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Research Initiation Award: Synthesis of Practically Implementable Robust Controllers

Research Initiation Award: Synthesis of Practically Implementable Robust Controllers
研究启动奖:实用鲁棒控制器的综合
批准号:
9309123
负责人:
Bassam Bamieh
金额:
$9.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1993
资助国家:
美国
项目状态:
已结题
起止时间:
1993-09-01 至 1997-02-28

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中文摘要
翻译
鲁棒控制器的设计在过去的十年中取得了显着进展,导致复杂的设计理论和算法,在存在不确定性的情况下产生高性能的控制器,并使设计者能够探测控制系统配置的性能的基本限制。 然而,理论设计问题忽略了一些重要的实现问题和约束,因此鲁棒控制设计往往是目前用于调查的性能限制,而不是实际生产的控制器。 建议的研究是围绕着将一般的实施约束和要求的鲁棒控制器设计理论的想法。 一个例子是连续时间性能目标的采样数据控制器的设计,这是由于考虑到采样数据控制器。 具有实现约束的控制器设计在理论上具有挑战性,它们的解决将极大地提高鲁棒控制理论在控制实践中的适用性。 ***
英文摘要
9309123 Bamieh The design of robust controllers has progressed significantly in the past decade, resulting in sophisticated design theories and algorithms that produce high performance controllers in the presence of uncertainty, and enabling the designer to probe the fundamental limits of performance of control systems configurations. However, theoretical design problems ignore some important implementations issues and constraints, and thus robust control designs tend to be currently used for investigating limits of performance rather than actually producing the controllers. The proposed research is centered around the idea of incorporating general implementation constraints and requirements in the theory of robust controller design. An example is the design of sampled-data controllers with continuous-time performance objectives, which arise from the consideration that sampled-data controllers. Controller design with implementation constraints give rise to theoretically challenging problems, and their solution will greatly enhance the applicability of robust control theory to control practice. ***
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会议论文
Collaborative Research: Robust-by-Design Networked Dynamical Systems: Bridging the Logic/Analog Divide
Optimal Field Sensing Strategies for Time-Critical Estimation and Prediction of Dynamic Environments
Control of ThermoAcoustic Phenomena with Applications to Novel Energy Conversion Devices
Quantifying Complex Behavior in Large-Scale Systems through Structured Uncertainty Analysis
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