Searched for: contributor:"Van Kampen, E. (mentor)"
(1 - 20 of 29)

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Dally, Killian (author)
Fault-tolerant flight control faces challenges as developing a model-based controller for each unexpected failure is unrealistic, and online learning methods can handle limited system complexity due to their low sample efficiency. In this research, a model-free coupled-dynamics flight controller for a jet aircraft able to withstand multiple...
master thesis 2021
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Smit, Beau (author)
Control augmentation systems based on Incremental Nonlinear Dynamic Inversion (INDI) are able to provide high-performance nonlinear control without the need for a model of the complete system. Considering a pitch rate control law for a fixed-wing aircraft, only a model for the elevator control effectiveness (CE) and sensor feedback of the pitch...
master thesis 2021
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Miloševiċ, S. (author)
Reinforcement Learning (RL) methods have become a topic of interest for performing guidance and navigation tasks, due to potential adaptability and autonomy improvements within dynamic systems. Nevertheless, a core component of RL is an agent exploring the environment it finds itself in, resulting in an intrinsic violation of the agent's safety....
master thesis 2020
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Kumtepe, Yagiz (author)
Incremental Nonlinear Dynamic Inversion (INDI) is a sensor-based control strategy, which has shown robustness against model uncertainties on various aerospace vehicles. The sensor-based nature of the method brings attractive properties which has made it popular in the last decade. INDI globally linearizes the system by making use of control...
master thesis 2020
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Das, Hemjyoti (author)
Pneumatic cylinders provide an environment-friendly actuation means by minimizing the leakage of any harmful industrial fluids, as occurs for hydraulic actuators. Thus, pneumatic actuators require less maintenance, compared to hydraulic actuators. Moreover, for a similar weight of hydraulic actuator, the cost of a pneumatic actuation system is...
master thesis 2020
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Kroezen, Dave (author)
Online Reinforcement Learning is a possible solution for adaptive nonlinear flight control. In this research an Adaptive Critic Design (ACD) based on Dual Heuristic Dynamic Programming (DHP) is developed and implemented on a simulated Cessna Citation 550 aircraft. Using an online identified system model approximation, the method is independent...
master thesis 2019
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Heyer, Stefan (author)
In recent years Adaptive Critic Designs (ACDs) have been applied to adaptive flight control of uncertain, nonlinear systems. However, these algorithms often rely on representative models as they require an offline training stage. Therefore, they have limited applicability to a system for which no accurate system model is available, nor readily...
master thesis 2019
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Leest, Steven (author)
Robotic behavior policies learned in simulation suffer from a performance degradation once transferred to a real-world robotic platform. This performance degradation originates from discrepancies between the real-world and simulation environment, referred to as the reality gap. To cross the reality gap, this papers presents a simple...
master thesis 2017
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Bhowal, Abhranil (author)
A Reinforcement Learning (RL) agent learns about its environment through exploration. For most physical applications such as search and rescue UAVs, this exploration must take place with safety in mind. Unregulated exploration, especially at the beginning of a run, will lead to fatal situations such as crashes. One approach to mitigating these...
master thesis 2017
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Helmer, A.M.C. (author)
Reinforcement learning is a paradigm for learning decision-making tasks from interaction with the environment. Function approximators solve a part of the curse of dimensionality when learning in high-dimensional state and/or action spaces. It can be a time-consuming process to learn a good policy in a high dimensional state space directly. A...
master thesis 2017
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Verbist, S. (author)
Reinforcement Learning is a much researched topic for autonomous machine behavior and is often applied to navigation problems. In order to deal with growing environments and larger state/action spaces, Hierarchical Reinforcement Learning has been introduced. Unfortunately learning from experience, which is central to Reinforcement Learning,...
master thesis 2017
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Beekman, M.E.J. (author)
master thesis 2016
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Regtuit, R.M. (author)
Acceptance of automation has been a bottleneck for successful introduction of automation in Air Traffic Control. Strategic conformal automation has been proven to increase automation acceptance, by creating a better match between automation and operator decision-making. In this paper strategic conformal automation for Air Traffic Control is...
master thesis 2016
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van 't Veld, R.C. (author)
Incremental Nonlinear Dynamic Inversion (INDI) is a variation on Nonlinear Dynamic Inversion (NDI) retaining the high-performance advantages of NDI, while increasing controller robustness to model uncertainties and decreasing the dependency on the vehicle model. After a successful flight test with a multirotor Micro Aerial Vehicle (MAV), the...
master thesis 2016
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Unni, S. (author)
The ease of availability of low cost aerial platforms has given rise to extensive research in the field of autonomous navigation. There are strong indications in existing research that UAV autonomy leads to significant gains in terms of safety as well as performance in a number of scenarios, including but not limited to search and rescue...
master thesis 2016
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Cheung, C. (author)
Unmanned aerial vehicle (UAV) applications are increasing and there is a need for safe operations in terms of avoidance. The Velocity Obstacle (VO) method uses position and velocity vectors to determine if a collision is going to happen; an adaptation of the VO- method is called the Selective Velocity Obstacle (SVO) method and adds navigation...
master thesis 2016
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Schonebaum, G. (author)
master thesis 2016
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Molenkamp, D. (author)
A novel intelligent controller selection method for quadrotor attitude and altitude control is presented that maintains performance in different regimes of the flight envelope. Conventional quadrotor controllers can behave insufficiently during aggressive manoeuvring, in extreme angles the quadrotor is unable to maintain height which may result...
master thesis 2016
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Bosman, L.M. (author)
In applications like model identification accurate methods for data approximation are required. Multivariate simplex B-splines form a class of nonlinear function approximators capable of approximating scattered data. Simplex B-splines are piecewise polynomials defined on a triangulation. Currently, data approximation using simplex B-splines is...
master thesis 2014
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Visser, T. (author)
A new type of multivariate spline, based on tensor-product splines, is introduced and applied for function approximation purposes. An algorithm for system identification using these multiplex splines is developed and validated on DelFly II flight tests data.
master thesis 2014
Searched for: contributor:"Van Kampen, E. (mentor)"
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