Intelligent Control of Complex Nonlinear Systems with Electric Power Application

电力应用复杂非线性系统的智能控制

• 批准号: 9301168
• 负责人: Ronald Mohler
• 金额: $ 21.16万
• 依托单位: Oregon State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-08-15 至 1997-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9301168&HistoricalAwards=false
• 关键词: Intelligent; Control; Complex; Nonlinear; Systems

9301168 Mohler This research is on "intelligent control systems" with electric power applications. Model-based nonlinear adaptive and optimal control methodologies are to be used. Linear, bilinear, and higher-order nonlinear approximations may be used. The potential role of artificial neural networks as a means to adapt to state space changes resulting from switching events or faults will be studied. Fast adaptation to structural changes of the system being controlled is a key objective of the research. The investigator proposes a hierarchial configuration in which an upper level consists of a statistical detector and an artificial neural network classifier. The combination would act to select the optimal control configuration to respond to changing power system conditions. ***

9301168 Mohler这项研究是关于电力应用的“智能控制系统”。 将使用基于模型的非线性自适应和最佳控制方法。 可以使用线性、双线性和高阶非线性近似。 人工神经网络作为一种手段，以适应状态空间的变化所造成的开关事件或故障的潜在作用将进行研究。 快速适应被控系统的结构变化是研究的一个关键目标。 研究者提出了一种层次结构，其中上层由一个统计检测器和一个人工神经网络分类器组成。 该组合将用于选择最优控制配置以响应变化的电力系统条件。 ***