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Extraction of affine invariant features for shape recognition based on ant colony optimization

Journal of systems Engineering and Electronics 2011年第6期22卷 1003-1009页

作者： Yuxing Mao Ching Y. Suen Wei He State Key Laboratory of Power Transmission Equipment ＆ System Security and New Technology Chongqing University Chongqing 400044 E R. China Centre for Pattern Recognition and Machine Intelligence Concordia University Montreal QC H3G 1M8 Canada

A new approach to extraction of affine invariant features of contour image and matching strategy is proposed for shape ***,the centroid distance and azimuth angle of each boundary point are ***,with a prior-defined angle interval,all the points in the neighbor region of the sample point are considered to calculate the average distance for eliminating *** that,the centroid distance ratios（CDRs） of any two opposite contour points to the barycenter are achieved as the representation of the shape,which will be invariant to affine *** the angles of contour points will change non-linearly among affine related images,the CDRs should be resampled and combined sequentially to build one-by-one matching pairs of the corresponding *** core issue is how to determine the angle positions for sampling,which can be regarded as an optimization problem of path *** ant colony optimization（ACO）-based path planning model with some constraints is presented to address this ***,the Euclidean distance is adopted to evaluate the similarity of shape features in different *** experimental results demonstrate the efficiency of the proposed method in shape recognition with translation,scaling,rotation and distortion.

关键词： shape recognition affine transformation centroid distance ratio(CDR) ant colony optimization(ACO) path planning.

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Boosting Explore-Exploit Behavior for Navigating Vehicle by Maintaining Informative Topological Frontier

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-11页

作者： Liu, Qiming Cui, Xinru Liu, Zhe Wang, Hesheng Department of Automation Shanghai Jiao Tong University Shanghai China MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

Target search in unknown environments places high demands not only on an autonomous vehicle's ability to perceive and interpret target cues, but also on its conscious of collecting these cues by active exploration. While existing navigation methods have successfully built target-driven policies by maintaining memory of explored areas, there has been a lack of focus on facilitating target-aware exploration-the informative frontier information at unexplored yet visible areas is often overlooked. In this paper, we introduce a novel topology-based memory structure, Frontier-enhanced Topological Memory (FTM), and a Hierarchical Topology Encoding and Extraction (HTEE) module, fostering the autonomous vehicle's awareness of both environmental exploration and target approach. Specifically, FTM innovatively incorporates informative ghost nodes on traditional topological map to represent unexplored yet visible regions. We leverage an online-trained implicit scene representation to estimate the positions and generate features of these ghost nodes. The HTEE then employs implicit graph convolutions and attention mechanisms to extract cognitive information from FTM, taking into account the hierarchical memory structure, target cues, and current state. Our design bolsters cognitive navigation decisions. The experiments in the high-fidelity environments, including performance tests, visualizations, and interpretability experiments, validate the effectiveness of our approach in enhancing the vehicle's exploratory behavior. The improved exploration awareness for target cue collection, in turn, enhances the success rate and path efficiency of target search. Furthermore, we demonstrate the adaptability of our algorithm in real-world physical environments. IEEE

关键词： Data mining

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Phantom motion intent decoding for transhumeral prosthesis control with fused neuromuscular and brain wave signals

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IET Cyber-systems and Robotics 2021年第1期3卷 77-88页

作者： Ejay Nsugbe Oluwarotimi Williams Samuel Mojisola Grace Asogbon Guanglin Li Independent Researcher Chinese Academy of Sciences(CAS)Key Laboratory of Human-Machine Intelligence-Synergy System Shenzhen Institutes of Advanced TechnologyShenzhenChina Shenzhen College of Advanced Technology University of Chinese Academy of SciencesShenzhenChina

In recent years,the electroencephalography(EEG)brain-computer interface(BCI)has been researched in the area of upper-limb prosthesis control due to the promise of being able to record neurological signals which follow activation patterns in the cortex directly from the brain with non-invasive *** is seen as a way of bypassing the limitation posed by acquiring neuromuscular signals predominantly with electromyography(EMG)directly from the stump,which possesses residual limb anatomy *** this study,the sequential forward selection algorithm to form a 10-optimal-channel representation,alongside an extended signal feature vector was applied,to investigate the motion intent decoding performance of EMG-only,EEG-only,and a fused EMG-EEG sensing configuration for four transhumeral amputees with varying stump *** results showed a considerable improvement for the EMG-only configuration with the advanced feature vector,but only a small increase for the EEG-only,and thus a marginal improvement when information from both signals was fused *** is likely due to the EEG requiring a greater number of channels spread across the skull to provide a reliable intent *** work will now involve optimisation studies to find a greater representation of electrode representation and parsimony,to minimise the number of channels while boosting motion intent decoding accuracy.

