PECASE: Robust Intelligent Control, Demonstrated for Reconfigurable Flight Systems

PECASE：稳健的智能控制，针对可重新配置的飞行系统进行了演示

• 批准号: 0448906
• 负责人: Silvia Ferrari
• 金额: $ 40万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-06-01 至 2012-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0448906&HistoricalAwards=false
• 关键词: PECASE; Robust; Intelligent; Control; Demonstrated

Recent advances in a variety of technologies and applications call for improved performance andreliability, while exacerbating the complexity and uncertainty of systems and their surroundings.Although classical control theory already allows for a high degree of machine automation, arenewed interest in systems that display intelligent behavior is emerging across disciplines. Theproposed research will develop a novel adaptive control approach that approximates the nonlinearcontrol law by a sigmoidal neural network, and optimizes its performance on line, subject toactual plant dynamics. By combining approximate dynamic programming and integral quadraticconstraints, it can be shown that the neural network controller is characterized by the sameclosed-loop stability and robustness guarantees as classical H-infinity controllers. Ensuring thatthese properties are preserved during adaptation will make the adaptive design viable forapplications where safety is a leading concern, such as, reconfigurable aircraft control.As part of the proposed research, the adaptive control approach will be demonstrated not onlythrough numerical simulations, but also through experiments. The first testbed will consist of acantilevered beam with piezoelectric devices used as disturbance and control sources. In theexperiments, the effectiveness of the adaptive controller for reducing the vibration of the first twonatural modes will be tested and compared to that of controllers with parameters held fixed.After considering this low-dimensional system, the approach will be implemented to design anadaptive flight controller based on the model of an experimental fly-by-wire Raytheon Bonanzaaircraft. The flight controller will be tested on a piloted simulator developed by an experiencedresearch group at Wichita State University (WSU). Subsequently, the PI will work with the WSUgroup and Raytheon Aircraft Company on interfacing the control software with the on-boardflight computer, and on testing it on the Bonanza through a set of experimental flights.Research and education on control theory and practice will be integrated by designing a set ofexperiments for undergraduate and TIP high-school students that employ the following testbeds: avibrating cantilevered beam, an acoustic enclosure, and a flapping micro-aerial vehicle. Thebroader impact of this project is the creation of initiatives that expose students from K12 throughgraduate school to advanced control research and experiments being conducted in the aerospaceindustry and at NASA. By leading undergraduates and TIP students through these experiments,the PI's graduate students will become important role models for a diverse and gifted group ofyoungsters.

近年来，各种技术和应用的进步要求提高系统的性能和可靠性，但同时也加剧了系统及其周围环境的复杂性和不确定性。尽管经典控制理论已经允许高度的机器自动化，但对显示智能行为的系统的新兴趣正在跨学科出现。本研究将发展一种新的适应性控制方法，借由S型类神经网路来逼近非线性控制律，并根据实际的对象动态特性，来在线优化其性能。通过结合近似动态规划和积分二次型约束，可以证明神经网络控制器具有与经典H ∞控制器相同的闭环稳定性和鲁棒性保证。确保这些属性在适应过程中得到保留将使自适应设计在安全性是主要关注点的应用中变得可行，例如可重构飞机控制。作为拟议研究的一部分，自适应控制方法不仅将通过数值模拟，而且还将通过实验来证明。第一个试验台将包括悬臂梁与压电器件用作干扰和控制源。在实验中，自适应控制器的有效性，以减少前两个自然模式的振动将被测试和控制器的参数保持固定的比较，考虑这个低维系统后，该方法将被实施，以设计一个自适应飞行控制器的实验模型的基础上，电传雷声Bonanza飞机。飞行控制器将在威奇托州立大学（WSU）的一个经验丰富的研究小组开发的有人驾驶模拟器上进行测试。随后，PI将与WSU集团和雷神飞机公司合作，将控制软件与机载飞行计算机连接起来，并通过一系列实验飞行在Bonanza上对其进行测试。通过为本科生和TIP高中生设计一系列实验，将控制理论和实践的研究和教育结合起来，这些实验采用以下测试平台：飞行悬臂梁、声学外壳和扑翼微型飞行器。该项目的更广泛的影响是创造的倡议，使学生从K12通过研究生院先进的控制研究和实验正在进行的航空航天工业和美国宇航局。通过带领本科生和TIP学生完成这些实验，PI的研究生将成为一个多元化和有天赋的青少年群体的重要榜样。