Searched for: author:"van Kampen, E."
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Wang, X. (author), van Kampen, E. (author), Chu, Q. P. (author), Lu, Peng (author)
As a sensor-based control method, incremental nonlinear dynamic inversion (INDI) has been applied to various aerospace systems and has shown desirable robust performance against aerodynamic model uncertainties. However, its previous derivation based on the time scale separation principle has some limitations. There is also a need for stability...
journal article 2019
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Wang, X. (author), van Kampen, E. (author), Chu, Q. P. (author)
This paper proposes a novel control framework that combines the recently reformulated incremental nonlinear dynamic inversion with (higher-order) sliding-mode controllers/observers, for generic multi-input/multi-output nonlinear systems, named incremental sliding-mode control. As compared to the widely used approach that designs (higher-order...
journal article 2019
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Siddiquee, M. (author), Junell, J. (author), van Kampen, E. (author)
Reinforcement Learning (RL) has been applied to teach quadcopters guidance tasks. Most applications rely on position information from an absolute reference system such as Global Positioning System (GPS). The dependence on “absolute position” information is a general limitation in the autonomous flight of Unmanned Aerial Vehicles (UAVs)....
conference paper 2019
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Zammit, C. (author), van Kampen, E. (author)
Advancements in Unmanned Aerial Vehicles (UAVs) design, actuator and sensory systems and control are making such devices financially available to a wide spectrum of users with various demands and expectations. To mitigate with this ever increasing demand robust, efficient and application–specific path planning is important. This paper...
conference paper 2019
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Keijzer, Twan (author), Looye, Gertjan (author), Chu, Q. P. (author), van Kampen, E. (author)
This paper discusses the design, implementation and flight testing of an incremental Backstepping (IBS) based manual flight control law with angular accelerometer (AA) feedback. The main advantages of incremental control laws are that they only require a partial model of the system and are of low complexity. Incremental control laws for...
conference paper 2019
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de Vries, Pieter Simke (author), van Kampen, E. (author)
Established Control Allocation (CA) methods rely on knowledge of the control effectiveness for distributing control effector utilization for control of (overactuated) systems. The Innovative Control Effectors (ICE) aircraft model is highly overactuated with its 13 control effectors, CA is a preferred method to distribute control effector...
conference paper 2019
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Naruta, Anton (author), Mannucci, T. (author), van Kampen, E. (author)
This paper describes an implementation of a reinforcement learning-based framework applied to the control of a multi-copter rotorcraft. The controller is based on continuous state and action Q-learning. The policy is stored using a radial basis function neural network. Distance-based neuron activation is used to optimize the generalization...
conference paper 2019
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Wang, X. (author), Sun, S. (author), van Kampen, E. (author), Chu, Q. P. (author)
This paper proposes an Incremental Sliding Mode Control driven by Sliding Mode Disturbance Observers (INDI-SMC/SMDO), with application to a quadrotor fault tolerant control problem. By designing the SMC/SMDO based on the control structure of the sensor-based Incremental Nonlinear Dynamic Inversion (INDI), instead of the model-based Nonlinear...
journal article 2019
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Mannucci, T. (author), van Kampen, E. (author), de Visser, C.C. (author), Chu, Q. (author)
Self-learning approaches, such as reinforcement learning, offer new possibilities for autonomous control of uncertain or time-varying systems. However, exploring an unknown environment under limited prediction capabilities is a challenge for a learning agent. If the environment is dangerous, free exploration can result in physical damage or in...
journal article 2018
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Goedhart, Menno (author), van Kampen, E. (author), Armanini, S.F. (author), de Visser, C.C. (author), Chu, Q. (author)
Flight control of Flapping Wing Micro Air Vehicles is challenging, because of their complex dynamics and variability due to manufacturing inconsistencies. Machine Learning algorithms can be used to tackle these challenges. A Policy Gradient algorithm is used to tune the gains of a Proportional-Integral controller using Reinforcement Learning. A...
conference paper 2018
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Wang, X. (author), van Kampen, E. (author), Chu, Q. (author), Lu, P (author)
As a sensor-based control approach, the Incremental Nonlinear Dynamic Inversion (INDI) method has been successfully applied on various aerospace systems and shown desirable robust performance to aerodynamic model uncertainties. However, its previous derivations based on the so-called time scale separation principle is not mathematically rigorous...
conference paper 2018
document
Zammit, C. (author), van Kampen, E. (author)
Unmanned Aerial Vehicles (UAVs) are being integrated into a wide range of indoor and outdoor applications. In this light, robust and efficient path planning is paramount. An extensive literature review showed that the A* and Rapidly{Exploring Random Tree (RRT) algorithms and their variants are the most promising path planning algorithms...
conference paper 2018
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Regtuit, Robert (author), Borst, C. (author), van Kampen, E. (author), van Paassen, M.M. (author)
Acceptance of automation has been a bottleneck for successful introduction of automation in Air Trac 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 Trac Control is designed...
conference paper 2018
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Grondman, Fabian (author), Looye, Gertjan H.N. (author), Kuchar, Richard O. (author), Chu, Q. (author), van Kampen, E. (author)
This paper describes the design, implementation and flight testing of flight control laws based on Incremental Nonlinear Dynamic Inversion (INDI). The method compares com- manded and measured accelerations to compute increments on the current control de ec- tions. This results in highly robust control solutions with respect to model...
conference paper 2018
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van 't Veld, Ronald (author), van Kampen, E. (author), Chu, Q. (author)
Incremental nonlinear dynamic inversion (INDI) is a variation on nonlinear dynamic inversion (NDI), retaining the high-performance characteristics, while reducing model dependency and increasing robustness. After a successful flight test with a multirotor micro aerial vehicle, the question arises whether this technique can be used to...
conference paper 2018
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Çakiroğlu, Can (author), van Kampen, E. (author), Chu, Q. (author)
Incremental Nonlinear Dynamic Inversion (INDI) is a robust nonlinear control tech­nique that is an adaptation of nonlinear dynamic inversion (NDI). By assuming time scale separation between fast and slow dynamics, and by using angular acceleration feedback, the inner loop of INDI directly controls angular accelerations with incremental control...
conference paper 2018
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Fasiello, Simone (author), Jump, Michael (author), Pavel, M.D. (author), van Kampen, E. (author), Masarati, Pierangelo (author)
Nowadays, the complexity of high speed civil transport and highly-augmented rotorcraft, has led to an increase in the chances of encountering unwanted unstable phenomena, such as the so called Aircraft/Rotorcraft-Pilot Couplings (A/RPCs) or Pilot-Induced Oscillations (PIOs), whose unpredictability has given rise to a serious problem concerning...
conference paper 2018
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Nabi, H.N. (author), Lombaerts, T.J.J. (author), Zhang, Y. (author), van Kampen, E. (author), Chu, Q. (author), de Visser, C.C. (author)
The research presented in this paper focuses on the effects of structural failures on the safe flight envelope of an aircraft, which is the set of all the states in which safe maneuver of the aircraft can be assured. Nonlinear reachability analysis basedonan optimal control formulation is performed to estimate the safe flight envelope using...
journal article 2018
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Helmer, Alexander (author), de Visser, C.C. (author), van Kampen, E. (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...
conference paper 2018
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Verbist, Stephen (author), Mannucci, T. (author), van Kampen, E. (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,...
conference paper 2018
Searched for: author:"van Kampen, E."
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