关键词： anatomy fused motion

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Resilient control of flexible hypersonic vehicles against unmatched distributed faults

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Chinese Journal of Aeronautics 2024年第5期37卷 60-70页

作者： Dong ZHAO Wenjing REN School of Artificial Intelligence Anhui UniversityHefei 230601China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China School of Electrical Engineering and Automation Hefei University of TechnologyHefei 230009China

This paper studies a robust fault compensation and vibration suppression problem of flexible hypersonic *** controlled plant is represented by a cascade system composed of a nonlinear Ordinary Differential Equation(ODE)and an Euler-Bernoulli Beam Equation(EBBE),in which the vibration dynamics is coupled with the rigid dynamics and suffers from distributed faults.A state differential transformation is introduced to transfer distributed faults to an EBBE boundary and a longitudinal dynamics is refined by utilizing T-S fuzzy IF-THEN rules.A novel T-S fuzzy based fault-tolerant control algorithm is developed and related stability conditions are *** robust exponential stability and well-posedness are proved by using the modified l_(0)-semigroup based Lyapunov direct approach.A simulation study on the longitudinal dynamics of flexible hypersonic vehicles effectively verifies the validity of the developed theoretical results.

关键词： Flexible hypersonic vehicles ODE-EBBE cascade Robust exponential stability Unmatched distributed fault compensation Vibration suppression

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Self-alignment for strapdown INS using real-time adaptive filter 7

Self-alignment for strapdown INS using real-time adaptive fi...

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7th IEEE Chinese Guidance, Navigation and control Conference, CGNCC 2016

作者： Jian, Zhao Fu-Jun, Pei Hong-Yun, Liu Beijing Key Laboratory of Computational Intelligence and Intelligent System School of Electronic Information and Control Engineering Beijing University of Technology 100124 China

ISBN: (纸本)9781467383189

As it is difficult to get an accurate mathematical noise model under various dynamic interference conditions, Strap-down Inertial Navigation system (SINS) was difficult to realize self-alignment. Although the fuzzy adaptive Kalman filter can be used to realize the SINS self-alignment, the algorithm complexity is high and the error term is unstable. To solve this problem, a novel self-alignment method using real-time adaptive filter was developed in this paper. This method is based on the theory of fuzzy adaptive adjustment and used the filter stability as the criterion. The exponential function was used to replace the fuzzy inference calculation, which eliminated the complex process of fuzzy, fuzzy inference and de-fuzzy. The stability and accuracy of the adaptive filter was also improved. Finally, the simulation process was used to test the algorithm of this method, and the results demonstrated that the self-alignment using real-time adaptive filter method reduced the complexity of the algorithm and had better stability and alignment accuracy. © 2016 IEEE.

关键词： Adaptive filters

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An improved NSGA2 algorithm with the adaptive differential mutation operator 34

An improved NSGA2 algorithm with the adaptive differential m...

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34th Chinese control Conference, CCC 2015

作者： Wei, Jing Qiao, Junfei Qinchao, Meng College of Electronic Information and Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (纸本)9789881563897

This paper proposes an improved non-dominated sorting genetic algorithm (NSGA2)-DNSGA2, with the aim of preserving diversity of obtained optimal solution and avoiding the original NSGA2 algorithm falling into local optimal. The proposed DNSGA2 algorithm which introduces a differential mutation operator to replace the original polynomial mutation because the method of differential local search is helpful to the uniformity of Pareto optimal solution set. The performance of the proposed DNSGA2, NSGA2 and W-LRCD-NSGA2 (Based on left-right crowding distance non-dominated sorting genetic algorithm) are compared via four benchmark functions. Simulation results indicate that the diversity and uniformity of Pareto optimal solution obtained by DNSGA2 are better than the other two algorithms. © 2015 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Differential mutation Multi-objective NSGA2 Pareto optimal solution

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94LVI Algorithms of OIpU(One-Iteration-per-Update) Type Handling Time-Dependent QP(Quadratic Programming) with Two Constraints 41

94LVI Algorithms of OIpU(One-Iteration-per-Update) Type Hand...

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第41届中国控制会议

作者： Yunong Zhang Zhiwen Yuan School of Computer Science and Engineering Sun Yat-sen University Guangdong Key Laboratory of Modern Control Technology Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Research Institute of Sun Yat-sen University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper presents three relatively effective numerical algorithms,i.e.,94 LVI algorithms of OIpU(one-iteration-perupdate) type,to handle time-dependent QP(quadratic programming) problems subject to two constraints respectively(i.e.,equality and inequality constraints,equality and bound constraints,or inequality and bound constraints).Specifically,two "bridges" play essential parts of the methods(i.e.,the first "bridge" makes a QP problem convert to an LVI [linear variational inequality],and the second "bridge" makes the LVI convert to a PLPE [piecewise-linear projection equation]).On the basis of the standard94 LVI algorithm,the methods only update once through the solution of the previous sampling time ***,we conduct a number of experiments to substantiate the three algorithms respectively,which use exponential functions,log functions,and trigonometric functions in corresponding coefficients of the experimental examples.

