Advances in Dynamic Inversion-based Flight Control Law Design

Abstract

Digital fly-by-wire (FBW) control technology has had - and continuous to make - a great impact on modern-day aviation. In particular, it enables stability and control augmentation of the dynamic characteristics of the bare airframe and brings opportunities for substantial automation of tasks related to flight. At the heart of FBW control technology are the control laws, which are embedded in a flight control computer. The so-called divide-and-conquer paradigm long prevailed in the development of flight control laws, which is based on trim-and-linearization of the nonlinear dynamics over a wide range of conditions over the flight envelope. This process enables the use of powerful Linear Time-Invariant (LTI) control design and synthesis tools. Gain scheduling is performed in the subsequent nonlinear implementation step. This is a critical task, for which different techniques can be used to arrive at successful designs. However, the process can be intensive and time-consuming, especially in the case of highly nonlinear aircraft.

Nonlinear Dynamic Inversion (NDI) was developed as an alternative to the divide-and-conquer strategy. Instead of subdividing the operating domain into many different local regions, NDI brings the notional benefit of automatic gain scheduling. This drastically simplifies the nonlinear implementation step. Moreover, as it enables a decoupling of different parts of the control design, NDI brings advantages in terms of design modularity. In its classical form, these aspects are achieved through the use of an on-board model embedded in the control law. Alternatively, in an effort to reduce this model-dependency, a sensor-based incremental variant of NDI (INDI) was proposed in the past. This form aims to increase control law robustness in the face of parametric modeling offsets by relying more directly on sensor measurements instead. Accordingly, different inversion strategies (model-based, sensor-based, or combinations of these) lead to vastly different robust stability and performance characteristics. However, a systematic understanding of these robustness implications has long been missing. In this thesis, this problem is approached using H_∞-based multivariable analysis and synthesis techniques.

In addition to the question of robustness, this thesis also focuses on multi-objective control design in the context of control allocation for input-redundant plants. This concerns over-determined control problems, for which secondary performance criteria can be addressed in addition to the primary motion control task. In particular, it is investigated how the framework of incremental control allocation (INCA) can be used in such multi-objective design scenarios.