反演(地质)
空气动力学
忠诚
非线性系统
控制工程
自适应控制
推进
计算机科学
高保真
航空航天工程
系统动力学
工程类
控制理论(社会学)
控制(管理)
人工智能
物理
电气工程
构造盆地
生物
古生物学
电信
量子力学
作者
J. Peter Harris,Christopher M. Elliott,Greg Tallant
摘要
View Video Presentation: https://doi.org/10.2514/6.2022-0791.vid Nonlinear dynamic inversion is a prominent method for control law design in modern tactical aircraft that is well-suited for providing excellent handling qualities over large flight envelopes. The dynamic inversion method requires a detailed and accurate on-board model of the aircraft aerodynamics, propulsion system, and mass properties to successfully "invert" the aircraft dynamics to achieve the desired response. This leads to an expensive, time-consuming model development effort that includes high-fidelity computational fluid dynamics, wind tunnel tests, and flight tests. Adaptive augmentation has long been proposed as a method to reduce the required model fidelity for successful dynamic inversion control laws, but to date this technology has rarely transitioned to operational systems. This paper presents Lockheed Martin efforts to develop an adaptive controller based on the L1 architecture to allow using dynamic inversion with low-fidelity, conceptual design-level aerodynamics models. The augmentation method is evaluated in a high-fidelity simulation environment against a tailless fighter aircraft representative of next-generation systems. Time domain results show that the adaptive dynamic inversion is able to successfully track desired dynamics when coupled with a low-fidelity on-board model and achieve improved performance over the non-adaptive baseline.
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