The Helicopter Emergency Medical Service (HEMS) accident rate has driven operators from around the world to address the management of risks inherent to their operations. In-flight decision-making, pre-flight planning, failure to follow standard operating procedures, delayed remedial actions, and misinterpretation of environmental cues are all areas that need to be addressed for safe HEMS operations. HEMS operations are complex, being a joint exercise between the flight crew, paramedics and supporting agencies. Operations occur around-the-clock, in all-weather conditions, and often with no fore-warning. In a time critical operation, where precious minutes may cost lives, operators must decide which cases warrant a HEMS response and if so, whether the conditions are safe to conduct the mission. Intelligent systems are an emerging field offering benefits to a multitude of applications. This research forms a comprehensive investigation of the application of 'intelligent systems' to the pre-mission analysis of HEMS operations. The research has resulted in the development of a prototype decision support system capable of assisting in the pre-mission analysis of HEMS operations. The prototype system is capable of supporting flight coordinators and crew in the decision-making processes prior to HEMS operations and can potentially improve emergency medical services to the community.

Master of Engineering (Research) / This thesis, by developing a Miniature Aerial Vehicle (MAV) hovering platform, presents a practical solution to allow researchers and students to implement their theoretical methods for guidance and navigation in the real world. The thesis is not concerned with the development of guidance and navigation algorithms, nor is it concerned with the development of external sensors. There have been some recent advances in guidance and navigation towards developing algorithms and simple sensors for MAVs. The task of developing a platform to test such advancements is the subject of this thesis. It is considered a difficult and time consuming process due to the complexities of autonomous flight control and the strict size, weight and computational requirements of this type of system. It would be highly beneficial to be able to buy a platform specifically designed for this task that already possesses autonomous hovering capability and the expansion connectivity for interfacing your own custom developed sensors and algorithms. Many biological and computer scientists would jump at the opportunity to maximize their research by real world implementation. The development of such a system is not a trivial task. It requires a great deal of understanding in a broad range of fields including; Aeronautical, Microelectronic, Mechanical, Computer and Embedded Software Engineering in order to create a successful prototype. The challenge of this thesis was to design a research platform to enable easy implementation of external sensors and guidance algorithms, in a real world environment for research and education. The system is designed so it could be used for a broad range of testing experiments. After extensive research in current MAV and avionics design it became obvious in several areas the best available products were not sufficient to meet the needs of the proposed platform. Therefore it was necessary to custom design and build; sensors, a data acquisition system and a servo controller. The latter two products are available for sale by Jimonics (www.jimonics.com). It was then necessary to develop a complete flight control system with integrated sensors, processor and wireless communications network which is called ‘The MicroBrain’. ‘The MicroBrain’ board measures only 45mm x 35mm x 11mm and weighs ~11 grams. The coaxial contra-rotating MAV platform design provides a high level of mechanical stability to help minimise the control system complexity. The platform was highly modified from a commercially available remotely controlled helicopter. The system incorporates a novel collision protection system that was designed to also double as a mounting place for external sensors around its perimeter. The platform equipped with ‘The MicroBrain’ is capable of fully autonomous hover. This provides a great base for testing guidance and navigational sensors and algorithms by decoupling the difficult task of platform design and low-level stability control. By developing a platform with these capabilities the researcher can now focus on the guidance and navigation task, as the difficulties in developing a custom platform have been taken care of. This therefore promotes a faster evolution of guidance and navigational control algorithms for MAVs.

