一个复杂的和大规模的系统上的一个单一的子系统的小订单是有吸引力的综合和实施。在已发表的分布式MPC设计的工作中，绝大多数依赖于系统动力学的状态空间表示，并以状态空间形式开发分析和综合条件。在本计画中，将研究输入/输出形式的空间分布系统的分散式MPC设计。输入/输出设计的重要性与实验确定的模型是输入/输出形式的事实有关。然后，很自然地解决基于输入/输出动态的控制器，并在实践中以数字方式实现所设计的控制器。此外，分布式控制设计与固定的结构（预定义的时间和空间顺序）在这里探索实现为一个本地控制律。与状态空间全阶控制器设计相比，采用低阶输入输出形式的分布式固定结构控制器，在MPC中两个采样时刻之间的大量在线计算被简化。空间分布系统可以看作是一系列子系统的互连，本文考虑了两个参数不变系统的分布式MPC设计，其中两个子系统具有相同的动态特性，以及由时/空变化子系统组成的分布式系统，其可以被表征为时/空线性变参数（LPV）模型。本计画研究分散式预测控制器的设计，以解决调节器的问题，并可在后续的研究中加以扩充，以解决设定值追踪的问题。随着使用有限的预测范围，渐近稳定性和性能规格将在分布式MPC设计条件，它可以被转换成线性矩阵不等式（LMI）的约束，使问题的可实现性和数值上易于处理的推导。所提出的分布式MPC设计的参数不变和变化的空间分布系统的方法将进行测试和评估偏微分方程管辖的空间分布系统。