In this paper, a classical PI and an on/off predictive boundary-based predictive controller (BBPC) algorithms are compared and verified using an ASM3-based model of an activated sludge system with a reactor and second...
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Enabling aerial robots to handle dynamic contacts happening at non-vanishing speeds can enlarge the range of their applications. In this work, we propose an impactaware strategy to allow aerial multirotor robots to re...
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ISBN:
(数字)9798331513283
ISBN:
(纸本)9798331513290
Enabling aerial robots to handle dynamic contacts happening at non-vanishing speeds can enlarge the range of their applications. In this work, we propose an impactaware strategy to allow aerial multirotor robots to recover from impacts. The method leverages a reactive strategy not requiring low-level changes to the motion controller commonly implemented onboard quadrotors, which might be not viable or not desirable for most users. Extensive simulation tests show that the proposed strategy considerably increases the tolerated velocity at impact in tasks in which the robot either picks an object up or collides against an object to clear its way. Preliminary experimental results using Crazyflie UAVs are also presented.
In this paper, we present a novel visual servoing (VS) approach based on latent Denoising Diffusion Probabilistic Models (DDPMs), that explores the application of generative models for vision-based navigation of UAVs ...
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ISBN:
(数字)9798331513283
ISBN:
(纸本)9798331513290
In this paper, we present a novel visual servoing (VS) approach based on latent Denoising Diffusion Probabilistic Models (DDPMs), that explores the application of generative models for vision-based navigation of UAVs (Uncrewed Aerial Vehicles). Opposite to classical VS methods, the proposed approach allows reaching the desired target view, even when the target is initially not visible. This is possible thanks to the learning of a latent representation that the DDPM uses for planning and a dataset of trajectories encompassing target-invisible initial views. A compact representation is learned from raw images using a Cross-Modal Variational Autoencoder. Given the current image, the DDPM generates trajectories in the latent space driving the robotic platform to the desired visual target. The approach has been validated in simulation using two generic multi-rotor UAVs (a quadrotor and a hexarotor). The results show that we can successfully reach the visual target, even if not visible in the initial view. A video summary with simulations can be found in: https://***/2Hb3nkkcszE.
Food contact materials (FCMs) may be responsible for migration of contaminants into food, especially during heating. This article describes the effect of electromagnetic microwaves used to heat food on the migration o...
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Information, such as reliable demand and generation forecasts is crucial for appropriate energy management in microgrids. However, the most valuable data is the aggregate energy flow in the managed network, rather tha...
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During the last two decades, interest in grid integrated renewable energy sources (RERs) into the electrical power grids has significantly grown. The motive being a promising strategy to reduce greenhouse gas emission...
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ISBN:
(数字)9798331527495
ISBN:
(纸本)9798331527501
During the last two decades, interest in grid integrated renewable energy sources (RERs) into the electrical power grids has significantly grown. The motive being a promising strategy to reduce greenhouse gas emissions generated by conventional power plants (CPPs) and hence environmental consequences, decrease losses in distribution lines to improve power system supply efficiency and reliability to consumers. As a result, several CPPs are being replaced by RERs such as solar PV system, wind energy, micro hydro-turbine, fuel cell, and small gas power plants. These are installed close to customers on low-voltage and medium-voltage sites to reduce losses in the network and improve power quality, overall efficiency and reliability. However, grid-connected RERs via inverter decreases system inertia due to decrease in CPPs with rotating mass serving as an immediate natural response to frequency deviations following network disturbances. Therefore, this paper presents the design of dynamic virtual-inertia control (DVIC) scheme. The developed DVIC incorporates the mechanism to adjust active and reactive demand in response to any frequency and voltage variations to ensure system stability. To validate the suitability of the presented technique, MATLAB/Simulink model is developed and simulated under various operating scenarios. Using the results obtained simulation study, it is evidently the proposed DVIC shows improved performance is achieved than when no inertia control system applied.
This article proposes a new sliding mode control (NSMC) reaching law to improve the speed tracking and anti-interference performance of permanent magnet synchronous motors (PMSMs). The NSMC improves the sliding mode c...
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To simultaneously suppress the periodic and aperiodic disturbances experienced by permanent magnet synchronous motors in model predictive control, a model-free predictive current control with adaptive resonance contro...
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In motion control applications, the precise regulation of Industrial Hydraulic Actuators (IHA) is essential for properly ascertaining the position of the actuator rod. This research used a Hammerstein-Wiener (HW) mode...
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Switched reluctance motors (SRMs) are capable of operating at high speeds and high loads. However, the large back-EMF results in the excitation winding current being demagnetized more slowly, which in turn reduces the...
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