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Fixed-time constrained acceleration reconstruction scheme for robotic exoskeleton via neural networks Research

Tao Xue, Zi-wei Wang, Tao Zhang, Ou Bai, Meng Zhang, Bin Han,taozhang@tsinghua.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 5,   Pages 649-808 doi: 10.1631/FITEE.1900418

Abstract: Accurate acceleration acquisition is a critical issue in the system, but it is difficult to directly obtain the acceleration via the existing sensing systems. The existing algorithm-based acceleration acquisition methods put more attention on finite-time convergence and disturbance suppression but ignore the error constraint and s. To this end, a novel radical bias function neural network (RBFNN) based fixed-time reconstruction scheme with error constraints is designed to realize high-performance acceleration estimation. In this scheme, a novel exponential-type is proposed to handle the error constraints. It also provides a unified and concise Lyapunov stability-proof template for constrained and non-constrained systems. Moreover, a fractional power sliding mode control law is designed to realize , where the convergence time is irrelevant to initial states or external disturbance, and depends only on the chosen parameters. To further enhance observer robustness, an RBFNN with the adaptive weight matrix is proposed to approximate and attenuate the completely unknown disturbances. Numerical simulation and human subject experimental results validate the unique properties and practical robustness.

Keywords： 加速度重构；固定时间收敛；约束控制；障碍李雅普诺夫函数；初始状态无关方法；外骨骼机器人    

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The Method and Formula for Stability Factor of Slope with State of Soil Original Stress

Wang Guoti

Strategic Study of CAE 2006, Volume 8, Issue 12,   Pages 80-84

Abstract:

The methods for analysis of stability of slope are usually considered, developed and improved along the line of finite slice method. But the safety factor of stability is facing challenge in engineering application. Because of the state of original stress in soil is ignored and disfigurement of finite slice method is in existence at all time. In different conditions of soil consolidation, K0, the lateral stress coefficient of soil state, has influenced the property of soil and excavation of slope. In this paper, in consideration of the state of soil original stress, the calculating formula for safety factor have been given with applying Coulomb's equation for shear strength of soil and Mohr - Coulomb rule. There are many examples of safety factor using the formula of this paper, which have been calculated and compared with finite slice methods selected from reference literatures. The formula have showed their clear concept, simple calculation and dependable result. They can be used in engineering.

Keywords： ateral stress coefficient K0     state of original stress     formula of safety factor of stability    

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A Laboratorial Method for Determining Incipient Yield Pressure of Thick Wall Cylinder

Zhang Yuxian’,Liao Zhenfang,Wang Hong ,Pei Jianghong

Strategic Study of CAE 2005, Volume 7, Issue 11,   Pages 72-75

Abstract:

Based on the relation between the incipient yield pressure and the limit of yielding in cylinder according to the elastic disabled rule, a laboratorial method of determining the incipient yield pressure is designed and a set of experimental data were gained. The incipient yield pressure of the cylinder is gained by analyzing the experimental data. The laboratorial method has a good reliability as the experimental value has a little error to the theory value.

Keywords： thick wall cylinder     disabled     incipient yield pressure    

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Theory and Method of Power System Integrated Security Region Irrelevant to Operation States: An Introduction Feature Article

Yixin Yu, Yanli Liu, Chao Qin, Tiankai Yang

Engineering 2020, Volume 6, Issue 7,   Pages 754-777 doi: 10.1016/j.eng.2019.11.016

Abstract:

How to comprehensively consider the power flow constraints and various stability constraints in a series of power system optimization problems without affecting the calculation speed is always a problem. The computational burden of probabilistic security assessment is even more unimaginable. In order to solve such problems, a security region (SR) methodology is proposed, which is a brand-new methodology developed on the basis of the classical point-wise method. Tianjin University has been studying the SR methodology since the 1980s, and has achieved a series of original breakthroughs that are described in this paper. The integrated SR introduced in this paper is mainly defined in the power injection space, and includes SRs to ensure steady-state security, transient stability, static voltage stability, and small disturbance stability. These SRs are uniquely determined for a given network topology (as well as location and clearing process for transient faults) and given system component parameters, and are irrelevant to operation states. This paper presents 11 facts and related remarks to introduce the basic concepts, composition, dynamics nature, and topological and geometric characteristics of SRs. It also provides a practical mathematical description of SR boundaries and fast calculation methods to determine them in a concise and systematic way. Thus, this article provides support for the systematic understanding, future research, and applications of SRs. The most critical finding on the topological and geometric characteristics of SRs is that, within the scope of engineering concern, the practical boundaries of SRs in the power injection space can be approximated by one or a few hyperplanes. Based on this finding, the calculation time for power system probabilistic security assessment (i.e., risk analysis) and power system optimization with security constraints can be decreased by orders of magnitude.

