网络控制系统及其在智能卫星上的应用:概览

Alex McCafferty-Leroux, Yuandi Wu, S. A. Gadsden
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摘要

过去几十年来,地球观测卫星研究的发展已证明其富有成效且日益重要。在气候监测、通信、全球定位系统、国防和空间研究等应用领域,我们对可靠卫星系统的依赖与日俱增。卫星在这些应用场景中取得成功的根本原因在于其姿态确定系统,该系统由控制和估计子系统组成,控制着卫星的传感器和执行器。对于简单的任务,姿态姿态确定可在卫星上进行计算。但通常情况下,地面站或其他卫星(即星座)会参与卫星运行,处理大量数据或复杂的控制算法。这种信息和控制循环是通过应用网络控制系统(NCS)实现的。NCS 使用无线网络或通信系统作为设备、执行器、传感器和其他系统之间的中间通信线路。这样就能实现相对快速的长距离通信和数据传输,并通过系统分布实现导航和控制的分散化。然而,这种方法容易受到各种形式的时间延迟和数据包丢失的影响,最终影响卫星的控制性能。文献表明,通过在卫星框架中实施各种智能系统,可以减轻这些非接触式系统特性的影响,提高其可行性。利用神经网络和强化学习等技术,卫星可以根据环境信息进行感知和行动,同时考虑经验记忆和注意力分配。下面的综合调查从智能系统的角度讨论了提高网络卫星系统鲁棒性的方法,为这些概念提供了先进的基础。
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Networked control systems and their applications to smart satellites: a survey
The advancement of Earth observation satellite research in past decades has demonstrated itself to be productive and increasingly important. Utilized for applications such as climate monitoring, communication, GPS, defense, and space research, our dependence on reliable satellite systems is ever-increasing. The success of satellites in these scenarios is fundamentally the result of its attitude determination system, consisting of control and estimation subsystems, which govern its sensors and actuators. For simple missions, attitude pose determination can be computed onboard the satellite. Typically, however, ground stations or other satellites (i.e. constellations) are involved in a satellite’s operation, processing large amounts of data or complex control algorithms. This information and control cycle is enabled through the application of Networked Control Systems (NCS). The NCS uses a wireless network or communication system as the intermediate line of communication between plant, actuators, sensors, and other systems. This enables relatively fast communication and data transmittance over long distances, as well as the decentralization of navigation and control through system distribution. However, this method is vulnerable to various forms of time delay and packet loss, which ultimately affects the control performance of a satellite. It is demonstrated in literature that the effects of these NCS properties can be mitigated, increasing its viability, through various implementations of smart systems into the satellite framework. Using techniques such as neural networks and reinforcement learning, the satellite can perceive and act based on environmental information, while considering experiential memory and attention allocation. The following comprehensive survey discusses methods for improving the robustness of networked satellite systems from a smart systems perspective, providing an advanced foundation for these concepts.
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