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1 Introduction
1.1 Scenario
In present days, aircraft crashes have human factor (HF) errors as their main cause. These errors occur in both civil and military aviation. Loss of manned aircraft to HF has caused more than 60 deaths and damages for 2 B$ in the USAF only in the past 20 years, while US Navy has suffered even greater expenses. This resulted in most of the developed countries to invest resources in FCS features able to prevent HF derived problems. [4]
Among military pilots, the most frequent HF problem is by far spatial disorientation (SD). Also known as vertigo, loss of spatial orientation is a critical condition for every kind of pilot. Most SD cases occur because of bad weather, extreme darkness, or fog. However, SD happens even under relatively normal conditions. When popular aviation site AVweb asked about SD in its Question of
the week, fighter pilot Gerry Humphreys answered:
“My worst SD incident […] happened in good vis[ibility] conditions but poor horizon. […] I was suddenly convinced that [a nearby aircraft] had entered a screaming death dive. Every bone in my body said I was going vertically down. […] It just goes to show that SD can happen in pretty benign conditions and can be very scary”.
To prevent SD related mishaps, Automatic Recovery Systems (ARS) were developed. An ARS is a feature of the FCS that, when certain conditions are met, takes control of the aircraft and commands straight and levelled flight. Depending on flight height, speed and mass configuration, the ARS may employ different recovery manoeuvres to achieve levelled flight. An ARS that activates at the pilot’s request is called a Pilot Activated Recovery System (PARS).
A particular kind of ARS is the GCAS (Ground Collision Avoidance System), a recovery system that activates to avoid impact with the ground. When in proximity of the ground, the FCS predicts trajectory of the aircraft and takes control of the aircraft if necessary.
ARSs are starting to appear in FCSs of new generation high-performance fighter aircrafts and to be integrated into already existing FCSs for older aircrafts.
For example, the FCS of the Eurofighter includes a PARS, and most F-16 now implement a PARS as part of a FCS upgrade. Also a PARS for the FCS of the military trainer M346 “Master” is currently under development.
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1.2 Thesis contribution
This thesis focuses on the analysis of the optimal recovery manoeuvres to be applied by an “ideal” ARS of an high-performance aircraft. The objective of this thesis is to define an adequate optimality index for the problem, to set up a dedicated optimization tool and environment to obtain the optimal recovery manoeuvre for the aircraft. Optimal manoeuvres are compared with PARS generated manoeuvres in order to evaluate the performance of the M346’s PARS.
Meanwhile, efforts have been made by the author to familiarize with the subjects of Optimal
Control Theory and numerical methods for the optimization. The subject being mostly of academic and specialist’s interest, documentation on the matter is either very technical and specific or very generic. The author tried to provide readers with a simple yet comprehensive summary about trajectory optimization problems and numerical methods for optimization.
1.3 Structure of the thesis
The second chapter illustrates ARSs, GCASs and PARS and focuses on the M346 PARS; objectives, functioning and recovery strategies of this feature are clearly defined. This chapter is intended to provide the reader with an insight of how the present PARS operates and of its recovery manoeuvres and resulting trajectories.
The third chapter introduces the Trajectory Optimization (TO) problem along with basics of the Optimal Control Theory. Numerical methods for the solution of the TO problem are described here in detail. Among these methods the Direct Collocation is the most effective and has been chosen for this thesis; an in-depth description of this method is therefore provided.
In the fourth chapter the optimization tools used in the thesis, GPOPS and ICLOCS, are presented. The optimization problem must be described to the tools in an appropriate format; luckily the format required by the optimization tools is really flexible, allowing us to use a Simulink® dynamic model for the specification of the aircraft dynamics. Then, two simple examples are given to show the equivalence of the two tools.
A Trajectory Optimization problem requires the formulation of a performance index; the index specifies how good a trajectory is. The fifth chapter introduces the problem of defining the optimal recovery and illustrate step-by-step how the performance index of this thesis was elaborated.
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The sixth chapter focuses on the Simulink® dynamic model of the aircraft used for the optimization. The dynamic model is a simplified version of the complex complete model, which contains the FCS control laws developed by AleniaAermacchi. Differences between the two models are highlighted, as well as their impact on the accuracy of the results.
The seventh chapter is dedicated to the results of the optimization. Here the optimal trajectories are comparedagainst the recovery trajectories obtained by the PARS.
