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Time-varying formation tracking control of high-order multi-agent systems with multiple leaders and multiplicative noise

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Science China(Information Sciences) 2024年第12期67卷 191-207页

作者： Ruru JIA Xiaofeng ZONG Qing WANG College of Artificial Intelligence Nankai University School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation Science and Electrical Engineering Beihang University

This work discusses the time-varying formation(TVF) tracking control problem of high-order multi-agent systems(MASs) with multiple leaders and multiplicative measurement noise. With the help of Lyapunov function tools and stochastic analysis methods, the TVF tracking protocol with multiple leaders and multiplicative noise is developed based on the relative state measurements, where followers are driven to realize the target TVF while tracking the convex combination formed by multiple leaders. Then, the TVF tracking problem is converted into the mean square asymptotic stability problem of a stochastic differential equation(SDE); sufficient conditions related to the control gains are given by stabilizing the corresponding stochastic system. Moreover, a TVF tracking algorithm is presented to outline the steps of protocol ***, the theoretical results are illustrated in terms of simulation examples.

关键词： multi-agent systems multiple leaders multiplicative measurement noise stochastic differential equation formation tracking control

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Optimal fusion estimation for stochastic systems with cross-correlated sensor noises

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Science China(Information Sciences) 2017年第12期60卷 57-70页

作者： Liping YAN Yuanqing XIA Mengyin FU School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology

This paper is concerned with the optimal fusion of sensors with cross-correlated sensor *** taking linear transformations to the measurements and the related parameters, new measurement models are established, where the sensor noises are decoupled. The centralized fusion with raw data, the centralized fusion with transformed data, and a distributed fusion estimation algorithm are introduced, which are shown to be equivalent to each other in estimation precision, and therefore are globally optimal in the sense of linear minimum mean square error(LMMSE). It is shown that the centralized fusion with transformed data needs lower communication requirements compared to the centralized fusion using raw data directly, and the distributed fusion algorithm has the best flexibility and robustness and proper communication requirements and computation complexity among the three algorithms(less communication and computation complexity compared to the existed distributed Kalman filtering fusion algorithms). An example is shown to illustrate the effectiveness of the proposed algorithms.

关键词： optimal estimation distributed fusion Kalman filter cross-correlated noises linear transformation

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Adaptive Robust Dead-Zone Compensation control of Electro-Hydraulic Servo systems with Load Disturbance Rejection

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Journal of systems Science & complexity 2015年第2期28卷 341-359页

作者： HE Yudong WANG Junzheng HAO Renjian Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

A backstepping method based adaptive robust dead-zone compensation controller is pro- posed for the electro-hydraulic servo systems （EHSSs） with unknown dead-zone and uncertain system parameters. Variable load is seen as a sum of a constant and a variable part. The constant part is regarded as a parameter of the system to be estimated real time. The variable part together with the friction are seen as disturbance so that a robust term in the controller can be adopted to reject them. Compared with the traditional dead-zone compensation method, a dead-zone compensator is incor- porated in the EH$S without constructing a dead-zone inverse. Combining backstepping method, an adaptive robust controller （ARC） with dead-zone compensation is formed. An easy-to-use ARC tuning method is also proposed after a further analysis of the ARC structure. Simulations show that the proposed method has a splendid tracking performance, all the uncertain parameters can be estimated, and the disturbance has been rejected while the dead-zone term is well estimated and compensated.

关键词： Adaptive robust control dead-zone servo systems tuning method. compensation disturbance rejection electro-hydraulic

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Development of electric cart for improving walking ability — application of control theory to assistive technology

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Science China(Information Sciences) 2017年第12期60卷 262-270页

作者： Jinhua SHE Yasuhiro OHYAMA Min WU Hiroshi HASHIMOTO School of Engineering Tokyo University of Technology School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Master Program of Innovation for Design & Engineering Advanced Institute of Industrial Technology

This paper explains the development of an electric cart that helps the elderly maintain or improve their physical strength. Unlike commercially available ones, it has a pedal unit that provides some exercise for a user in training his lower limbs. An impedance model describes the feeling of pushing the pedals. The largest pedal load is determined based on a pedaling experiment. An H∞ controller is designed for each of the largest pedal load and virtually no load. A control law, which is based on the concept of dynamic parallel distributed compensation, is designed using the rating of perceived exertion of a driver as a criterion to choose a pedal load between the largest and almost zero. Five university students and twelve elderly people participated experiments to verify the system design and the validity of the system.

关键词： aging Borg’s scale dynamic parallel distributed compensation electrical cart H_∞ control Karvonen formula lower limbs pedaling rating of perceived exertion

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A CUDA-Based Parallel Adaptive Dynamic Programming Algorithm 36

A CUDA-Based Parallel Adaptive Dynamic Programming Algorithm

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第36届中国控制会议

作者： Lu Li Xin Chen Wei Wang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Adaptive Dynamic Programming（ADP） with critic-actor architecture is a useful way to achieve online learning *** algorithm Gaussian-Kernel Adaptive Dynamic Programming（GK-ADP） that has been developed before has a kind of two-phase iteration,which not only approximates value function,but also optimizes hyper-parameters ***,just like most iteration algorithms are applied in practice,the scale of sample set will increase as the complexity of the system increases,and it will induce a high computation *** order to speed up computation,a practical acceleration method using parallel computation for GK-ADP is presented in this *** realize parallel computation,a high efficient configuration based on CUDA is designed,in which a group of GPUs work in parallel to compute the most complex part of *** comparison test illustrates that the computation burden which hinders GK-ADP’s application is reduced to a large extent when the parallel computing is introduced.

