The standard approach of controlling in-orbit large flexible structures only by adopting actuators and sensors located at platform level is currently being challenged by new missions’ stringent requirements in terms of demanding guidance profiles and instrument performance. In this perspective, smart materials offer a different solution to improve the performance of space systems by controlling the vibrations of such lightweight structures. In this paper, the problem of designing an end-to-end architecture for active control of large in-orbit structures is addressed. First, a FE model of a large space antenna is derived by using commercial software. The instrument is designed to be supported by an active deployable frame hosting an optimal minimum set of collocated smart actuators and sensors. To this purpose, a comparison among different placement techniques, as Gramian and Modal Strain Energy (MSE) based methods, is proposed to find the final configuration for both actuators and sensors. Attention is paid to create a GNC strategy combining collocated control on flexible appendages with platform control, while minimizing the relative displacements among the most critical points of the antenna. To achieve high performance, Linear Fractional Transformation (LFT) modelling and advanced multivariable techniques are implemented. Finally, to validate the proposed controller, the control system is tested by simulating typical spacecraft manoeuvre profiles.

仅通过采用位于平台级别的执行器和传感器来控制在轨大型柔性结构的标准方法目前正受到新任务在苛刻的制导剖面和仪器性能方面的严格要求的挑战。从这个角度来看，智能材料提供了一种不同的解决方案，通过控制这种轻型结构的振动来提高空间系统的性能。在本文中，解决了设计用于主动控制大型在轨结构的端到端架构的问题。首先，利用商业软件推导出大空间天线的有限元模型。该仪器设计为由一个主动可部署框架支持，该框架承载一组最佳的最小并置智能执行器和传感器。为此，建议比较不同的放置技术，如基于 Gramian 和模态应变能 (MSE) 的方法，以找到执行器和传感器的最终配置。注意创建将柔性附件的并置控制与平台控制相结合的 GNC 策略，同时最小化天线最关键点之间的相对位移。为了实现高性能，实施了线性分数变换 (LFT) 建模和高级多变量技术。最后，为了验证所提出的控制器，通过模拟典型的航天器机动剖面来测试控制系统。注意创建将柔性附件的并置控制与平台控制相结合的 GNC 策略，同时最小化天线最关键点之间的相对位移。为了实现高性能，实施了线性分数变换 (LFT) 建模和高级多变量技术。最后，为了验证所提出的控制器，通过模拟典型的航天器机动剖面来测试控制系统。注意创建将柔性附件的并置控制与平台控制相结合的 GNC 策略，同时最大限度地减少天线最关键点之间的相对位移。为了实现高性能，实施了线性分数变换 (LFT) 建模和高级多变量技术。最后，为了验证所提出的控制器，通过模拟典型的航天器机动剖面来测试控制系统。