检索结果-南通市图书馆

Prescribed Performance Evolution Control for Quadrotor Autonomous Shipboard Landing

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1151-1162页

作者： Yang Yuan Haibin Duan Zhigang Zeng State Key Laboratory of Virtual Reality Technology and Systems the School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083China State Key Laboratory of Virtual Reality Technology and Systems the School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083 Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China school of Artificial Intelligence and automation Huazhong University of Science and TechnologyWuhan 430074China

The shipboard landing problem for a quadrotor is addressed in this paper,where the ship trajectory tracking control issue is transformed into a stabilization control issue by building a relative position model.To guarantee both transient performance and steady-state landing error,a prescribed performance evolution control(PPEC)method is developed for the relative position control.In addition,a novel compensation system is proposed to expand the performance boundaries when the input saturation occurs and the error exceeds the predefined threshold.Considering the wind and wave on the relative position model,an adaptive sliding mode observer(ASMO)is designed for the disturbance with unknown upper bound.Based on the dynamic surface control framework,a shipboard landing controller integrating PPEC and ASMO is established for the quadrotor,and the relative position control error is guaranteed to be uniformly ultimately bounded.Simulation results have verified the feasibility and effectiveness of the proposed shipboard landing control scheme.

关键词： error integrating stabilization

KnowledgeMapping of Hybrid Solar PV andWind Energy Standalone Systems: A Bibliometric Analysis

维普期刊数据库

同方期刊数据库博看期刊评论

在线全文

学校读者我要写书评

暂无评论

Energy engineering 2024年第7期121卷 1781-1803页

作者： Quan Zhou Haiyang Li school of mechanical and electrical engineering Central South University of Forestry and TechnologyChangsha410004China

Renewable energy is becoming more attractive as traditional fossil fuels are rapidly depleted and expensive,and their use would release pollutants.Power systems that use both wind and solar energy are more reliable and efficient than those that utilize only one energy.Hybrid renewable energy systems(HRES)are viable for remote areas operating in standalone mode.This paper aims to present the state-of-the-art research on off-grid solar-wind hybrid energy systems over the last two decades.More than 1500 published articles extracted from the Web of Science are analyzed by bibliometric methods and processed by CiteSpace to present the results with figures and tables.Productive countries and highly cited authors are identified,and hot topics with hotspot articles are shown in landscape and timeline views.Emerging trends and new developments related to techno-economic analysis and microgrids,as well as the application of HOMER software,are predicted based on the analysis of citation bursts.Furthermore,the opportunities of hybrid energy systems for sustainable development are discussed,and challenges and possible solutions are proposed.The study of this paper provides researchers with a comprehensive understanding and intuitive representation of standalone solar-wind hybrid energy systems.

关键词： Wind energy solar PV standalone citation bursts emerging trends

Simulation and analysis of soil homogenization drills based on discrete element method and response surface methodology

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Particuology 2024年第5期88卷 128-148页

作者： Zhipeng Wang Tong Zhu Youzhao Wang Song Yang Feng Ma Xu Li Institute of Process Equipment and Environmental engineering School of Mechanical Engineering and AutomationNortheastern UniversityShenyang110819China Liaoning Coning Testing Co. Ltd.Shenyang110170 China

Currently,rotary drilling is one of the main pieces of equipment used for in-situ remediation of contaminated soil.However,this equipment has problems such as uneven mixing and low utilization efficiency,which affect the efficiency of in-situ soil remediation.To improve the efficiency of in-situ soil remediation,this paper takes contaminated black soil as the research object,and the structural design of the new three-stage soil remediation auger is carried out based on SolidWorks.The mixing process of soil and heavy metal passivator under different motion and structural parameters was investigated by the discrete element method(DEM)and response surface methodology.The experimental design was based on rotational speed,homogenizing mixing time,crushing section pitch,and homogenizing section pitch as factors,and soil fragmentation ratio,the coefficient of dispersion,and torque as optimization indices.The kinematic and structural parameters of the three-stage auger drill bit were then optimized using the one-factor method,the orthogonal test,and the response surface methodology,respectively.The test method uses a one-way test to determine the central level value of the orthogonal test and a comprehensive balance method to determine the best combination of parameters for the orthogonal test,which is then used as the central value of the response surface test for parameter optimization.The optimal combinations of kinematic and structural parameters of the three-stage auger drill bit are determined and validated using response surface methodology.The optimum combination of parameters was found to be a speed of 129 rpm,a homogenizing mixing time of 24 s,a pitch of 165 mm in the crushing section,and a pitch of 132 mm in the homogenizing section.The error between the optimal value of the predicted model using the response surface method and the actual simulated value under the optimal parameters is 4.2%,4.9%,and 5.3%,respectively.The optimized factor parameters provide a reference for the design of the structural and kinem

