SBIR Phase I: MatLab Based Toolbox for Promoting Engineering Education of L1 Adaptive Control Theory

SBIR 第一阶段：基于 MatLab 的工具箱，促进 L1 自适应控制理论的工程教育

• 批准号: 1113365
• 负责人: David Carroll
• 金额: $ 15万
• 依托单位: CU Aerospace, LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-01 至 2012-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1113365&HistoricalAwards=false
• 关键词: SBIR; Phase; MatLab; Based; Toolbox

This Small Business Innovation Research (SBIR) Phase I project will develop a MATLAB based toolbox that can be used in educational laboratory environments for the training of the next generation of engineers with modern adaptive control theory, and will be performed by CU Aerospace (CUA) and team partner the University of Illinois at Urbana-Champaign (UIUC). The existing MATLAB toolboxes for control system design that use the dated theoretical advances from 1980?s and 90?s are suitable for applications in linear systems. However, the existing toolboxes cannot effectively serve the purpose of control design for complex systems in the presence of uncertainties. The key feature of this breakthrough L1 adaptive control theory is the separation between identification and control. It leads to decoupling of adaptation from robustness and ensures uniform and predictable response in the presence of unpredictable failures and disturbances. The CUA-UIUC team will build a commercial toolbox that captures the recent advances in control theory having routines for implementation of L1 adaptive controllers, and apply the new toolbox in laboratory classroom environments to train our future generation of scientist-engineers.The broader impact/commercial potential of this project is that the development of the L1 Adaptive Control Toolbox will serve as the ideal tool to transition this modern control theory to a much wider technical audience both through continuing education of practicing professionals and engineering students. Within a very short time span, the architectures of this powerful theory for robust adaptive control of complex systems has supported a large number of very challenging and ambitious experiments including: (i) flight tests of a subscale commercial jet (GTM-AirSTAR) at NASA, including post-stall flight regimes; (ii) control of nuclear plants; (iii) coordination of multiple unmanned autonomous vehicles in time-critical missions within given spatial constraints using vision-based sensors; (iv) pressure control in drilling applications of oil production; control of fiber optics; (v) networked control systems in the presence of various failures; (vi) control of anesthesia; (vii) iterative learning control in the presence of unpredictable disturbances; (viii) aerobiological sampling; control of smart materials in the presence of hysterisis; (ix) aerial refueling of multiple UAVs in turbulence; (x) control of flexible aircraft; and (xi) control of rotorcraft. The development of this toolbox into a commercial product will serve as a springboard for CUA to develop systematic design methods for broader applications of this theory to industry and many governmental departments including DOE, DOD, DOT, and NASA.

该小型企业创新研究 (SBIR) 第一阶段项目将开发一个基于 MATLAB 的工具箱，可在教育实验室环境中使用，以利用现代自适应控制理论培训下一代工程师，该项目将由 CU Aerospace (CUA) 执行和团队合作伙伴是伊利诺伊大学厄巴纳-香槟分校 (UIUC)。 现有的用于控制系统设计的 MATLAB 工具箱采用了 20 世纪 80 年代和 90 年代过时的理论进展，适用于线性系统中的应用。 然而，现有的工具箱无法有效地满足存在不确定性的复杂系统的控制设计目的。 这一突破性的L1自适应控制理论的关键特征是识别与控制的分离。 它使适应性与鲁棒性脱钩，并确保在出现不可预测的故障和干扰时提供一致且可预测的响应。 CUA-UIUC 团队将构建一个商业工具箱，捕捉控制理论的最新进展，并具有用于实现 L1 自适应控制器的例程，并将新工具箱应用于实验室课堂环境中，以培训我们下一代的科学家工程师。更广泛的影响/该项目的商业潜力在于，L1 自适应控制工具箱的开发将作为理想的工具，通过对执业专业人员和工程专业学生的继续教育，将这种现代控制理论转移给更广泛的技术受众。 在很短的时间内，这种复杂系统鲁棒自适应控制的强大理论架构已经支持了大量极具挑战性和雄心勃勃的实验，包括：(i) NASA 小型商用喷气式飞机 (GTM-AirSTAR) 的飞行测试，包括失速后飞行制度； ㈡ 核电厂的控制； (iii) 使用基于视觉的传感器在给定空间限制内协调多辆无人驾驶车辆执行时间紧迫的任务； (iv) 石油生产钻井应用中的压力控制；光纤控制； (v) 出现各种故障时的联网控制系统； (vi) 麻醉控制； (vii) 存在不可预测的干扰时的迭代学习控制； (viii) 空气生物采样；在存在迟滞的情况下控制智能材料； (ix) 多架无人机在湍流中进行空中加油； (x) 灵活航空器的控制； (xi) 旋翼机的控制。将该工具箱开发成商业产品将成为 CUA 开发系统设计方法的跳板，以便将该理论更广泛地应用于工业界和许多政府部门，包括 DOE、DOD、DOT 和 NASA。