This thesis makes a number of new contributions to control and sensing for unmanned vehicles. I begin by developing a non-linear simulation of a small unmanned helicopter and then proceed to develop new algorithms for control and sensing using the simulation. The work is field-tested in successful flight trials of biologically inspired vision and neural network control for an unstable rotorcraft. The techniques are more robust and more easily implemented on a small flying vehicle than previously attempted methods.¶ Experiments from biology suggest that the sensing of image motion or optic flow in insects provides a means of determining the range to obstacles and terrain. This biologically inspired approach is applied to control of height in a helicopter, leading to the World’s first optic flow based terrain following controller for an unmanned helicopter in forward flight. Another novel optic flow based controller is developed for the control of velocity in hover. Using the measurements of height from other sensors, optic flow is used to provide a measure of the helicopters lateral and longitudinal velocities relative to the ground plane. Feedback of these velocity measurements enables automated hover with a drift of only a few cm per second, which is sufficient to allow a helicopter to land autonomously in gusty conditions with no absolute measurement of position.¶ New techniques for sensor fusion using Extended Kalman Filtering are developed to estimate attitude and velocity from noisy inertial sensors and optic flow measurements. However, such control and sensor fusion techniques can be computationally intensive, rendering them difficult or impossible to implement on a small unmanned vehicle due to limitations on computing resources. Since neural networks can perform these functions with minimal computing hardware, a new technique of control using neural networks is presented. First a hybrid plant model consisting of exactly known dynamics is combined with a black-box representation of the unknown dynamics. Simulated trajectories are then calculated for the plant using an optimal controller. Finally, a neural network is trained to mimic the optimal controller. Flight test results of control of the heave dynamics of a helicopter confirm the neural network controller’s ability to operate in high disturbance conditions and suggest that the neural network outperforms a PD controller. Sensor fusion and control of the lateral and longitudinal dynamics of the helicopter are also shown to be easily achieved using computationally modest neural networks.

<p>There are a number of ongoing projects developing autonomous vehicles, both helicopters and airplanes. The purpose of this thesis is to study a concept for calculating the height and attitude of a helicopter. The system will be active during landing. This thesis includes building an experimental setup and to develop algorithms and software.</p><p>The basic idea is to illuminate the ground with a certain pattern and in our case we used laser pointers to create this pattern. The ground is then filmed and the images are processed to extract the pattern. This provides us with information about the height and attitude of the helicopter. Furthermore, the concept implies that no equipment on the ground is needed. With further development the sensor should be able to calculate the movement of the underlying surface relative to the helicopter. This is very important when landing on a moving surface, e.g. a ship at sea.</p><p>To study the concept empirically an experimental setup was constructed. The setup provides us with the necessary information to evaluate how well the system could perform in reality. The setup is built with simple and cheap materials. In the setup an ordinary web camera and laser pointers that are avaliable for everyone have been used.</p> / <p>Det finns flera pågående projekt inom autonomflygande farkoster, både för helikoptrar och flygplan. Syftet med vårt examensarbetet är att undersöka ett koncept för en landningssensor för autonom landning med helikopter. Examensarbetet innebär att bygga en fysisk modell för test av konceptet samt att utveckla mjukvara.</p><p>Konceptet för sensorn består av att belysa marken med ett speciellt mönster, i vårt fall skapas mönstret av laserpekare, som därefter fotograferas och bildbehandlas. Detta mönster ger sedan information om helikopterns höjd och attityd i luften. Vidare innebär konceptet också att ingen markutrustning krävs för att sensorn ska fungera. I förlängningen ska man med detta koncept kunna beräkna hur underlaget rör sig relativt helikoptern, vilket är väldigt viktigt vid landning på objekt som rör sig, till exempel ett fartyg.</p><p>För att undersöka hur bra sensorn presterar i verkligheten så har en rigg byggts. Riggen är byggd med enkla och billiga material. I det här fallet används en webbkamera och laserpekare som går att köpa i vanliga elektronikaffärer.</p>

