Automatic Flight Control Systems

The history of flight control is inseparably linked to the history of aviation itself. Since the early days, the concept of automatic flight control systems has evolved from mechanical control systems to highly advanced automatic fly-by-wire flight control systems which can be found nowadays in military jets and civil airliners. Even today, many research efforts are made for the further development of these flight control systems in various aspects. Recent new developments in this field focus on a wealth of different aspects. This book focuses on a selection of key research areas, such as inertial navigation, control of unmanned aircraft and helicopters, trajectory control of an unmanned space re-entry vehicle, aeroservoelastic control, adaptive flight control, and fault tolerant flight control. This book consists of two major sections. The first section focuses on a literature review and some recent theoretical developments in flight control systems. The second section discusses some concepts of adaptive and fault-tolerant flight control systems. Each technique discussed in this book is illustrated by a relevant example

Imitation Learning and Direct Perception for Autonomous Driving

This thesis presents two learning based approaches to solve the autonomous driving problem: end-to-end imitation learning and direct visual perception. Imitation learning uses expert demonstrations to build a policy that serves as a sensory stimulus to action mapping. During inference, the policy takes in readings from the vehicle's onboard sensors such as cameras, radars, and lidars, and converts them to driving signals. Direct perception on the other hand uses these sensor readings to predict a set of features that define the system's operational state, or affordances, then these affordances are used by a physics based controller to drive the vehicle. To reflect the context specific, multimodal nature of the driving task, these models should be aware of the context, which in this case is driver intention. During development of the imitation learning approach, two methods of conditioning the model were trialed. The first was providing the context as an input to the network, and the second was using a branched model with each branch representing a different context. The branched model showed superior performance, so branching was used to bring context awareness to the direct perception model as well. There were no preexisting datasets to train the direct perception model, so a simulation based data recorder was built to create training data. By creating new data that included lane change behavior, the first direct perception model that includes lane change capabilities was trained. Lastly, a kinematic and a dynamic controller were developed to complete the direct perception pipeline. Both take advantage of having access to road curvature. The kinematic controller has a hybrid feedforward-feedback structure where the road curvature is used as a feedforward term, and lane deviations are used as feedback terms. The dynamic controller is inspired by model predictive control. It iteratively solves for the optimal steering angle to get the vehicle to travel in a path that matches the reference curvature, while also being assisted by lane deviation feedback

Physics-Based Modeling for Control and Autonomous Operation of Unmanned Aerial Vehicles

UAS are widely employed in commercial and military applications, and their utilization is growing at a rapid pace. Effective predictive models for aeromechanics, body dynamics and control are critical in trajectory planning and optimization, autonomous operations, and decision-making. Aeromechanical and wind models that are currently used in the control and guidance of UAS are typically simplistic and often do not represent the essential physics to an adequate degree. Therefore, the performance and versatility of such vehicles may be limited in extreme flight conditions. At the other end of the spectrum, there exist high fidelity models that are computationally expensive, and thus not applicable in path planning, optimization, and onboard flight controllers. The major goal of this dissertation is to bridge the gap between physics-based models and onboard decision-making. Multi-disciplinary models of appropriate fidelity are developed and integrated into a comprehensive flight simulation software suite. These models are experimentally validated and utilized in trajectory planning, optimization, onboard control and autonomous flight. Studying the impact of models of different fidelity for the environment and the aerodynamics determines the impact of modeling uncertainty on system-level goals. A vortex-based model for lifting surfaces is developed, using which control surfaces and couplings therein can be efficiently represented. Using this model, the interaction of the propeller wake with a downstream wing is studied, and it is demonstrated these models are effective tools in predicting the propeller-induced span-wise loading. Such a model is beneficial for trajectory planning and optimization applications to improve flight stability and trajectory tracking. Next, a novel HBEM model is developed to predict rotor forces over a wide range of flight conditions. The HBEM model is self-contained and combines blade element theory, momentum theory and a linear inflow model to determine the {em unique} inflow that is {em consistent with all theories}. The model utilizes the blade geometry and the flight condition as inputs to determine the relationship between the forces/moments and the rotor RPM. A detailed set of wind tunnel experiments is conducted to validate the model across a very wide range of flight regimes. Further, a semi-empirical model for the RIPF is developed using experimental data. It is noted that these models can be executed in real-time which makes them useful for implementation in flight software. A custom quadrotor is built and equipped with an ultrasonic wind sensor and RPM sensors. The HBEM and RIPF models are embedded in quadrotor flight software, and it is illustrated these models are fully integrable and efficient enough to run on a typical onboard compute module. To evaluate the ability of these models to function in harsh environmental conditions, motion capture aided autonomous flight is realized in the presence of strong wind gusts generated by a large industrial fan. A feedforward controller is designed to incorporate physical insight into flight mechanics and to provide estimates of the state. Flight tests are conducted in and out of strong crosswind conditions to further show the impact of computationally efficient models that are capable of being executed onboard in real-time. It is shown that the wind sensing and physics-based models along with the feedforward controller improve trajectory tracking in extreme environmental conditions.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169719/1/davoudi_1.pd