Keywords： Security region     Composition     Power flow security     Static voltage stability     Small-disturbance stability     Transient stability     Dynamics nature     Topological and geometric characteristics Hyperplane    

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Illuminating the new method process of slope stability analysis by soil stress state

Wang Guoti,Wang Wandi

Strategic Study of CAE 2010, Volume 12, Issue 1,   Pages 52-55

Abstract:

According to the soil stress state and calculation method of slope stability coefficient, and combined with soil properties, this paper illuminated basic assumption, formula derivation process and project application in detail. As the calculation formula of slope stability coefficient's theory analysis is rigorous, and the derived formula is correct, the project application is reliable. This paper will provide reference for relative project application and further research.

Keywords： slope stability analysis method     stress state     slope stability coefficient    

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A matrix-based static approach to analysis of finite state machines Research Article

He DENG, Yongyi YAN, Zengqiang CHEN,yyyan@mail.nankai.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 8,   Pages 1239-1246 doi: 10.1631/FITEE.2100561

Abstract: Traditional matrix-based approaches in the field of construct state transition matrices, and then use the powers of the state transition matrices to represent corresponding dynamic transition processes, which are cornerstones of system analysis. In this study, we propose a static matrix-based approach that revisits a finite state machine from its structure rather than its dynamic transition process, thus avoiding the "explosion of complexity" problem inherent in the existing approaches. Based on the static approach, we reexamine the issues of closed-loop detection and controllability for deterministic . In addition, we propose controllable equivalent form and minimal controllable equivalent form concepts and give corresponding algorithms.

Keywords： Logical systems     Finite-valued systems     Semi-tensor product of matrices     Finite state machines     Matrix approaches    

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Coherence analysis and Laplacian energy of recursive trees with controlled initial states Research Articles

Mei-du Hong, Wei-gang Sun, Su-yu Liu, Teng-fei Xuan,wgsun@hdu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 6,   Pages 809-962 doi: 10.1631/FITEE.1900133

Abstract: We study the of a family of recursive trees with novel features that include the initial states controlled by a parameter. The problem in a linear system with additive noises is characterized as , which is defined by a Laplacian spectrum. Based on the structures of our recursive treelike model, we obtain the recursive relationships for Laplacian eigenvalues in two successive steps and further derive the exact solutions of first- and second-order coherences, which are calculated by the sum and square sum of the reciprocal of all nonzero Laplacian eigenvalues. For a large network size , the scalings of the first- and second-order coherences are ln and $, respectively. The smaller the number of initial nodes, the better the bears. Finally, we numerically investigate the relationship between and , showing that the first- and second-order coherences increase with the increase of at approximately exponential and linear rates, respectively.

Keywords： 一致性；网络一致性；拉普拉斯能量    

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A Data and Knowledge Collaboration Strategy for Decision-Making on the Amount of Aluminum Fluoride Addition Based on Augmented Fuzzy Cognitive Maps Article

Weichao Yue、 Weihua Gui、 Xiaofang Chen、 Zhaohui Zeng、 Yongfang Xie

Engineering 2019, Volume 5, Issue 6,   Pages 1060-1076 doi: 10.1016/j.eng.2019.10.005

Abstract:

