CAREER: System Design Under Risk Constraints

职业：风险约束下的系统设计

• 批准号: 9984260
• 负责人: Constantino Lagoa
• 金额: $ 20万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-04-01 至 2005-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9984260&HistoricalAwards=false
• 关键词: CAREER; System; Design; Under; Risk

9984260LagoaThe research objective of this proposal is to provide a comprehensive framework for system design under risk constrains in the presence of parametric uncertainty. The PI aims at developing efficient design procedures for both the case when the distribution of the uncertain parameters is known and for the case when the distribution is not available. Recent results in the emergent area of Probabilistic Robustness provide the main motivation for the proposed research since they provide a framework for risk assessment even if the distribution of the uncertain parameters is not known, only some of its characteristics are available.One question that one might ask is: Why consider risk constraints when designing a system? Although in many cases it is desirable to satisfy the performance specifications for every possible value of the admissible uncertainties, there are cases in which one is willing to have a tradeoff between a small risk of violation of the specifications and complexity of the system. Also, there are several problems that naturally lead to a formulation involving risk specifications. One example relates to emergency system handling. In this case, one is willing to tolerate some risk of failure of the system in exchange for an improvement on the performance and, therefore, a better chance of handling the emergency at hand. Hence, it would be desirable to be able to design a control system that maximizes the performance under a small well defined risk of system failure. Results to date on system design under risk constraints are limited. They use random search to determine the system gains and only address the case where the distribution of the uncertain parameters is available. The research proposed aims at developing efficient deterministic procedures for system design under risk specifications when the distribution of the uncertain parameters is available and when only some of its characteristics are known.The education plan described in this proposal includes curriculum development of both undergraduate and graduate courses. The objective is to interconnect the Principal Investigator current research with the content of the courses and to "bring" the students closer to the latest developments in control science. As for undergraduate education, the emphasis will be put in the improvement of the content of senior courses in control, introducing concepts which are not usually covered in undergraduate courses such as system uncertainty. This will also include the development of laboratory experiments which will provide the students with a hands-on experience in system design. The PI also plans on developing two graduate courses. The first, whose preliminary title is "Discrete-Time Stochastic Systems", is a course whose emphasis will be in the analysis and controller design for discrete stochastic systems. This course will be designed as a multidisciplinary course, aimed not only at students in control but also at students in other areas, namely at those in the communications area. The second course will be dedicated to the study of the latest developments in multivariable control. This course is to be developed in collaboration with the Mechanical Engineering Department.***

9984260Lagoa 该提案的研究目标是在参数不确定性存在的情况下，为风险约束下的系统设计提供一个全面的框架。 PI 旨在针对不确定参数分布已知的情况和分布不可用的情况开发有效的设计程序。 概率鲁棒性这一新兴领域的最新成果为拟议的研究提供了主要动机，因为它们提供了风险评估的框架，即使不确定参数的分布未知，只有其一些特征可用。人们可能会问的一个问题是：为什么在设计系统时考虑风险约束？ 尽管在许多情况下希望满足可容许不确定性的每个可能值的性能规范，但在某些情况下，人们愿意在违反规范的小风险和系统的复杂性之间进行权衡。 此外，还有几个问题自然会导致涉及风险规范的制定。 一个例子涉及紧急系统处理。 在这种情况下，人们愿意容忍系统出现故障的一些风险，以换取性能的改进，从而有更好的机会处理手头的紧急情况。 因此，希望能够设计一种在系统故障风险较小且明确的情况下最大化性能的控制系统。 迄今为止，在风险约束下的系统设计结果有限。 他们使用随机搜索来确定系统增益，并且仅解决不确定参数分布可用的情况。 所提出的研究旨在当不确定参数的分布可用且仅已知其一些特征时，在风险规范下开发有效的确定性程序。该提案中描述的教育计划包括本科生和研究生课程的课程开发。 目的是将首席研究员当前的研究与课程内容联系起来，并“让”学生更接近控制科学的最新发展。 在本科教育方面，重点是控制学高级课程内容的完善，引入系统不确定性等本科课程中通常没有涉及的概念。 这还包括实验室实验的开发，为学生提供系统设计的实践经验。 PI 还计划开发两门研究生课程。 第一门课程的初步标题是“离散时间随机系统”，该课程的重点是离散随机系统的分析和控制器设计。 本课程将被设计为多学科课程，不仅针对控制领域的学生，还针对其他领域的学生，即通信领域的学生。 第二门课程将致力于研究多变量控制的最新发展。 本课程将与机械工程系合作开发。***