Terminal control of a variable-stability slender reentry vehicle

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2008.Includes bibliographical references (p. 127-129).Various terminal control schemes are applied to a proposed slender reentry vehicle, controlled by two separately-articulating flaps. The flap deflections are summarized as symmetric and asymmetric flap deflections; the former manipulates the drag, lift-curve slope, and static margin; the latter controls the vehicle trim characteristics. The control problem is interesting because the static margin can be actively controlled from statically stable in pitch to statically unstable in pitch. Deflection limits on the flaps present a control saturation that must be considered in control system design. A baseline, angle of attack tracking linear-quadratic servo (LQ-servo) controller is detailed, including an analysis of actuator dynamics and a lead compensator. Desired time response characteristics and robustness to center of pressure uncertainty, reduced control effectiveness, and external pitch accelerations drive the selection of a symmetric deflection at specified points on the reentry trajectory. A hybrid switchinglinear controller (SLC) is developed to reduce the peak overshoot and settling time. A saturated control drives the phase plane trajectory toward a region of satisfactory linear control, where the LQ-servo controller is properly initialized and controls the phase plane trajectory to the reference command. SLC does not provide appreciable robustness gains compared to the LQ-servo controller. A model-reference adaptive controller is described. Saturation effects prevent the adaptive controller from providing additional robustness. A method to adaptively control both the symmetric and asymmetric flap deflections is proposed.by Matthew Thomas Karmondy.S.M

A Doppler Lidar system with preview control for wind turbine load mitigation

This dissertation focuses on the development of a system for wind turbine in order to mitigate the load from unstable wind speed. The work is divided into 2 main parts: a cost efficient Doppler wind Lidar system is developed based on a short coherence length laser system in combine with multiple length delayline concept; a preview pitch control is developed based on the design of a combination of 2 degree of freedom (2-DOF) feedback / feedforward control with a model predictive control

Innovative decision-making methods for the preliminary design and operations of air-cushion and other marine vehicles

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 178-183).Ship design is a large-scale, multi-level, complex problem that requires decision-making at every stage of the design process. As such, it requires a great deal of time and resources. The evolution of the process of ship design has been relatively slow and is still based to a large extent on traditional methods that have been used for many decades. Evans' design spiral, which dates back to 1959, is the most characteristic example. These methods are reflected on the structure of various modem ship design software. However, these methods include inherent inefficiencies that need to be addressed. Some of them are the increased number of iterations, as well as the speed of execution of every iteration. The methods proposed in this dissertation try to alleviate such inefficiencies by introducing novel and easy-to-use approaches, including the formulation of new algorithms. Furthermore, concrete models are introduced in cases where there is no systematic approach to a problem. These approaches include both optimization and heuristic techniques. Neural networks belong to the first category, and although they have been used for small-scale marine problems, they haven't been extensively tested in a more general framework. Heuristics include methods such as the Mapping Model and the QuickEst algorithm, which are not found in marine applications. Heuristic methods are divided into quantitative and qualitative techniques. This research focuses on Air Cushion Vehicles since they are the newest type of advanced marine vehicles and their study is considered both tedious and challenging. However, the research also expands to other types of marine vehicles. Both design and operational aspects are examined as case studies. The results from these methods are cross-validated with other well-established and widely-used methods such as Multiple Linear Regression, proving the usefulness and validity of the considered methods.by Georgios Gougoulidis.Ph.D

The role of joint training in inter-organizational collaboration in emergency management

Doctoral thesis (PhD) – Nord University, 2021publishedVersio