The article presents an automated assembly station designed by students as part of Project Based Learning. The task of the project was to familiarize with the issues of integration of automation and control elements o...
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Electric vehicles(EVs)are widely deployed throughout the world,and photovoltaic(PV)charging stations have emerged for satisfying the charging demands of EV *** paper proposes a multi-objective optimal operation method...
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Electric vehicles(EVs)are widely deployed throughout the world,and photovoltaic(PV)charging stations have emerged for satisfying the charging demands of EV *** paper proposes a multi-objective optimal operation method for the centralized battery swap charging system(CBSCS),in order to enhance the economic efficiency while reducing its adverse effects on power *** proposed method involves a multi-objective optimization scheduling model,which minimizes the total operation cost and smoothes load fluctuations,***,we modify a recently proposed multi-objective optimization algorithm of non-sorting genetic algorithm III(NSGA-III)for solving this scheduling ***,simulation studies verify the effectiveness of the proposed multi-objective operation method.
A highly sensitive temperature sensing array is prepared by all laser direct writing(LDW)method,using laser induced silver(LIS)as electrodes and laser induced graphene(LIG)as temperature sensing layer.A finite element...
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A highly sensitive temperature sensing array is prepared by all laser direct writing(LDW)method,using laser induced silver(LIS)as electrodes and laser induced graphene(LIG)as temperature sensing layer.A finite element analysis(FEA)photothermal model incorporating a phase transition mechanism is developed to investigate the relationship between laser parameters and LIG properties,providing guidance for laser processing parameters selection with laser power of 1–5 W and laser scanning speed(greater than 50 mm/s).The deviation of simulation and experimental data for widths and thickness of LIG are less than 5%and 9%,*** electrical properties and temperature responsiveness of LIG are also *** changing the laser process parameters,the thickness of the LIG ablation grooves can be in the range of 30–120μm and the resistivity of LIG can be regulated within the range of 0.031–67.2Ω・*** percentage temperature coefficient of resistance(TCR)is calculated as−0.58%/°***,the FEA photothermal model is studied through experiments and simulations data regarding LIS,and the average deviation between experiment and simulation is less than 5%.The LIS sensing samples have a thickness of about 14μm,an electrical resistivity of 0.0001–100Ω・m is insensitive to temperature and pressure ***,for a LIS-LIG based temperature sensing array,a correction factor is introduced to compensate for the LIG temperature sensing being disturbed by pressure stimuli,the temperature measurement difference is decreased from 11.2 to 2.6°C,indicating good accuracy for temperature measurement.
This work introduces a method for closed-loop system identification using frequency analysis, employing Empirical Transfer Function Estimation (ETFE). By integrating optimization within a Monte Carlo framework, it enh...
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ISBN:
(数字)9798350373974
ISBN:
(纸本)9798350373981
This work introduces a method for closed-loop system identification using frequency analysis, employing Empirical Transfer Function Estimation (ETFE). By integrating optimization within a Monte Carlo framework, it enhances the precision of ETFE, resulting in minimized frequency response errors compared to actual system data. Leveraging controller information in an offline model fitting scheme, it achieves optimal realization of process dynamics. The method is evaluated on a data center rack-level cooling system, showing Bode magnitude plots of actual and estimated closed-loop and open-loop dynamics, with confidence intervals demonstrating algorithm consistency. Numerical evaluations confirm the feasibility and potential of the approach to improve offline closed-loop system identification performance in the frequency domain, beneficial for analysis and design. There will not be a comparative study for the introduced approach.
Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and ...
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Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, ***, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation ***, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.
This paper explores the impact of the burgeoning electric vehicle (EV) presence on distribution grid operations, highlighting the challenges they present to conventional pricing strategies due to their dual role as po...
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Small multirotors demonstrate significant potential due to their simple airframe and human-friendly operation. However, the reduced size results in substantially higher energy consumption, which severely limits their ...
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Small multirotors demonstrate significant potential due to their simple airframe and human-friendly operation. However, the reduced size results in substantially higher energy consumption, which severely limits their flight endurance and restricts their range of applications. Ornithopters, while offering better aerodynamic efficiency, experience energy losses due to the mechanical complexity required to generate reciprocating motion. In this work, inspired by the samara, we present a lightweight aircraft with an exceptionally simple design featuring a single actuator and a mono airfoil. To optimize the flight configuration for minimal power consumption, we employed a Surrogate optimization method that integrates spinning airfoil dynamics, motor-propeller efficiency, and hovering equilibrium. As a result, the proposed vehicle achieves position-controlled hovering flight for up to 26 minutes with a takeoff weight of only 32 grams. Its superior power efficiency is demonstrated by a high power loading of 9.1 grams per watt. Compared to state-of-the-art systems, the proposed design shows significant improvements in both flight endurance and power efficiency. The reliable and stable position-holding flight over an extended period further validates the effectiveness of the proposed methods and the practical applicability of the fabricated prototype.
In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based ...
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Although conventional false data injection attacks can circumvent the detection of bad data detection (BDD) in sustainable power grid cyber physical systems, they are easily detected by well-trained deep learning-base...
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With the increasing emphasis on embedding advanced technology into system controls, the Direct Power control (DPC) approach has garnered considerable attention due to its simple and highly adaptable algorithm. This ap...
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