关键词： Black soil Mixing homogeneity Orthogonal method Response surface methodology Discrete element method Soil remediation

Electricity Theft Detection Method Based on Ensemble Learning and Prototype Learning

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 213-224页

作者： Xinwu Sun Jiaxiang Hu Zhenyuan Zhang Di Cao Qi Huang Zhe Chen Weihao Hu the school of mechanical and electrical engineering University of Electronic Science and Technology of ChinaChengduChina Southwest University of Science and TechnologyChengduChina

With the development of advanced metering infrastructure(AMI),large amounts of electricity consumption data can be collected for electricity theft detection.However,the imbalance of electricity consumption data is violent,which makes the training of detection model challenging.In this case,this paper proposes an electricity theft detection method based on ensemble learning and prototype learning,which has great performance on imbalanced dataset and abnormal data with different abnormal level.In this paper,convolutional neural network(CNN)and long short-term memory(LSTM)are employed to obtain abstract feature from electricity consumption data.After calculating the means of the abstract feature,the prototype per class is obtained,which is used to predict the labels of unknown samples.In the meanwhile,through training the network by different balanced subsets of training set,the prototype is representative.Compared with some mainstream methods including CNN,random forest(RF)and so on,the proposed method has been proved to effectively deal with the electricity theft detection when abnormal data only account for 2.5%and 1.25%of normal data.The results show that the proposed method outperforms other state-of-the-art methods.

关键词： Electricity theft detection ensemble learning prototype learning imbalanced dataset deep learning abnormal level

Comparison of brain functions between healthy participants and methamphetamine users with various addiction histories:Data analysis based on EEG and fNIRS

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Journal of Innovative Optical Health Sciences 2024年第3期17卷 41-55页

作者： Xuelin Gu Xiaoou Li Banghua Yang College of Medical Instruments Shanghai University of Medicine&Health SciencesShanghai 201318P.R.China school of mechanical and electrical engineering and automation Shanghai UniversityShanghai 200444P.R.China

The electroencephalogram(EEG)rhythm and functional near-infrared spectroscopy(fNIRS)activation levels have not been compared between a healthy control group(HCG)and methamphetamine user group(MUG)with different addiction histories.This study used 64-electrode EEG and fNIRS to conduct an experiment that analyzed the resting and craving states.The EEG and fNIRS data of 56 participants were collected,including 14 healthy participants,14 methamphetamine users with an addiction history of 0.5–5 years,14 users with an addiction history of 5–10 years,and 14 users with an addiction history of 10–15 years.Isolated effective coherence(iCoh)within the brain network was used to process the EEG data.Statistical analysis was performed to compare differences in iCoh among the delta,theta,alpha,beta,and gamma bands and explore oxyhemoglobin activation levels in the ventrolateral prefrontal cortex,dorsolateral prefrontal cortex,orbitofrontal cortex,and frontopolar prefrontal cortex(FPC)of the control group.Finally,the Kmeans,Gaussian mixed model(GMM),linear discriminant analysis(LDA),support vector machine(SVM),Bayes,and convolutional neural networks(CNN)algorithms were used to classify methamphetamine users based on drug and neutral images.A 3-class accuracy was achieved.Changes in EEG and fNIRS activation levels of HCG and MUG with varied addiction histories were demonstrated.

关键词： Drug addiction history electroencephalogram functional near-infrared spectroscopy isolated effective coherence addiction history classification

Observer design and interval estimation of time-delay discrete-time linear systems with external disturbance and measurement noise

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Control Theory and Technology 2024年第1期22卷 69-80页

作者： Junqi Yang Jianhao Xie Feiyang Liu school of electrical engineering and automation Henan Key Laboratory of Intelligent Detection and Control of Coal Mine EquipmentHenan Polytechnic UniversityJiaozuo454003HenanChina

For a class of time-delay discrete-time linear systems with external disturbance and measurement noise, the interval estimation problems of state and measurement noise are investigated in this paper. First, the system state together with the time-delay term and measurement noise is augmented as a new state, and a singular system is then constructed. Subsequently, a kind of decoupling technique is employed to eliminate the effect of external disturbance, and an observer is designed to simultaneously estimate the system state and measurement noise. Based on the estimated state and measurement noise, the interval estimations of system state and measurement noise are obtained by reachability analysis technique. Finally, the effectiveness of the proposed method is verified by a four-tank liquid level system.