In the aluminum reduction process, aluminum fluoride (AlF3) is added to lower the liquidus temperature of the electrolyte and increase the electrolytic efficiency. Making the decision on the amount of AlF3 addition (referred to in this work as MDAAA) is a complex and knowledge-based task that must take into consideration a variety of interrelated functions; in practice, this decision-making step is performed manually. Due to technician subjectivity and the complexity of the aluminum reduction cell, it is difficult to guarantee the accuracy of MDAAA based on knowledge-driven or data-driven methods alone. Existing strategies for MDAAA have difficulty covering these complex causalities. In this work, a data and knowledge collaboration strategy for MDAAA based on augmented fuzzy cognitive maps (FCMs) is proposed. In the proposed strategy, the fuzzy rules are extracted by extended fuzzy k-means (EFKM) and fuzzy decision trees, which are used to amend the initial structure provided by experts. The state transition algorithm (STA) is introduced to detect weight matrices that lead the FCMs to desired steady states. This study then experimentally compares the proposed strategy with some existing research. The results of the comparison show that the speed of FCMs convergence into a stable region based on the STA using the proposed strategy is faster than when using the differential Hebbian learning (DHL), particle swarm optimization (PSO), or genetic algorithm (GA) strategies. In addition, the accuracy of MDAAA based on the proposed method is better than those based on other methods. Accordingly, this paper provides a feasible and effective strategy for MDAAA.

Keywords： AlF 3 addition     Fuzzy cognitive maps     Learning algorithms     State transition algorithm     Fuzzy decision trees    

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Study on evaluation method of weapon equipment readiness

Yu Xiang,Du Gang and He Qiwei

Strategic Study of CAE 2015, Volume 17, Issue 5,   Pages 76-82

Abstract:

Weapon equipment readiness evaluation is important for the meticulous and scientific usage management and maintenance support of weapon equipment. However， the current evaluation methods don’t fit the new situation and new requirements in terms of timeliness， accuracy and task matching. Therefore， an improved evaluation method for weapon equipment readiness based on the technical status of the main onboard machinery was presented. Through the simulation evaluation of the readiness for a certain type of destroyer， the feasibility of this method was verified， and some countermeasures and suggestions to further improve the method and mechanism for equipment readiness evaluation were proposed.

Keywords： equipment readiness；technical status；maintenance support of equipment；countermeasures    

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Multi-AUV SOM task allocation algorithm considering initial orientation and ocean current environment Special Feature on Intelligent Robats

Da-qi ZHU, Yun QU, Simon X. YANG

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 3,   Pages 330-341 doi: 10.1631/FITEE.1800562

Abstract:

There is an ocean current in the actual underwater working environment. An improved self-organizing neural network task allocation model of multiple autonomous underwater vehicles (AUVs) is proposed for a three-dimensional underwater workspace in the ocean current. Each AUV in the model will be competed, and the shortest path under an ocean current and different azimuths will be selected for task assignment and path planning while guaranteeing the least total consumption. First, the initial position and orientation of each AUV are determined. The velocity and azimuths of the constant ocean current are determined. Then the AUV task assignment problem in the constant ocean current environment is considered. The AUV that has the shortest path is selected for task assignment and path planning. Finally, to prove the effectiveness of the proposed method, simulation results are given.

Keywords： Autonomous underwater vehicles     Self-organizing neural networks     Azimuths     Ocean current    

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A Hierarchical-Based Initialization Method for K-Means Algorithm

Tang Jiubin,Lu Jianfeng,Tang Zhenmin, Yang Jingyu

Strategic Study of CAE 2007, Volume 9, Issue 11,   Pages 74-79

Abstract:

K-means algorithm is one of common clustering algorithms,  but the cluster center initialization is a hard problem.  In this paper,  a hierarchical-based initialization approach is proposed for K-Means algorithm.  The general clustering problem is treated as weighted clustering problem,  the original data is sampled level by level to reduce the data amount.  Then clustering is carried out at each level by top-down.  The initial center of each level is mapped from the clustering center of upper level and this procedure is repeated until the original data level is reached.  As a result,  the initial center for the original data is obtained.  Both the experimental results on simulated data and real data show that the proposed method has high converging speed,  high quality of clustering and is insensitive to noise,  which is superior to some existing clustering algorithms.

