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.

这个小企业创新研究（SBIR）第一阶段项目将开发一个基于MATLAB的工具箱，可用于教育实验室环境中，用于培训具有现代自适应控制理论的下一代工程师，并将由CU Aerospace（CUA）和团队合作伙伴伊利诺伊大学香槟分校（UIUC）执行。 现有的MATLAB工具箱的控制系统设计，使用过时的理论进展，从1980年？s和90？S适用于线性系统中的应用。 然而，现有的工具箱不能有效地服务于存在不确定性的复杂系统的控制设计的目的。 这种突破性的L1自适应控制理论的关键特征是识别和控制之间的分离。 它导致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作出统一和可预测的反应。CUA-UIUC团队将构建一个商业工具箱，该工具箱将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，并在实验室教室环境中应用新的工具箱来培养我们未来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自适应控制器的开发将成为过渡这种现代控制的理想工具通过对实践专业人员和工程专业学生的继续教育，将理论传播给更广泛的技术受众。 在很短的时间内，这个强大的复杂系统鲁棒自适应控制理论的体系结构已经支持了大量非常具有挑战性和雄心勃勃的实验，包括：（i）缩尺商用喷气式飞机的飞行试验（ii）核电站的控制;（iii）使用基于视觉的传感器在给定的空间限制内协调多个无人驾驶自主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）存在各种故障时的网络控制系统;（vi）麻醉控制;（vii）存在不可预测干扰时的迭代学习控制;（viii）空气生物学采样;存在滞后时的智能材料控制;（ix）湍流中多个UAV的空中加油;（x）柔性飞机的控制;以及（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和许多政府部门，包括DOE，DOD，DOT和NASA。