Identification of Nonlinear Systems

非线性系统的辨识

• 批准号: RGPIN-2015-06464
• 负责人: Westwick, David
• 金额: $ 1.82万
• 依托单位: University of Calgary
• 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=614169
• 关键词: Identification; Nonlinear; Systems

Automatic control systems are ubiquitous in the modern world. They can range in scale from the position controller that regulates the position of the read/write head in a hard disk, to the autopilots that control the movement of aircraft, to the advanced traffic control systems that regulate the flow of traffic in major cities. Since the controller is designed based on a mathematical model of the system that will be controlled, the system’s performance will be limited by the accuracy of the model used in its design. Thus, having an accurate mathematical model of the target system is a necessary pre-requisite to the design of a high-performance control system. While models of comparatively simple systems can be derived based on first principles, this approach quickly becomes intractable as the system’s scale and/or complexity increases. System identification, on the other hand, is a data-driven process that creates mathematical models of dynamic systems from measurements of their inputs and outputs. This research programme will develop system identification techniques that can create accurate mathematical models of nonlinear systems from data that have been gathered under normal operating conditions and when some form of control system is operating. The system identification process is greatly simplified if the input to the system is independent of any disturbances that affect the system, or of any noise that may be contained in the measurements. Unfortunately, many systems can only be operated in a “closed-loop” configuration, where the system output is measured, compared to a desired trajectory, and this error is then used to adjust the input signal. This type of feedback control may be necessary for safety, performance or economic reasons. The nonlinear system identification algorithms developed in this research programme will be designed to operate on data that have been gathered under closed-loop conditions, as this will allow them to be applied without the need for a separate, often impossible to perform, open-loop experiment. Instead, we will concentrate on constructing models from normal operating data, as this will minimize the economic impact of generating the model.

自动控制系统在现代世界中无处不在。它们的范围很广，从调节硬盘读写头位置的位置控制器，到控制飞机运动的自动驾驶仪，再到调节大城市交通流量的先进交通控制系统。由于控制器是根据被控制系统的数学模型设计的，因此系统的性能将受到其设计中使用的模型的准确性的限制。因此，拥有目标系统的精确数学模型是设计高性能控制系统的必要前提。