关键词： Interval estimation Time-delay system Observer design Reachability analysis

Non-contact and full-field online monitoring of curing temperature during the in-situ heating process based on deep learning

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Advances in Manufacturing 2024年第1期12卷 167-176页

作者： Qiang-Qiang Liu Shu-Ting Liu Ying-Guang Li Xu Liu Xiao-Zhong Hao College of mechanical and electrical engineering Nanjing University of Aeronautics and AstronauticsNanjing210016People’s Republic of China school of mechanical and Power engineering Nanjing Tech UniversityNanjing211816People’s Republic of China

Online monitoring of the curing temperature field is essential to improving the quality and efficiency of the manufacturing process of composite parts.Traditional embedded sensor-based technologies have difficulty monitoring the full temperature field or have to introduce heterogeneous items that could have an undesired impact on the part.In this paper,a non-contact,full-field monitoring method based on deep learning that predicts the internal temperature field of composite parts in real time using surface temperature measurements of auxiliary materials is proposed.Using the proposed method,an average temperature monitoring accuracy of 97%is achieved in various heating patterns.In addition,this method also demonstrates satisfying feasibility when a stronger thermal barrier covers the part.This method was experimentally validated during the self-resistance electric heating process,in which the monitoring accuracy reached 93.1%.This method can potentially be applied to automated manufacturing and process control in the composites industry.

关键词： Online monitoring Curing temperature field Deep learning(DL) In-situ heating

Research of caged dynamics of clusters center atoms in Pd_(82)Si_(18) amorphous alloy

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese Physics B 2024年第4期33卷 623-629页

作者：邓永和陈贝祁清华李兵兵高明文大东王小云彭平 school of Computational Science and Electronics Hunan Institute of EngineeringXiangtan 411104China school of Physics and mechanical&electrical engineering Jishou UniversityJishou 416000China school of Materials Science and engineering Hunan UniversityChangsha 410082China

To date,there is still a lack of a comprehensive explanation for caged dynamics which is regarded as one of the intricate dynamic behaviors in amorphous alloys.This study focuses on Pd_(82)Si_(18)as the research object to further elucidate the underlying mechanism of caged dynamics from multiple perspectives,including the cage's lifetime,atomic local environment,and atomic potential energy.The results reveal that Si atoms exhibit a pronounced cage effect due to the hindrance of Pd atoms,resulting in an anomalous peak in the non-Gaussian parameters.An in-depth investigation was conducted on the caged dynamics differences between fast and slow Si atoms.In comparison to fast Si atoms,slow Si atoms were surrounded by more Pd atoms and occupied lower potential energy states,resulting in smaller diffusion displacements for the slow Si atoms.Concurrently,slow Si atoms tend to be in the centers of smaller clusters with coordination numbers of 9 and 10.During the isothermal relaxation process,clusters with coordination numbers 9 and 10 have longer lifetimes,suggesting that the escape of slow Si atoms from their cages is more challenging.The findings mentioned above hold significant implications for understanding the caged dynamics.

关键词： caged dynamics Pd_(82)Si_(18) amorphous alloy fast and slow atoms clusters lifetime

Prediction and Output Estimation of Pattern Moving in Non-Newtonian mechanical Systems Based on Probability Density Evolution

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Computer Modeling in engineering & Sciences 2024年第4期139卷 515-536页

作者： Cheng Han Zhengguang Xu school of automation and electrical engineering University of Science and Technology BeijingBeijing100083China Key Laboratory of Knowledge automation for Industrial Processes University of Science and Technology BeijingBeijing100083China

A prediction framework based on the evolution of pattern motion probability density is proposed for the output prediction and estimation problem of non-Newtonian mechanical systems,assuming that the system satisfies the generalized Lipschitz condition.As a complex nonlinear system primarily governed by statistical laws rather than Newtonian mechanics,the output of non-Newtonian mechanics systems is difficult to describe through deterministic variables such as state variables,which poses difficulties in predicting and estimating the system’s output.In this article,the temporal variation of the system is described by constructing pattern category variables,which are non-deterministic variables.Since pattern category variables have statistical attributes but not operational attributes,operational attributes are assigned to them by posterior probability density,and a method for analyzing their motion laws using probability density evolution is proposed.Furthermore,a data-driven form of pattern motion probabilistic density evolution prediction method is designed by combining pseudo partial derivative(PPD),achieving prediction of the probability density satisfying the system’s output uncertainty.Based on this,the final prediction estimation of the system’s output value is realized by minimum variance unbiased estimation.Finally,a corresponding PPD estimation algorithm is designed using an extended state observer(ESO)to estimate the parameters to be estimated in the proposed prediction method.The effectiveness of the parameter estimation algorithm and prediction method is demonstrated through theoretical analysis,and the accuracy of the algorithm is verified by two numerical simulation examples.

关键词： Non-newtonian mechanical systems prediction and estimation pattern moving probability density evolution pseudo partial derivative