关键词： Gaussian-Kernel Adaptive Dynamic Programming CUDA Parallel Computing GPU

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Performance Diagnosis of controller Based on Eigenvector Subspace K-mean Clustering 36

Performance Diagnosis of Controller Based on Eigenvector Sub...

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第36届中国控制会议

作者： Man Hao Wei-Hua Cao Min Wu Yan Yuan Zhen-Tao Liu School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

To diagnose the specific reasons that lead to deterioration of controller performance and improve the diagnostic accuracy,a performance diagnosis method based on eigenvector subspace K-mean clustering is ***,the number of standard deterioration performance subspace with different degrees of deterioration information is increased on the basis of the eigenvector subspace distance diagnosis method,in which multiple distance values between eigenvector subspaces are ***,K-mean clustering is used to divide these distance values into two classes,and the clustering center with a maximum number of points is selected as the representative ***,current performance degradation factor is attributed to the category that represented by the nearest standard performance *** simulation,a double-tank model is established,and simulation result shows that average accuracy of controller performance diagnosis reaches 99.4%approximately.

关键词： controller performance performance diagnosis eigenvector subspace K-mean clustering

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Short-term Wind Power Prediction by Using Empirical Mode Decomposition Based GA-SVR 36

Short-term Wind Power Prediction by Using Empirical Mode Dec...

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第36届中国控制会议

作者： Hua Xie Min Ding Luefeng Chen Jianqi An Zhangbing Chen Min Wu School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Accurate short-term wind power prediction can improve the trade and the dispatch level of wind *** predict the short-term wind power,we investigated the empirical mode decomposition（EMD） of numerical weather prediction（NWP） and genetic algorithm（GA） optimization of support vector regression（SVR）.First,the wind speed data from NWP is decomposed into the EMD components,including multiple intrinsic mode functions（IMFs） and one ***,a genetic algorithmsupport vector regression model（GA-SVR） is used to build models of all ***,the prediction results of all components are integrated,which as input of wind-power curve for obtain the predicted value of wind *** order to validate the proposed method,one real-world dataset was used for model training and testing,and the results show that the proposed method is more accurate and effective than SVR and back propagation neural networks（BPNN）.

关键词： Wind Power Prediction Empirical Mode Decomposition Support Vector Regression Genetic Algorithm Fast Fourier Transform Wavelet Filter

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A memetic algorithm for path planning of curvature-constrained UAVs performing surveillance of multiple ground targets

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Chinese Journal of Aeronautics 2014年第3期27卷 622-633页

作者： Zhang Xing Chen Jie Xin Bin Peng Zhihong School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles （UAVs） performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so that the constraints of UAVs＇ minimal turning radius can be taken into account. In view of the effective surveillance range of the sensors equipped on UAVs, the problem is formulated as a Dubins traveling salesman problem with neighborhood （DTSPN）. Considering its prohibitively high computational complexity, the Dubins paths in the sense of terminal heading relaxation are introduced to simplify the calculation of the Dubins distance, and a boundary-based encoding scheme is proposed to determine the visiting point of every target neighborhood. Then, an evolutionary algorithm is used to derive the optimal Dubins tour. To further enhance the quality of the solutions, a local search strategy based on approximate gradient is employed to improve the visiting points of target neighborhoods. Finally, by a minor modification to the individual encoding, the algorithm is easily extended to deal with other two more sophisticated DTSPN variants （multi-UAV scenario and multiple groups of targets scenario）. The performance of the algorithm is demonstrated through comparative experiments with other two state-of-the-art DTSPN algorithms identified in literature. Numerical simulations exhibit that the algorithm proposed in this paper can find high-quality solutions to the DTSPN with lower computational cost and produce significantly improved performance over the other algorithms.

关键词： Approximate gradient Dubins traveling salesmanproblem with neighborhood Local search Memetic algorithm Unmanned aerial vehicles

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Multi-layer Performance Assessment Method for Sintering Production Process control System 36

Multi-layer Performance Assessment Method for Sintering Prod...

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第36届中国控制会议

作者： Wei Jiao Xin Chen Min Wu Wei Hua Cao School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

According to the hierarchical control system of sintering production process,a multi-layer performance assessment method is *** discuss the structure,function and technology used of multi-layer performance assessment strategy which is composed of sintering comprehensive coke ratio(CCR) assessment module,sintering ignition assessment module and fuzzy synthetic decision-making *** multi-layer performance assessment for sintering production process control system is realized based on sintering CCR prediction model,performance assessment method for sintering ignition control,and fuzzy synthetic evaluation *** proposed multi-layer performance assessment method is implemented on the simulation platform of the sintering production process in the laboratory,which effectively realized the performance assessment for sintering production process plant level control system,and then provides effective information for the staff to maintain the control system.

关键词： Hierarchical control system Performance assessment method Fuzzy synthetic evaluation Comprehensive coke ratio Sintering ignition control

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Speaker-independent Speech Emotion Recognition Based on Random Forest Feature Selection Algorithm 36

Speaker-independent Speech Emotion Recognition Based on Rand...

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第36届中国控制会议

作者： Wei-Hua Cao Jian-Ping Xu Zhen-Tao Liu School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Feature selection is a crucial step in the development of a system for identifying emotions in *** to select high correlation features is an open *** paper focuses on feature selection method which aims to extract the most effective acoustic features to improve the performance of emotion *** feature selection of speakerindependent speech based on Random Forest is proposed,which can remove the redundant features that have high correlations with each *** on the speech emotion recognition based on Support Vector Machines(SVM) is performed,where the speaker-independent features selected by the proposal and Spearman correlation analysis are used for emotion recognition,*** results show that the proposal achieves 78.6%recognition rate on average,which is 2.2%higher than using Spearman.

关键词： Emotion Recognition Speech Speaker-independent Feature Selection Random Forest

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