Intelligent Control Strategies for Nonlinear Systems with Faults

非线性故障系统的智能控制策略

• 批准号: RGPIN-2017-04087
• 负责人: Gadsden, Stephen
• 金额: $ 1.97万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=651315
• 关键词: Intelligent; Control; Strategies; Nonlinear; Systems

In order to protect the public health and safety, there is substantial need for the reliable control and diagnosis of mechanical and electrical systems. This research program aims to develop intelligent controllers and strategies that can be used by a number of different engineering systems, including cars, planes, robots, and unmanned aerial systems, to name a few. A long-term research goal of this program is to provide techniques for a system to enable it to successfully predict the occurrence of faults and take appropriate control actions prior to the fault event. In other words, provide a system with some form of cognition. This offers a number of benefits to society (safety) as well as the economy (reduced maintenance costs, fewer catastrophic events, and less downtime). The proposed activities are important to the advancement of knowledge and understanding within the field. In addition, this work will have a positive impact in a number of industries, including: automotive, aerospace, defense, manufacturing, and space systems.*** My research group studies intelligent control and estimation methods. We seek to advance the use of machine learning (artificial neural networks) and Bayesian (probability-based) techniques on engineering control and estimation problems. Inherent to intelligence is the ability to remember the past (memory) and predict the future (estimation) based on a knowledge base (built through human training or system interactions) and the external environment (measurements and senses). Sometimes referred to as ‘cognitive', intelligent controllers are able to learn (adapt) over time and are able to predict and anticipate the future environment. Intelligent systems are important to protect the public health and safety. In addition to technical advancements, my research group trains highly-qualified personnel who help meet Canada's demand for engineers and will contribute to its economic success.

为了保护公众的健康和安全，对机电系统进行可靠的控制和诊断是非常必要的。这项研究计划旨在开发智能控制器和策略，可用于许多不同的工程系统，包括汽车、飞机、机器人和无人驾驶航空系统，仅举几例。该计划的一个长期研究目标是为系统提供技术，使其能够成功地预测故障的发生，并在故障事件之前采取适当的控制措施。换句话说，为系统提供某种形式的认知。这为社会(安全)和经济(降低维护成本、减少灾难性事件和减少停机时间)提供了许多好处。拟议的活动对于增进实地的知识和了解很重要。此外，这项工作将对许多行业产生积极影响，包括：汽车、航空航天、国防、制造和空间系统。*我的研究组研究智能控制和估计方法。我们寻求在工程控制和估计问题上推进机器学习(人工神经网络)和贝叶斯(基于概率)技术的使用。智力与生俱来的能力是记忆过去(记忆)和预测未来(估计)的能力，基于知识库(通过人类训练或系统交互建立)和外部环境(测量和感官)。智能控制器有时被称为“认知”，它能够随着时间的推移而学习(适应)，并能够预测和预期未来的环境。智能系统对保障公众健康和安全具有重要意义。除了技术进步，我的研究小组还培养高素质的人才，帮助满足加拿大对工程师的需求，并将为加拿大的经济成功做出贡献。