Keywords： hierarchical technique     initial cluster centers     weighted data     K-means clustering    

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Distribution system state estimation: an overview of recent developments Review Article

Gang WANG, Georgios B. GIANNAKIS, Jie CHEN, Jian SUN

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 1,   Pages 4-17 doi: 10.1631/FITEE.1800590

Abstract:

In the envisioned smart grid, high penetration of uncertain renewables, unpredictable participation of (industrial) customers, and purposeful manipulation of smart meter readings, all highlight the need for accurate, fast, and robust power system state estimation (PSSE). Nonetheless, most real-time data available in the current and upcoming transmission/distribution systems are nonlinear in power system states (i.e., nodal voltage phasors). Scalable approaches to dealing with PSSE tasks undergo a paradigm shift toward addressing the unique modeling and computational challenges associated with those nonlinear measurements. In this study, we provide a contemporary overview of PSSE and describe the current state of the art in the nonlinear weighted least-squares and least-absolutevalue PSSE. To benchmark the performance of unbiased estimators, the Cramér-Rao lower bound is developed. Accounting for cyber attacks, new corruption models are introduced, and robust PSSE approaches are outlined as well. Finally, distribution system state estimation is discussed along with its current challenges. Simulation tests corroborate the effectiveness of the developed algorithms as well as the practical merits of the theory.

Keywords： State estimation     Cramér-Rao bound     Feasible point pursuit     Semidefinite relaxation     Proximal linear algorithm     Composite optimization     Cyber attack     Bad data detection    

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Experimental research on the mixed sand ratio and initial dry density of weathered sand improved expansive soil free load swelling rate

Yang Jun,Yang Zhi,Zhang Guodong,Tang Yunwei and Chen Hongping

Strategic Study of CAE 2014, Volume 16, Issue 2,   Pages 73-78

Abstract:

Through the indoor free load swelling rate test，Yichang City，a section of a highway reconstruction project of expansive soil were studied. Key analysis free load swelling rate of a non-load time，the proportion of mixed sand，the relationship between the initial dry density， experimental studies have shown that：Free load swelling rate is mainly divided into rapid expansion，slow expansion and eventually stabilize in three stages；during the initial dry density is constant，weathered sand soil free load swelling rate will increase the proportion of sand mixed with the rapid decrease slowly after the first lower，weathered sand soil modified free load swelling rate is not sensitive to the amount of sand mixed；in the same mixed sand ratio， weathered sand soil free load swelling rate increases with increasing initial dry density increases rapidly between them have a good linear correlation，expansive soil subgrade construction in progress when control of the initial dry density，to help reduce its swelling deformation，ensuring the stability of embankment.

Keywords： expansive soils     weathered sand     initial dry density     mixing sand ratio     free load swelling rate    

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Visual interactive image clustering: a target-independent approach for configuration optimization in machine vision measurement Research Article

Lvhan PAN, Guodao SUN, Baofeng CHANG, Wang XIA, Qi JIANG, Jingwei TANG, Ronghua LIANG

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 3,   Pages 355-372 doi: 10.1631/FITEE.2200547

Abstract: (MVM) is an essential approach that measures the area or length of a target efficiently and non-destructively for product quality control. The result of MVM is determined by its configuration, especially the in image acquisition and the algorithmic in image processing. In a traditional workflow, engineers constantly adjust and verify the configuration for an acceptable result, which is time-consuming and significantly depends on expertise. To address these challenges, we propose a target-independent approach, , which facilitates configuration optimization by grouping images into different clusters to suggest lighting schemes with common parameters. Our approach has four steps: data preparation, data sampling, data processing, and visual analysis with our visualization system. During preparation, engineers design several candidate lighting schemes to acquire images and develop an algorithm to process images. Our approach samples engineer-defined parameters for each image and obtains results by executing the algorithm. The core of data processing is the explainable measurement of the relationships among images using the algorithmic parameters. Based on the image relationships, we develop VMExplorer, a visual analytics system that assists engineers in grouping images into clusters and exploring parameters. Finally, engineers can determine an appropriate lighting scheme with robust parameter combinations. To demonstrate the effectiveness and usability of our approach, we conduct a case study with engineers and obtain feedback from expert interviews.

