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Fuzzy force control of constrained robot manipulators based on impedance model in an unknown environment

LIU Hongyi, WANG Fei, WANG Lei

Frontiers of Mechanical Engineering 2007, Volume 2, Issue 2,   Pages 168-174 doi: 10.1007/s11465-007-0028-4

Abstract: To precisely implement the force control of robot manipulators in an unknown environment, a control strategyThe influences of unknown parameters of the environment on the contact force are analyzed based on experimentaltrajectory in the impedance model is predicted exactly and rapidly in the cases that the contact surface is unknown, the contact stiffness changes, and the fuzzy force control algorithm has high adaptability to the unknown

Keywords： predictive     tracking     corresponding     stiffness     algorithm    

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Stability and agility: biped running over varied and unknown terrain

Yang YI,Zhi-yun LIN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 4,   Pages 283-292 doi: 10.1631/FITEE.1400284

Abstract: We tackle the problem of a biped running over varied and unknown terrain.Then to ensure a small state jump at touchdown on the unknown terrain, the velocity of the swing foot

Keywords： Underactuated running biped     Dynamic balance     Varied and unknown terrain    

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A robot fuzzy motion planning approach in unknown environments

FU Yi-li, JIN Bao, LI Han, WANG Shu-guo

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 3,   Pages 336-340 doi: 10.1007/s11465-006-0033-z

Abstract: A fuzzy robot motion planning approach is proposed in unknown environments for three-degree industrial

Keywords： manipulator     repelling influence     manipulator configuration     three-degree industrial     simulation    

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The problems about the theory of “Known for unknown”

Zhu Xun

Strategic Study of CAE 2015, Volume 17, Issue 2,   Pages 35-39

Abstract:

“Known for unknown” is an important guiding ideology and prospecting method in mineral“Known for unknown” discuss relative to the prospecting for new working target，mainly inspace layout and the difference between the point and the surface and the unknown regions and known oredeposits，and put forward prospecting method to analysis of development theory in “Known for unknownAnd then promote and determine “Known for unknown” theory in ore prospecting work in practical

Keywords： Known for unknown； theory； prospecting； method； practice    

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High-order moment methods for LRFD including random variables with unknown probability distributions

Zhao-Hui LU, Yan-Gang ZHAO, Zhi-Wu YU

Frontiers of Structural and Civil Engineering 2013, Volume 7, Issue 3,   Pages 288-295 doi: 10.1007/s11709-013-0210-1

Abstract: However, in reality, the probability distributions of some of the basic random variables are often unknownIn this paper, the high-order moment methods for LRFD including random variables with unknown probabilityfactors can be determined even when the probability distributions of the basic random variables are unknown

Keywords： high-order moment methods     applicable range     load and resistance factors     target mean resistance    

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New decentralized control technique based on substructure and LQG approaches

Ying LEI, Ying LIN,

Frontiers of Mechanical Engineering 2009, Volume 4, Issue 4,   Pages 386-392 doi: 10.1007/s11465-009-0041-x

Abstract: local controller with interaction forces at substructural interfaces, which are considered as “unknownAn algorithm of recursive least squares estimation for the unknown excitation is proposed.

Keywords： substructures     decentralized control     linear quadratic Gaussian (LQG)     Kalman filter     unknown input     least-squares    

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Convergence of time-varying networks and its applications Research Articles

Qingling Wang,qlwang@seu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 1,   Pages 1-140 doi: 10.1631/FITEE.2000160

Abstract: In this study, we present the convergence of . Then, we apply the convergence property to cooperative control of nonlinear multiagent systems (MASs) with (UCDs), and illustrate a new kind of based control algorithms. It is proven that if the are cut-balance, the convergence of nonlinear MASs with nonidentical UCDs is achieved using the presented algorithms. A critical feature of this application is that the designed algorithms can deal with nonidentical UCDs by employing conventional s. Finally, one simulation example is given to illustrate the effectiveness of the presented algorithms.

