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Control Laws Development for a Free-Flying Unmanned Robotic System to Support Interplanetary Bodies Prospecting and Characterization Missions

机译:自由飞行的无人机器人系统的控制法则开发,以支持行星际探测和表征任务

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In situ Resource Utilization (ISRU) facilitates planetary exploration by drawing needed resources, such as water, from the local environment. However, the extreme nature of these environments require the development of advanced unmanned space systems integrated with sample-capture devices to achieve the ultimate goal of prospecting these resources. This paper presents the design, development and Hardware-in-the-Loop (HIL) simulation testing of guidance and tracking control laws for an autonomous small marsupial free-flyer prospector system. The control laws are based on an extended non-linear dynamic inversion (NLDI) approach and its implementation is illustrated through HIL simulation using a mathematical model of an autonomous vehicle research platform developed by NASA Kennedy Space Center. This vehicle has been designed to support the development, testing and validation of algorithms for safe, reliable, and scalable control space missions with minimal need for human intervention in complex, unstructured environments. The main objective of the control laws is to minimize 3-axis distances with respect to a desired trajectory and maintain stability and adequate performance in the presence of uncertainties. The performance of the control laws is evaluated during autonomous flight in terms of trajectory tracking errors, real-time execution on board the flight computer, and control activity at nominal and dynamically-changing conditions. The results show that for all mission cases investigated the control laws approach has desirable capabilities and is reliable for in-flight testing operation as a next step towards the validation and verification of this configuration.
机译:原位资源利用(ISRU)通过从当地环境中获取所需的资源(例如水)来促进行星勘探。但是,这些环境的极端性质要求开发与样本捕获设备集成在一起的先进的无人空间系统,以实现勘探这些资源的最终目标。本文介绍了自治的有袋小飞鸟探矿系统的制导和跟踪控制律的设计,开发和在环仿真(HIL)仿真测试。控制律基于扩展的非线性动态反演(NLDI)方法,并通过使用由NASA肯尼迪航天中心开发的自动驾驶汽车研究平台的数学模型进行的HIL仿真来说明其实现。该车辆的设计目的是支持在安全,可靠和可扩展的控制空间任务中开发,测试和验证算法,而在复杂的,非结构化的环境中,则无需人工干预。控制定律的主要目的是使相对于所需轨迹的3轴距离最小化,并在存在不确定性的情况下保持稳定性和足够的性能。在自主飞行期间,根据轨迹跟踪误差,在飞行计算机上的实时执行以及在名义上和动态变化的条件下的控制活动来评估控制律的性能。结果表明,对于所调查的所有任务案例,控制律方法均具有理想的功能,并且对于飞行中的测试操作而言是可靠的,这是迈向验证和验证此配置的下一步。

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