Keywords： Machine vision measurement     Lighting scheme design     Parameter optimization     Visual interactive image clustering    

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Initial position estimation strategy for a surface permanent magnet synchronous motor used in hybrid electric vehicles Article

Bing TIAN,Qun-tao AN,Li SUN,Dong-yang SUN,Jian-dong DUAN

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 8,   Pages 803-813 doi: 10.1631/FITEE.1500298

Abstract: A novel nonlinear model for surface permanent magnet synchronous motors (SPMSMs) is adopted to estimate the initial rotor position for hybrid electric vehicles (HEVs). Usually, the accuracy of initial rotor position estimation for SPMSMs relies on magnetic saturation. To verify the saturation effect, the transient finite element analysis (FEA) model is presented first. Hybrid injection of a static voltage vector (SVV) superimposed with a high-frequency rotating voltage is proposed. The magnetic polarity is roughly identified with the aid of the saturation evaluation function, based on which an estimation of the position is performed. During this procedure, a special demodulation is suggested to extract signals of iron core saturation and rotor position. A Simulink/MATLAB platform for SPMSMs at standstill is constituted, and the effectiveness of the proposed strategy is verified. The proposed method is also validated by experimental results of an SPMSM drive.

Keywords： Surface permanent magnet synchronous motor (SPMSM)     Initial position estimation     Nonlinear model     Hybrid injection     Position observer    

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Title Author Date Type Operation

Fixed-time constrained acceleration reconstruction scheme for robotic exoskeleton via neural networks

Tao Xue, Zi-wei Wang, Tao Zhang, Ou Bai, Meng Zhang, Bin Han,taozhang@tsinghua.edu.cn

Journal Article

The Method and Formula for Stability Factor of Slope with State of Soil Original Stress

Wang Guoti

Journal Article

A Laboratorial Method for Determining Incipient Yield Pressure of Thick Wall Cylinder

Zhang Yuxian’,Liao Zhenfang,Wang Hong ,Pei Jianghong

Journal Article

Theory and Method of Power System Integrated Security Region Irrelevant to Operation States: An Introduction

Yixin Yu, Yanli Liu, Chao Qin, Tiankai Yang

Journal Article

Illuminating the new method process of slope stability analysis by soil stress state

Wang Guoti,Wang Wandi

Journal Article

A matrix-based static approach to analysis of finite state machines

He DENG, Yongyi YAN, Zengqiang CHEN,yyyan@mail.nankai.edu.cn

Journal Article

Coherence analysis and Laplacian energy of recursive trees with controlled initial states

Mei-du Hong, Wei-gang Sun, Su-yu Liu, Teng-fei Xuan,wgsun@hdu.edu.cn

Journal Article

A Data and Knowledge Collaboration Strategy for Decision-Making on the Amount of Aluminum Fluoride Addition Based on Augmented Fuzzy Cognitive Maps

Weichao Yue、 Weihua Gui、 Xiaofang Chen、 Zhaohui Zeng、 Yongfang Xie

Journal Article

Study on evaluation method of weapon equipment readiness

Yu Xiang,Du Gang and He Qiwei

Journal Article

Multi-AUV SOM task allocation algorithm considering initial orientation and ocean current environment

Da-qi ZHU, Yun QU, Simon X. YANG

Journal Article

A Hierarchical-Based Initialization Method for K-Means Algorithm

Tang Jiubin,Lu Jianfeng,Tang Zhenmin, Yang Jingyu

Journal Article

Distribution system state estimation: an overview of recent developments

Gang WANG, Georgios B. GIANNAKIS, Jie CHEN, Jian SUN

Journal Article

Experimental research on the mixed sand ratio and initial dry density of weathered sand improved expansive soil free load swelling rate

Yang Jun,Yang Zhi,Zhang Guodong,Tang Yunwei and Chen Hongping

Journal Article

Visual interactive image clustering: a target-independent approach for configuration optimization in machine vision measurement

Lvhan PAN, Guodao SUN, Baofeng CHANG, Wang XIA, Qi JIANG, Jingwei TANG, Ronghua LIANG

Journal Article

Initial position estimation strategy for a surface permanent magnet synchronous motor used in hybrid electric vehicles

Bing TIAN,Qun-tao AN,Li SUN,Dong-yang SUN,Jian-dong DUAN

Journal Article