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The given data contains the results from laboratory trials related to the paper "Optimizing Congestion Management andEnhancing Resilience in Low-Voltage Grids Using OPF and MPC Control Algorithms Through Edge Computing and IEC 61850 Standards" currently in publication in IEEE Access.
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74 Views
This is an IMU dataset of human arm motions.
Users wear a smart watch that is equipped with IMU sensors.
A VR controller is attached to a smart watch to provide orientation and location ground truth.
The orientation and location ground truth is accurately calibrated using techniques proposed in 'Real-time tracking of smartwatch orientation and location by multitask learning'.
This dataset contains magnetic distortion feature in many data traces, which means the magnetic field does not always point to the same direction (i.e., north) in global reference.
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137 Views
The robot arm system with no or low-accuracy Lagrange dynamic identification is a typical unknown-structure MIMO coupled system. It is difficult to achieve fast-convergence and high-accuracy control for this practical system, especially with no empirical pre-adjustment of the initial input direction. To solve this practical problem, a novel prescribed finite-time nondirectional AT-S fuzzy control method is proposed.
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114 Views
Smart grids today are characterized by the integration of distributed energy resources, including renewable energy sources, traditional power sources, and storage systems. These components typically employ various control technologies that interface with generators through smart inverters, making them susceptible to numerous cyber threats. To address this vulnerability, there is a crucial need for datasets that document attacks on these systems, enabling risk evaluation and the development of effective monitoring algorithms. This dataset
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312 Views
Developing mind-controlled prosthetics that seamlessly integrate with the human nervous system is a significant challenge in the field of bioengineering. This project investigates the use of labelled brainwave patterns to control a bionic arm equipped with a sense of touch. The core objective is to establish a communication channel between the brain and the artificial limb, enabling intuitive and natural control while incorporating sensory feedback.
The project involves:
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528 Views
Energy-storage-equipped static synchronous compensators (E-STATCOM) are crucial devices in a modern
power grid to regulate both the active and reactive power, thereby improving the efficiency and power
quality. Current controllers commonly used with E-STATCOM devices include proportional-integral (PI),
repetitive, and deadbeat controllers. However, each has application-dependent restrictions and therefore lack
the ability to achieve optimal operation. This paper presents a novel hybrid current controller that combines
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246 Views
The dataset encompasses a diverse array of electrical signals representing Power Quality Disturbances (PQD), both in single and combined forms, meticulously generated in adherence to the IEEE 1159 guideline. Crucially, the dataset includes both raw data and corresponding labels, facilitating supervised learning tasks and enabling the development and evaluation of classification algorithms.
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1146 Views
The dataset contains 5G positioning measurements simulated using a MATLAB raytracer tool in realistic environments (outdoors and indoors).
Outdoor scenarios include static and dynamic users in the urban area of Città Studi, Milan, Italy, near the Politecnico di Milano - Campus Leonardo.
The indoor context is reconstructed using a LiDAR acquisition in the MADE Competence Center I4.0 located in Politecnico di Milano - Campus Durandò, Bovisa, Milan, Italy.
The datasets include:
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150 Views
we propose a novel Non-Line-of-Sight (NLOS) identification and error-mitigation method for dynamic object positioning and ultra-wideband (UWB) ranging. By applying inverse estimation on known Anchor Points (Aps) and improved unscented Kalman filter (IRUKF), the proposed technology identifies and compensates for NLOS occlusions between tag and APs, reducing positioning errors. The approach has been verified through simulation and experiment, with identification precision of 97.02%.
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324 Views
Electromyography (EMG) has limitations in human machine interface due to disturbances like electrode-shift, fatigue, and subject variability. A potential solution to prevent model degradation is to combine multi-modal data such as EMG and electroencephalography (EEG). This study presents an EMG-EEG dataset for enhancing the development of upper-limb assistive rehabilitation devices. The dataset, acquired from thirty-three volunteers without neuromuscular dysfunction or disease using commercial biosensors is easily replicable and deployable.
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1923 Views