Integrated Actuator/Sensor Design for Control of Distributed Parameter Systems

用于分布式参数系统控制的集成执行器/传感器设计

• 批准号: RGPIN-2015-06053
• 负责人: Morris, Kirsten
• 金额: $ 2.19万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=613912
• 关键词: Integrated; Actuator; Sensor; Design; Control

The dynamics of many systems depend  not only on time, but also on the spatial distribution of the system. Examples include: fluid flow, transmission networks, structural vibrations, acoustic noise. These systems are known as distributed parameter systems (DPS) and models involve partial differential equations. This is different from lumped parameter systems, such as circuits, where the models are ordinary differential equations. This introduces a number of complexities into estimator and controller design. For  control and estimation of systems that vary in space, performance depends on the location of controller hardware, the sensors and actuators. The best locations may be different from those chosen based on physical intuition. Analysis is crucial, as it is often difficult to move hardware. For example, piezo-electric actuator/sensors are useful in structural control and estimation, but once placed, cannot be moved without damaging the structure. A mechatronic approach that  integrates controller/estimator design  with actuator/sensor location should be used. Sensor location in particular has many applications. These applications include sensor placement on structures, thermostat placement to improve building efficiency and sensor placement to study environmental changes in lakes. One question involves sensor selection: for a given budget, which choice yields better performance, a small number of quality sensors or a larger number of cheap sensors? What is the best control of moving sensors in order to obtain the best estimate of a contaminant location? Many sensors or actuators, particularly those composed of smart materials, can be produced in fairly arbitrary shapes. For a given application, and mass of material, what is the best shape for achieving estimation (or a control objective)? Results on sensor location will lead naturally to establishing a strategy for joint actuator/sensor location as part of an integrated approach to output feedback controller design.  Recent research by the principal investigator led to fundamental results on some actuator location problems and these results will be helpful in the proposed research. Advances in theory and computation are needed. Theory that includes the effect on system dynamics of sensors and actuators will be developed. An efficient algorithm that can be used for arbitrary spatial domains is critical. Integrated DPS controller design means that hardware location is integrated with controller/estimator development. Many processes are nonlinear. Examples include large vibrations, heating with phase change, smart-materials, charge estimation in lithium-ion batteries. Both theory for control and estimation of these systems, and methods that can be used for practical synthesis, are needed. Combined with results on actuator/sensor location this will lead to a integrated controller design strategy for DPS.

许多系统的动力学不仅取决于时间，还取决于系统的空间分布。例子包括：流体流动，传输网络，结构振动，声学噪声。这些系统被称为分布参数系统（DPS）和模型涉及偏微分方程。这不同于集中参数系统，例如电路，其中模型是常微分方程。这就给估计器和控制器的设计带来了许多复杂性。 对于空间变化的系统的控制和估计，性能取决于控制器硬件、传感器和执行器的位置。最佳位置可能与基于物理直觉选择的位置不同。分析至关重要，因为移动硬件通常很困难。例如，压电致动器/传感器在结构控制和估计中是有用的，但是一旦放置，就不能在不损坏结构的情况下移动。机电一体化的方法，集成控制器/估计器的设计与执行器/传感器的位置。传感器的位置，特别是有许多应用。这些应用包括在结构上放置传感器，放置恒温器以提高建筑效率，以及放置传感器以研究湖泊中的环境变化。其中一个问题涉及传感器的选择：对于给定的预算，哪种选择会产生更好的性能，是少量的优质传感器还是大量的廉价传感器？为了获得污染物位置的最佳估计，移动传感器的最佳控制是什么？ 许多传感器或致动器，特别是由智能材料组成的传感器或致动器，可以以相当任意的形状生产。对于给定的应用和材料质量，实现估计（或控制目标）的最佳形状是什么？ 传感器位置的结果自然会导致建立一个战略关节执行器/传感器的位置作为一个综合的方法来输出反馈控制器设计的一部分。 最近的主要研究者的研究导致了一些致动器的位置问题的基本结果，这些结果将有助于在拟议的研究。 需要在理论和计算方面取得进展。理论，包括传感器和执行器的系统动力学的影响将被开发。一个有效的算法，可用于任意空间域是至关重要的。集成DPS控制器设计意味着硬件定位与控制器/估计器开发集成在一起。 许多过程是非线性的。例子包括大振动，相变加热，智能材料，锂离子电池的电荷估计。这些系统的控制和估计理论，以及可用于实际合成的方法，都是需要的。结合执行器/传感器位置的结果，这将导致一个集成的控制器设计策略的DPS。