<p>This master thesis was carried out at the Department of Aerodynamics and Flight Mechanics at Saab Aerosystems, Linköping, Sweden. It makes up the author’s final work prior to graduation in the field Applied Physics and Electrical Engineering at the Department of Electrical Engineering at The Linköping Institute of Technology (LiTH), Linköping, Sweden.</p><p> </p><p>The objective of the paper was to study a non-uniform helicopter rotor downwash model in forward flight for the unmanned helicopter Skeldar, which is under development at Saab. The main task was to compare the mentioned model with today’s uniform downwash model in order to find differences and similarities. This was done both from a modeling and a controlling perspective. To start with, an introduction is given which is followed by a helicopter theory chapter. The following three chapters deal with the theory of induced velocity, the helicopter model and the Linear Quadratic Regulator (LQR). Finally, the results are presented and discussed.</p><p> </p><p>The downwash models were derived using Momentum Theory (MT) and Blade Element Theory (BET). These two theories were combined in order to find a connection between the induced velocity and the rotor thrust coefficient. The non-uniform downwash model that was studied is proposed by Pitt & Peters and describes a linear variation of the induced velocity in the longitudinal plane.</p><p> </p><p>For the control, a LQ-regulator was chosen since it is easily implemented in MATLAB and it stabilizes the plant model by feedback and consequently creates a robust system. Before the controller could be implemented, the models had to be reduced and the states had to be divided into longitudinal and lateral ones.</p><p> </p><p>The comparison between the open systems clearly shows that differences in the inflow models propagate to all states and consequently the helicopter behaves differently in all planes. Great discrepancies are apparent for the angular velocities <em>p</em> and <em>q</em>. For Pitt & Peters’ model those states are believed to be strongly affected by the system’s positive real pole, causing a rather unstable behavior. When the systems were closed by feedback, the differences were reduced dramatically. Pitt & Peters’ model resulted in greater overshoots than the uniform model, but the overall behavior of all states was rather similar for the two models.</p><p> </p><p>It is concluded, that the adaption of Pitt & Peters’ inflow model does not make any substantial difference when a controller is implemented. The differences between the open systems, however, are reason enough to question Pitt & Peters’ model. In order to evaluate the non-uniform model properly, it has to be compared to suitable flight data which is still lacking up to this date.</p>

There are a number of ongoing projects developing autonomous vehicles, both helicopters and airplanes. The purpose of this thesis is to study a concept for calculating the height and attitude of a helicopter. The system will be active during landing. This thesis includes building an experimental setup and to develop algorithms and software. The basic idea is to illuminate the ground with a certain pattern and in our case we used laser pointers to create this pattern. The ground is then filmed and the images are processed to extract the pattern. This provides us with information about the height and attitude of the helicopter. Furthermore, the concept implies that no equipment on the ground is needed. With further development the sensor should be able to calculate the movement of the underlying surface relative to the helicopter. This is very important when landing on a moving surface, e.g. a ship at sea. To study the concept empirically an experimental setup was constructed. The setup provides us with the necessary information to evaluate how well the system could perform in reality. The setup is built with simple and cheap materials. In the setup an ordinary web camera and laser pointers that are avaliable for everyone have been used. / Det finns flera pågående projekt inom autonomflygande farkoster, både för helikoptrar och flygplan. Syftet med vårt examensarbetet är att undersöka ett koncept för en landningssensor för autonom landning med helikopter. Examensarbetet innebär att bygga en fysisk modell för test av konceptet samt att utveckla mjukvara. Konceptet för sensorn består av att belysa marken med ett speciellt mönster, i vårt fall skapas mönstret av laserpekare, som därefter fotograferas och bildbehandlas. Detta mönster ger sedan information om helikopterns höjd och attityd i luften. Vidare innebär konceptet också att ingen markutrustning krävs för att sensorn ska fungera. I förlängningen ska man med detta koncept kunna beräkna hur underlaget rör sig relativt helikoptern, vilket är väldigt viktigt vid landning på objekt som rör sig, till exempel ett fartyg. För att undersöka hur bra sensorn presterar i verkligheten så har en rigg byggts. Riggen är byggd med enkla och billiga material. I det här fallet används en webbkamera och laserpekare som går att köpa i vanliga elektronikaffärer.

