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Reconfigurable Autopilot Design using Nonlinear Model Predictive Control: Application to High Performance and Autonomous Aircraft
(Master thesis, 2012)The work presented in this thesis examines several aspects of Nonlinear ModelPredictive Control (NMPC) that display and confirm its promising potentials as apowerful reconfigurable control scheme. The effects of significant ... -
A reconfigurable multi-mode implementation of hyperspectral target detection algorithms
(Peer reviewed; Journal article, 2020)Hyperspectral images obtained by imaging spectrometer contain a large data amount that requires techniques such as target detection for information extraction. The proposed multi-mode FPGA implementation combines matrix ... -
Reconfigurable Sensor Timing and Navigation System for UAVs
(Journal article; Peer reviewed, 2018)As the use of unmanned aerial vehicles (UAVs) for industrial use increases, so are the demands for highly accurate navigation solutions, and with the high dynamics that UAVs offer, the accuracy of a measurement does not ... -
Reconstruction of Building Facades in 3D for Remote Inspection Using a Multicopter
(Master thesis, 2014)This thesis' focus is on how computer vision can be used to reconstruct building facades in 3D based on images taken by an unmanned aerial vehicle for the purpose of inspection. It explores and presents different algorithms ... -
Recurrent Neural Networks and Nonlinear Model-based Predictive Control of an Oil Well with ESP
(Master thesis, 2020)Modellering og simulering er et avgjørende verktøy for å forstå komplekse ulineære systemer. Nøyaktige modeller er ofte nyttige i reguleringssammenhenger, men kan være vanskelige å anskaffe. Innenfor oljeindustrien har ... -
Recursive Feasibility of Stochastic Model Predictive Control with Mission-Wide Probabilistic Constraints
(Chapter, 2021)This paper is concerned with solving chance-constrained finite-horizon optimal control problems, with a particular focus on the recursive feasibility issue of stochastic model predictive control (SMPC) in terms of mission-wide ... -
Recursive Multi-Channel Prony for PMU
(Journal article; Peer reviewed, 2023)The phasor estimation process is important in monitoring, controlling and protecting power networks. Prony's method can be used as an estimator by which electrical power system parameters are approximated. The Prony algorithm ... -
Redesign and Analysis of Globally Asymptotically Stable Bearing Only SLAM
(Chapter; Peer reviewed, 2017)The Simultaneous Localization And Mapping (SLAM) estimation problem is a nonlinear problem, due to the nature of the range and bearing measurements. In latter years it has been demonstrated that if the nonlinearities from ... -
Reduced order modeling of fluid flows: Machine learning, Kolmogorov barrier, closure modeling, and partitioning
(Peer reviewed; Journal article, 2020)In this paper, we put forth a long short-term memory (LSTM) nudging framework for the enhancement of reduced order models (ROMs) of fluid flows utilizing noisy measurements. We build on the fact that in a realistic ... -
Reduced order models for finite-volume simulations of turbulent flow around wind-turbine blades
(Journal article; Peer reviewed, 2021) -
Reduced Order Observer Design for Managed Pressure Drilling
(Master thesis, 2012)Reduced Order Observer Design for Managed Pressure Drilling -
Reduced-Attitude Control of Fixed-Wing Unmanned Aerial Vehicles Using Geometric Methods on the Two-Sphere
(Peer reviewed; Journal article, 2020)As an alternative to reduced-attitude control of fixed-wing unmanned aerial vehicles using roll and pitch angles, we propose to use a global representation that evolves on the two-sphere. The representation of reduced ... -
Reducing Ground Reflection Multipath Errors for Bluetooth Angle-of-Arrival Estimation by Combining Independent Antenna Arrays
(Peer reviewed; Journal article, 2023)For outdoor navigation using Bluetooth direction finding, elevation angle estimate errors due to ground reflection multipath interference is a significant challenge at low elevation angles. One of the ways to reduce this ... -
Reducing Overparametrization in MRAC for Hyperbolic PDEs
(Peer reviewed; Journal article, 2020)We construct a method of dealing with the problem of overparameterization in model reference adaptive control (MRAC) of 2 ×2 linear hyperbolic partial differential equations (PDEs). The method is based on linear interpolation ... -
Reducing power transients in diesel-electric dynamically positioned ships using re-positioning
(Journal article, 2014)A thrust allocation method with a functionality to assist power management systems by using the hull of the ship as a store of potential energy in the field of environmental forces has been recently proposed and demonstrated ... -
Redundant MEMS-based Inertial Navigation using Nonlinear Observers
(Journal article; Peer reviewed, 2017)We present two alternative methods for fault detection and isolation (FDI) with redundant Microelectromechanical system (MEMS) inertial measurement units (IMUs) in inertial navigation systems (INS) based on nonlinear ... -
Redundant System for Precision Landing of VTOL UAVs
(Master thesis, 2018)This thesis investigates how Vertical Take Off and Landing (VTOL) Unmanned Aerial Vehicles (UAVs) can be automatically landed with high precision in a robust way. Automatic precision landing can allow pilots to land in ... -
Reference optimisation of uncertain offshore hybrid power systems with multi-stage nonlinear model predictive control
(Chapter, 2023)This paper presents a modified multi-stage economic nonlinear model predictive controller (M-ENMPC) for reference optimisation of isolated, uncertain offshore hybrid power systems (OHPSs). These systems require control ... -
Refining Dynamics Identification for Co-Bots: Case Study on KUKA LWR4+
(Journal article; Peer reviewed, 2017)This paper presents an attempt to improve dynamic identification procedure for robotic manipulators, such that obtained models are appropriate for trajectory planning and motion control. In addition to algorithms development, ... -
Regularization when modeling with biased simulation data as a prior
(Chapter, 2023)Embedding physical knowledge in system identification increases the generalization capabilities of the identified models. For complex engineering systems, such as a process plant, the most complete and detailed quantitative ...