CAREER: Control Design of Complex Engineering Systems

ECS-9875244 Dullerud复杂性越来越成为高性能工程系统设计中的一个主要和核心问题。 工程中大多数系统的巨大复杂性部分是由于长期公认的事实，即使是相对简单的物理系统也可以表现出非常复杂和微妙的行为，但更直接的原因是由于许多异构子系统相互连接而导致的系统增长。 在物理组件和计算能力快速发展的推动下，这一增长趋势似乎正在加速。 随着系统变得越来越复杂，对系统性能水平的期望也越来越高。 这对复杂系统工程提出了核心设计挑战，因为此类系统的行为本质上是不确定的。 除了处理复杂动态系统的更复杂和微妙的非线性行为外，当前和未来工程的控制和系统方法必须应对不完整或不确定的模型和信息问题。 PI研究计划的长期目标是开发直接适用于非线性复杂系统的先进控制和动态分析方法。 该提案的研究计划描述了PI将在这一方向上采取的一些创新和实质性步骤，以及研究生和本科生教育的综合计划。 该计划的主要研究贡献将在三个主要领域，第一个领域是构建复杂非线性系统沿着轨迹控制的分析和综合工具，以及更一般的非线性控制方法。 第二个领域是从实验获得的数据中验证不确定的非线性模型;这很重要，因为复杂系统的精确第一原理建模是不可能的，因此与数据的直接比较至关重要。 最后一个领域是专门的控制策略，需要为“系统组成的系统”的调查，并可以利用更普遍的新的驱动技术的外观，特别是分布式控制方法将被追求。 这里提出的计划强调新的理论和分析方法的发展，但是计算算法的创建和通用可重用软件的完成是该计划的主要目标;这将使该计划的想法和工具立即提供给从业者和行业。 该计划将使用非线性，鲁棒性和数值工具的组合。 半定规划将形成程序中大部分优化工作的基础，而对特定领域优化的直接贡献被认为是程序的次要目标。 为了补充所提出的计划，计划的实验设施表现出复杂的行为将被用来严格评估和部分指导这个分析program.The研究计划是在动力系统和控制理论，控制应用，数值模拟和优化的汇合。 研究生和本科教育都集成在研究计划中;参与该计划的学生将获得相当多的研究经验，使他们的工程背景更广泛，研究能力更强。 该教育计划具体包括通过各种特别选择的项目，包括优化工具，基于网络的教育软件和实验建设项目，让本科生参与研究

ECS-9875244DullerudComplexity is increasingly a major and central issue in the design of high performance engineering systems. The enormous complexity of most systems in engineering is partially due to the long recognized fact that even relatively simple physical systems can exhibit very complex and subtle behavior, but is more directly attributable to the growth of systems by interconnecting many heterogeneous subsystems. This growing trend, fueled by the rapid development of physical components and computing capability, seems to be accelerating. While systems are becoming more and more complex, expectations on the level of system performance are increasing. This poses a central design challenge for complex systems engineering as the behavior of such systems are inherently uncertain. In addition to dealing with the more complicated and subtle nonlinear behavior of complex dynamical systems, control and systems methods for current and future engineering must necessarily contend with the issues of incomplete or uncertain models and information. At the same time they must be computationally tractable.The long term objective of the PI's research program is the development of advanced control and dynamical analysis methods that are directly applicable to nonlinear complex systems. The research plan of this proposal describes some innovative and substantial steps that the PI will take in this direction, together with an integrated program for both graduate and undergraduate education. The major research contributions of the proposed program will be in three main areas, The first area is construction of analysis and synthesis tools for the control of complex nonlinear systems along trajectories, and more general nonlinear control approaches. The second area is the verification of uncertain nonlinear models from experimentally obtained data; this is important because exact first principles modeling of complex systems is not possible, and so direct comparison with data is crucial. The final area is the investigation of specialized control strategies that are required for "systems comprised of systems" and can be exploited more generally with the appearance of new actuation technology; specifically distributed control methods will be pursued. The program proposed here emphasizes new theory and the development of analytical methods, however the creation of computational algorithms and the completion of general reuseable software are major objectives of the program; this will make the ideas and tools of the program immediately available to practitioners and industry. The program will use a combination of nonlinear, robust and numerical tools. Semi-definite programming will form a basis for much of the optimization work in the program, and direct contributions to domain specific optimization is considered a secondary aim of the program. To complement the proposed program, planned experimental facilities exhibiting complex behavior will be used to critically evaluate and partially direct this analytical program.The research program is at the confluence of dynamical systems and control theory, control applications, and numerical simulation and optimization. Both graduate and undergraduate education are integrated in the research program; students involved with the program will gain considerable research experience, making their engineering background broader and their research capabilities stronger. The education plan specifically includes the involvement of undergraduates in research through a variety of specially selected projects, including optimization tools, web-based education software, and experiment construction projects