This master thesis was carried out at the Department of Aerodynamics and Flight Mechanics at Saab Aerosystems, Linköping, Sweden. It makes up the author’s final work prior to graduation in the field Applied Physics and Electrical Engineering at the Department of Electrical Engineering at The Linköping Institute of Technology (LiTH), Linköping, Sweden.   The objective of the paper was to study a non-uniform helicopter rotor downwash model in forward flight for the unmanned helicopter Skeldar, which is under development at Saab. The main task was to compare the mentioned model with today’s uniform downwash model in order to find differences and similarities. This was done both from a modeling and a controlling perspective. To start with, an introduction is given which is followed by a helicopter theory chapter. The following three chapters deal with the theory of induced velocity, the helicopter model and the Linear Quadratic Regulator (LQR). Finally, the results are presented and discussed.   The downwash models were derived using Momentum Theory (MT) and Blade Element Theory (BET). These two theories were combined in order to find a connection between the induced velocity and the rotor thrust coefficient. The non-uniform downwash model that was studied is proposed by Pitt &amp; Peters and describes a linear variation of the induced velocity in the longitudinal plane.   For the control, a LQ-regulator was chosen since it is easily implemented in MATLAB and it stabilizes the plant model by feedback and consequently creates a robust system. Before the controller could be implemented, the models had to be reduced and the states had to be divided into longitudinal and lateral ones.   The comparison between the open systems clearly shows that differences in the inflow models propagate to all states and consequently the helicopter behaves differently in all planes. Great discrepancies are apparent for the angular velocities p and q. For Pitt &amp; Peters’ model those states are believed to be strongly affected by the system’s positive real pole, causing a rather unstable behavior. When the systems were closed by feedback, the differences were reduced dramatically. Pitt &amp; Peters’ model resulted in greater overshoots than the uniform model, but the overall behavior of all states was rather similar for the two models.   It is concluded, that the adaption of Pitt &amp; Peters’ inflow model does not make any substantial difference when a controller is implemented. The differences between the open systems, however, are reason enough to question Pitt &amp; Peters’ model. In order to evaluate the non-uniform model properly, it has to be compared to suitable flight data which is still lacking up to this date.

Research has presented several approaches to achieve varying degrees of fault-tolerance in unmanned aircraft. Approaches in reconfigurable flight control are generally divided into two categories: those which incorporate multiple non-adaptive controllers and switch between them based on the output of a fault detection and identification element and those that employ a single adaptive controller capable of compensating for a variety of fault modes. Regardless of the approach for reconfigurable flight control, certain fault modes dictate system restructuring in order to prevent a catastrophic failure. System restructuring enables active control of actuation not employed by the nominal system to recover controllability of the aircraft. After system restructuring, continued operation requires the generation of flight paths that adhere to an altered flight envelope. The control architecture developed in this research employs a multi-tiered hierarchy to allow unmanned aircraft to generate and track safe flight paths despite the occurrence of potentially catastrophic faults. The hierarchical architecture increases the level of autonomy of the system by integrating five functionalities with the baseline system: fault detection and identification, active system restructuring, reconfigurable flight control, reconfigurable path planning, and mission adaptation. Fault detection and identification algorithms continually monitor aircraft performance and issue fault declarations. When the severity of a fault exceeds the capability of the baseline flight controller, active system restructuring expands the controllability of the aircraft using unconventional control strategies not exploited by the baseline controller. Each of the reconfigurable flight controllers and the baseline controller employ a proven adaptive neural network control strategy. A reconfigurable path planner employs an adaptive model of the vehicle to re-shape the desired flight path. Generation of the revised flight path is posed as a linear program constrained by the response of the degraded system. Finally, a mission adaptation component estimates limitations on the closed-loop performance of the aircraft and adjusts the aircraft mission accordingly. A combination of simulation and flight test results using two unmanned helicopters validates the utility of the hierarchical architecture.

The purpose of this study was to create a proof-of-concept piezoelectric actuator system capable of meeting the performance requirements necessary for actuation of a trailing edge flap for a helicopter main rotor blade. Due to extremely small displacements produced by piezoelectric actuators, their output is amplified several times in order to produce the required displacement for this device. The amplification is accomplished in two stages. The first stage, mechanical amplification, uses differential length lever arms to increase the piezoelectric actuator output. The second stage, hydraulic amplification, is coupled to the first stage and uses differential area pistons to further amplify the output of the mechanical amplifier. The actuation systems force and displacement output is characterized based on frequency.

This thesis concerns the development, evaluation, comparison and testing of a UH-1H helicopter simulation model with various fidelity levels. In particular, the well known minimum complexity simulation model is updated with various higher fidelity simulation components, such as the Peters-He inflow model, horizontal tail contribution, improved tail rotor model, control mapping, ground eect, fuselage interactions, ground reactions etc. Results are compared with available flight test data. The dynamic model is integrated into the open source simulation environment called Flight Gear. Finally, the model is cross-checked through evaluations using test pilots.