Robust adaptive control: from theory to practical applications to aerospace systems

拟议研究计划的总体目标是开发一种新的方法，用于设计具有自适应能力的健壮的定期飞行控制系统，以及出席验证程序。**电子飞行控制系统(EFCS)的开发、集成和许可是繁琐、昂贵和耗时的过程。除了与稳定性、精确度和瞬变特性相关的标准要求外，EFCS还必须满足由飞行和操纵质量组成的严格规格，以反映飞机的易飞性。此外，EFCS必须对外部干扰(例如风、阵风)、变化的参数(例如质量、惯性、重心位置)以及潜在的数学模型不确定性和部分故障具有健壮性。**飞机的动态行为在其飞行区域内变化很大，单一的线性时不变控制器不能确保在整个飞行包线上的鲁棒性能。几十年来，工程师们一直求助于增益--调度技术来设计飞行控制器。传统上，增益调度包括在飞行包线的网格上设计线性控制器；因此，控制器增益根据代表飞行条件的调度变量(例如，高度、马赫数、空速)来更新。控制器的增益存储在查找表中，并使用多线性插值法计算每个工作点的增益。这种方法提供了有效的解决方案，但这是一个繁琐的迭代过程，涉及许多试验和错误循环。此外，所设计的控制器很少是最优的或鲁棒的。**本研究计划的主要目标是基于新的理论方法开发可靠的实用工具，以促进和改进航空航天系统的控制器设计。我们将重点关注以下三个主要挑战：**1.第一个挑战在于合成能够轻松调度到整个操作域的固定结构控制器，以及能够从整体上解决这一问题的控制方法。为此，我们的第一个目标是利用到目前为止在鲁棒控制中尚未开发的强大的理论结果，例如守护映射来开发程序，以产生关于操作域的鲁棒调度控制器。**2.第二个挑战涉及调度控制器的全局稳定性评估。事实上，由于控制器综合通常是在有限数量的工作点上执行的，所以不能保证每隔一个点的稳定性。因此，第二个目标建议开发和使用基于监护地图的新工具来评估整个操作领域的性能和稳健性。**3.最后，第三个挑战在于如何在遇到不确定性或系统故障的情况下恢复性能。对航空航天系统自适应方法的重新关注提供了新的工具，这些工具可以有利地用于增强基线控制器。为此，第三个目标是用自适应回路来增强鲁棒基线调度控制器。**这些新开发的方法和随后的工具将通过降低飞行控制系统的开发成本和节省开发时间而极大地有利于航空航天工业。

The overall goal of the proposed research program is to develop a novel methodology for the design of robust scheduled flight control systems with adaptation capabilities, as well as the attending validation procedures. **The development, integration and clearance of electrical flight control systems (EFCS) are tedious, costly and time--consuming processes. In addition to standard requirements related to stability, accuracy and transient behaviour, the EFCS must meet stringent specifications composed of flying and handling qualities that reflect the ease to fly the plane. Moreover the EFCS have to be robust to external disturbances (e.g. wind, gust), varying parameters (e.g. mass, inertia, centre of gravity location), and to underlying mathematical model uncertainties and partial failures. **The dynamic behaviour of an aircraft varies greatly within its flight domain and one single linear time--invariant controller cannot ensure robust performances over the whole flight envelope. For several decades, engineers have resorted to gain--scheduling techniques to design flight controllers. Traditionally, gain-scheduling consists in designing linear controllers over a gridding of the flight envelope; controller gains are thus updated according to scheduling variables that are representative of the flight condition (e.g. altitude, Mach number, airspeed). The controller gains are stored in look--up tables and multilinear interpolation is used to compute the gains at every operating point. This approach provides working solutions but is a cumbersome iterative process that involves many trials and errors loops. Moreover, the designed controllers are seldom optimal or robust.**The main objective of this research program is to develop solid practical tools based on novel theoretical approaches that will facilitate and improve controller design for aerospace systems. We will focus on the three following major challenges:**1. The first challenge lies in the synthesis of fixed-structured controllers that can be easily scheduled to cover the entire operating domain, as well as control methods that can solve this problem as a whole. To this end, our first objective is to capitalize on hitherto unexploited powerful theoretical results in robust control such as the guardian maps to develop procedures that yield robust scheduled controllers with respect to the operating domain.**2. The second challenge concerns the global stability assessment of the scheduled controller. Indeed, as the controller synthesis is usually performed on a finite number of operating points, the stability at every other point is not guaranteed. Therefore, the second objective proposes to develop and to use novel tools based upon guardian maps to assess performances and robustness over the whole operating domain. **3. Finally, the third challenge consists in recovering performance versus encountered uncertainties or system failures. The renewed interest in adaptive methods for aerospace systems provides new tools that can be advantageously used to enhance baseline controllers. To this end, the third objective aims at augmenting the robust baseline scheduled controller with an adaptive loop. **These newly developed methods and subsequently tools will greatly benefit the aerospace industry by reducing development costs and saving development time of flight control systems.