首页> 外文期刊>Journal of Mechanisms and Robotics: Transactions of the ASME >Improving Prediction of Flapping-Wing Motion By Incorporating Actuator Constraints With Models of Aerodynamic Loads Using In-Flight Data
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Improving Prediction of Flapping-Wing Motion By Incorporating Actuator Constraints With Models of Aerodynamic Loads Using In-Flight Data

机译:通过使用飞行数据将致动器约束加入致动器限制来改善拍打翼运动的预测

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Flapping-wing flight is a challenging system integration problem for designers due to tight coupling between propulsion and flexible wing subsystems with variable kinematics. High fidelity models that capture all the subsystem interactions are computationally expensive and too complex for design space exploration and optimization studies. A combination of simplified modeling and validation with experimental data offers a more tractable approach to system design and integration, which maintains acceptable accuracy. However, experimental data on flapping-wing aerial vehicles which are collected in a static laboratory test or a wind tunnel test are limited because of the rigid mounting of the vehicle, which alters the natural body response to flapping forces generated. In this study, a flapping-wing aerial vehicle is instrumented to provide in-flight data collection that is unhindered by rigid mounting strategies. The sensor suite includes measurements of attitude, heading, altitude, airspeed, position, wing angle, and voltage and current supplied to the drive motors. This in-flight data are used to setup a modified strip theory aerodynamic model with physically realistic flight conditions. A coupled model that predicts wing motions is then constructed by combining the aerodynamic model with a model of flexible wing twist dynamics and enforcing motor torque and speed bandwidth constraints. Finally, the results of experimental testing are compared to the coupled modeling framework to establish the effectiveness of the proposed approach for improving predictive accuracy by reducing errors in wing motion specification.
机译:扑振翼飞行是由于推进与可变运动学的柔性翼子系统之间的紧密耦合,是设计人员的具有挑战性的系统集成问题。捕获所有子系统交互的高保真模型是计算昂贵的,对于设计空间探索和优化研究来说太复杂了。简化建模和验证与实验数据的组合提供了更具易易触手的系统设计和集成方法,这保持了可接受的准确性。然而,由于车辆的刚性安装,在静态实验室试验或风洞测试中收集的扑翼飞行器或风隧道试验的实验数据受到限制,这改变了对产生的拍打力的自然身体响应。在这项研究中,透翼飞行器被仪表被仪表以提供飞行的数据收集,这些数据收集通过刚性安装策略无阻碍。传感器套件包括姿态,标题,高度,空速,位置,机翼角度和电压和电流提供给驱动电机的电压。这种飞行中的数据用于设置具有物理现实的飞行条件的改进的条带理论空气动力学模型。然后通过将空气动力学模型与柔性翼扭转动力学模型组合来构造预测翼运动的耦合模型,并强制执行电动机扭矩和速度带宽约束。最后,将实验测试的结果与耦合的建模框架进行比较,以确定通过减少翼运动规范中的误差来提高预测准确性的提高方法的有效性。

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