关键词： Quadratic programming Time-dependent Numerical algorithms Linear variational inequalities(LVI)

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Data-driven intelligent monitoring system for key variables in wastewater treatment process

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Chinese Journal of Chemical Engineering 2018年第10期26卷 2093-2101页

作者： Honggui Han Shuguang Zhu Junfei Qiao Min Guo College of Electronic Information & Control Engineering Beijing University of Technology Beijing 100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing 100124 China Engineering Research Center of Digital Community Ministry of Education Beijing 100124 China Beijing Laboratory for Urban Mass Transit Beijing 100124 China

In wastewater treatment process(WWTP), the accurate and real-time monitoring values of key variables are crucial for the operational strategies. However, most of the existing methods have difficulty in obtaining the real-time values of some key variables in the process. In order to handle this issue, a data-driven intelligent monitoring system, using the soft sensor technique and data distribution service, is developed to monitor the concentrations of effluent total phosphorous(TP) and ammonia nitrogen(NH_4-N). In this intelligent monitoring system, a fuzzy neural network(FNN) is applied for designing the soft sensor model, and a principal component analysis(PCA) method is used to select the input variables of the soft sensor model. Moreover, data transfer software is exploited to insert the soft sensor technique to the supervisory control and data acquisition(SCADA) system. Finally, this proposed intelligent monitoring system is tested in several real plants to demonstrate the reliability and effectiveness of the monitoring performance.

关键词： Data-driven Soft sensor Intelligent monitoring system Data distribution service Wastewater treatment process

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Spatio-temporal evolution of Beijing 2003 SARS epidemic

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Science China Earth Sciences 2010年第7期53卷 1017-1028页

作者： CAO ZhiDong ZENG DaJun ZHENG XiaoLong WANG QuanYi WANG FeiYue WANG JinFeng WANG XiaoLi Key Laboratory of Complex Systems and Intelligence Science Institute of AutomationChinese Academy of SciencesBeijing 100190China Beijing Center for Disease Control and Prevention Beijing 100013China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China

Studying spatio-temporal evolution of epidemics can uncover important aspects of interaction among people, infectious diseases, and the environment, providing useful insights and modeling support to facilitate public health response and possibly prevention measures. This paper presents an empirical spatio-temporal analysis of epidemiological data concerning 2321 SARS-infected patients in Beijing in 2003. We mapped the SARS morbidity data with the spatial data resolution at the level of street and township. Two smoothing methods, Bayesian adjustment and spatial smoothing, were applied to identify the spatial risks and spatial transmission trends. Furthermore, we explored various spatial patterns and spatio-temporal evolution of Beijing 2003 SARS epidemic using spatial statistics such as Moran’s I and LISA. Part of this study is targeted at evaluating the effectiveness of public health control measures implemented during the SARS epidemic. The main findings are as follows. (1) The diffusion speed of SARS in the northwest-southeast direction is weaker than that in northeast-southwest direction. (2) SARS’s spread risk is positively spatially associated and the strength of this spatial association has experienced changes from weak to strong and then back to weak during the lifetime of the Beijing SARS epidemic. (3) Two spatial clusters of disease cases are identified: one in the city center and the other in the eastern suburban area. These two clusters followed different evolutionary paths but interacted with each other as well. (4) Although the government missed the opportunity to contain the early outbreak of SARS in March 2003, the response strategies implemented after the mid of April were effective. These response measures not only controlled the growth of the disease cases, but also mitigated the spatial diffusion.

关键词： severe acute respiratory syndrome (SARS) Beijing morbidity rate spatial analysis spatio-temporal evolution control measures

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A data-derived soft-sensor method for monitoring effluent total phosphorus

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Chinese Journal of Chemical Engineering 2017年第12期25卷 1791-1797页

作者： Shuguang Zhu Honggui Han Min Guo Junfei Qiao College of Electronic Information & Control Engineering Beijing University of Technology Beijing 100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing 100124 China Engineering Research Center of Digital Community Ministry of Education Beijing 100124 China Beijing Laboratory for Urban Mass Transit Beijing 100124 China

The effluent total phosphorus(ETP) is an important parameter to evaluate the performance of wastewater treatment process(WWTP). In this study, a novel method, using a data-derived soft-sensor method, is proposed to obtain the reliable values of ETP online. First, a partial least square(PLS) method is introduced to select the related secondary variables of ETP based on the experimental data. Second, a radial basis function neural network(RBFNN) is developed to identify the relationship between the related secondary variables and ETP. This RBFNN easily optimizes the model parameters to improve the generalization ability of the soft-sensor. Finally, a monitoring system, based on the above PLS and RBFNN, named PLS-RBFNN-based soft-sensor system, is developed and tested in a real WWTP. Experimental results show that the proposed monitoring system can obtain the values of ETP online and own better predicting performance than some existing methods.

关键词： Data-derived soft-sensor Effluent total phosphorus Wastewater treatment process Radial basis function neural network Partial least square method

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