Ultra Wideband Based Indoor Localization Using Sensor Fusion And Support Vector Machine
Download Ultra Wideband Based Indoor Localization Using Sensor Fusion And Support Vector Machine PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Ultra Wideband Based Indoor Localization Using Sensor Fusion And Support Vector Machine book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Ultra-wideband Based Indoor Localization Using Sensor Fusion and Support Vector Machine
Author: Zhuoqi Zeng
language: en
Publisher: Logos Verlag Berlin GmbH
Release Date: 2020-12-21
To further improve the NLOS detection and mitigation performance for Ultra-wideband (UWB) system, this thesis systematically investigates the UWB LOS/NLOS errors. The LOS errors are evaluated in different environments and with different distances. Different blockage materials and blockage conditions are considered for NLOS errors. The UWB signal propagation is also investigated. Furthermore, the relationships between the CIRs and the accurate/inaccurate range measurements are theoretically discussed in three different situations: ideal LOS path, small-scale fading: multipath and NLOS path. These theoretical relationships are validated with real measured CIRs in the Bosch Shanghai office environment. Based on the error and signal propagation investigation results, four different algorithms are proposed for four different scenarios to improve the NLOS identification accuracy. After the comparison of the localization performance for TOA/TDOA, it is found that on normal office floor, TOA works better than TDOA. In harsh industrial environments, where NLOS frequently occurs, TDOA is more suitable than TOA. Thus, in the first scenario, the position estimation is realized with TOA on the office floor, while in the second scenario, a novel approach to combined TOA and TDOA with accurate range and range difference selection is proposed in the harsh industrial environment. The optimization of the feature combination and parameters in machine learning algorithms for accurate measurement detection is discussed for both scenarios. For the third and fourth scenarios, the UWB/IMU fusion system stays in focus. Instead of detecting the NLOS outliers by assuming that the error distributions are Gaussian, the accurate measurement detection is realized based on the triangle inequality theorem. All the proposed approaches are tested with the collected measurements from the developed UWB system. The position estimation of these approaches has better accuracy than that of the traditional methods.
Optimal active power control of wind turbines for grid stability support
Author: Bashar Mousa Melhem
language: en
Publisher: Logos Verlag Berlin GmbH
Release Date: 2025-03-07
This dissertation addresses the critical challenge of grid frequency stability in the context of increasing reliance on renewable energy sources, particularly wind power. As the integration of wind turbines into power systems grows, ensuring their effective contribution to frequency regulation becomes essential. This research proposes a novel approach that employs data-enabled predictive control to enhance the frequency control of the future heterogeneous power grid and hence improve the overall grid stability. The study begins with a comprehensive analysis of the dynamic interactions between wind turbines and the power grid, identifying key factors that impact frequency control. A predictive control framework is developed to anticipate grid frequency fluctuations and optimize turbine responses. Through rigorous simulations and practical case studies, the author demonstrates the effectiveness of the proposed strategies in mitigating frequency deviations and improving overall system resilience. The findings highlight that data-enabled control not only enhances the responsiveness of wind turbines, among other generating units, to frequency support but also contributes significantly to a more stable and reliable power grid.
Distributed Optimisation for Multi-Robot Cooperative Manipulation Control in Dynamic Environments
Author: Yanhao He
language: en
Publisher: Logos Verlag Berlin GmbH
Release Date: 2022-12-15
Since the manipulation tasks for robotic systems become more and more complicated, multi-robot cooperation has been attracting much attention recently. Furthermore, under the trend of human-robot co-existence, collision-free motion control is now also desired on multi-robot groups. This dissertation aims to design a novel distributed optimal control framework to deal with multi-robot cooperative manipulation of rigid objects in dynamic environments. Besides object transportation, the control scheme also tackles obstacle avoidance, joint-space performance optimisation and internal force suppression. The proposed control framework has a two-layer structure, with a distributed optimisation algorithm in the kinematic layer for generating proper joint configuration references, followed by a robot motion controller in the dynamic control layer to fulfil the reference. An indirect and a direct distributed optimisation method are developed for the kinematic layer, both of which are computationally and communicationally efficient. In the dynamic control layer, impedance control is employed for safe physical interaction. As another highlight, abundant experiments carried out on a multi-arm test bench have demonstrated the effectiveness of the presented control schemes under various environmental and task settings. The recorded computation time shows the applicability of the control framework in practice.