Modular distributed model predictive control of nonlinear neighbor-affine systems

非线性邻域仿射系统的模块化分布式模型预测控制

• 批准号: 310613429
• 负责人: Professor Dr. Knut Graichen
• 金额: --
• 依托单位: Lehrstuhl für Regelungstechnik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2016
• 资助国家: 德国
• 起止时间: 2015-12-31 至 2018-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/310613429?language=en
• 关键词: Modular; distributed; model; predictive; control; Modular; distributed; model; predictive; control

The steadily growing demands on efficiency and flexibility of modern automation and control systems requires a broader design approach for the overall system that goes beyond the isolated look at and control of single subsystems. Decentral and distributed control schemes follow this holistic design approach by including the interdependencies between the subsystems in the control design.Model predictive control (MPC) appears to be a suitable control approach to tackle these kind of systems. In essence, MPC relies on the numerical solution of a finite-horizon dynamic optimization problem that is repetitively solved according to the sampling rate of the system. An extension of MPC to coupled systems is distributed MPC (DMPC), which assigns a single communicating MPC agent to each subsystem. The goal of the proposed project is to develop a DMPC scheme for nonlinear coupled systems, where each MPC agent contains a neighborhood model that anticipates the dynamical behavior of its neighbors in order to enhance the convergence and robustness of the distributed algorithm. Besides the development and mathematical investigation of the methodology, a further goal of the project is the numerical and experimental realization of the control approach. A particular intention of the project is to develop a modular framework that allows for an easy configuration and adaptation of the couplingstructure for suitable system classes. To achieve these mathematical, numerical and experimental goals, the proposed work programme buildsupon own preliminary work that is detailled in the proposal.

对现代自动化和控制系统的效率和灵活性的稳步增长的需求需要为整体系统采用更广泛的设计方法，这超出了单个子系统的孤立观察和控制。分散和分布式控制方案遵循这种整体设计方法，包括控制设计中的子系统之间的相互依存关系。模型预测性控制（MPC）似乎是解决此类系统的合适控制方法。从本质上讲，MPC依赖于根据系统的采样率重复求解的有限 - 摩恩动力学优化问题的数值解。 MPC向耦合系统的扩展是分布式MPC（DMPC），该MPC（DMPC）将单个通信MPC代理分配给每个子系统。拟议项目的目的是为非线性耦合系统开发DMPC方案，在该系统中，每个MPC代理都包含一个邻里模型，该模型可以预测其邻居的动态行为，以增强分布式算法的收敛性和稳健性。除了对该方法的发展和数学研究外，该项目的进一步目标是控制方法的数值和实验实现。该项目的一个特殊意图是开发一个模块化框架，该框架允许对合适的系统类的耦合结构进行简单的配置和改编。为了实现这些数学，数字和实验目标，提议的工作计划构建了自己的初步工作，这些工作在提案中被确定。