Keywords： Time-varying networks     Unknown control directions     Nussbaum-type function     Cut-balance condition    

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Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and

Frontiers in Energy 2023, Volume 17, Issue 4,   Pages 527-544 doi: 10.1007/s11708-023-0880-x

Abstract: Intelligent power systems can improve operational efficiency by installing a large number of sensors. Data-based methods of supervised learning have gained popularity because of available Big Data and computing resources. However, the common paradigm of the loss function in supervised learning requires large amounts of labeled data and cannot process unlabeled data. The scarcity of fault data and a large amount of normal data in practical use pose great challenges to fault detection algorithms. Moreover, sensor data faults in power systems are dynamically changing and pose another challenge. Therefore, a fault detection method based on self-supervised feature learning was proposed to address the above two challenges. First, self-supervised learning was employed to extract features under various working conditions only using large amounts of normal data. The self-supervised representation learning uses a sequence-based Triplet Loss. The extracted features of large amounts of normal data are then fed into a unary classifier. The proposed method is validated on exhaust gas temperatures (EGTs) of a real-world 9F gas turbine with sudden, progressive, and hybrid faults. A comprehensive comparison study was also conducted with various feature extractors and unary classifiers. The results show that the proposed method can achieve a relatively high recall for all kinds of typical faults. The model can detect progressive faults very quickly and achieve improved results for comparison without feature extractors in terms of F1 score.

Keywords： fault detection     unary classification     self-supervised representation learning     multivariate nonlinear time series    

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Indirect adaptive fuzzy-regulated optimal control for unknown continuous-time nonlinear systems

Haiyun Zhang, Deyuan Meng, Jin Wang, Guodong Lu,gray_sun@zju.edu.cn,tinydreams@126.com,dwjcom@zju.edu.cn,lugd@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 2,   Pages 141-286 doi: 10.1631/FITEE.1900610

Abstract: indirect adaptive fuzzy-regulated optimal control scheme for continuous-time nonlinear systems with unknown

Keywords： Hamilton-Jacobi-Bellman equation     Fuzzy-regulated critic     Adaptive optimal control actor     Actor-critic structure     Unknown    

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Decentralized Searching of Multiple Unknown and Transient Radio Sources with Paired Robots Article

Chang-Young Kim, Dezhen Song, Jingang Yi, Xinyu Wu

Engineering 2015, Volume 1, Issue 1,   Pages 58-65 doi: 10.15302/J-ENG-2015010

Abstract: this paper, we develop a decentralized algorithm to coordinate a group of mobile robots to search for unknown

Keywords： wireless localization     networked robots     transient targets    

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Enhanced Autonomous Exploration and Mapping of an Unknown Environment with the Fusion of Dual RGB-D Sensors Article

Ningbo Yu, Shirong Wang

Engineering 2019, Volume 5, Issue 1,   Pages 164-172 doi: 10.1016/j.eng.2018.11.014

Abstract:

The autonomous exploration and mapping of an unknown environment is useful in a wide range of applicationssystematic approach with dual RGB-D sensors to achieve the autonomous exploration and mapping of an unknown

Keywords： Autonomous exploration     Red/green/blue-depth     Sensor fusion     Point cloud     Partial map simulation     Global frontier search    

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Target detection for multi-UAVs via digital pheromones and navigation algorithm in unknown environments Research

Yan Shao, Zhi-feng Zhao, Rong-peng Li, Yu-geng Zhou,shaoy@zju.edu.cn,zhaozf@zhejianglab.com,lirongpeng@zju.edu.cn,yugeng.zhou@wfjyjt.com

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 5,   Pages 649-808 doi: 10.1631/FITEE.1900659

Abstract: Coordinating multiple unmanned aerial vehicles (multi-UAVs) is a challenging technique in highly dynamic and sophisticated environments. Based on as well as current mainstream unmanned system controlling algorithms, we propose a strategy for multi-UAVs to acquire targets with limited prior knowledge. In particular, we put forward a more reasonable and effective pheromone update mechanism, by improving digital pheromone fusion algorithms for different semantic pheromones and planning individuals’ probabilistic behavioral decision-making schemes. Also, inspired by the flocking model in nature, considering the limitations of some individuals in perception and communication, we design a model on top of Olfati-Saber’s algorithm for flocking control, by further replacing the pheromone scalar to a vector. Simulation results show that the proposed algorithm can yield superior performance in terms of coverage, detection and revisit efficiency, and the capability of obstacle avoidance.

Keywords： 群体智能；数字信息素；人工势场；领航算法    

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Adaptive neural network based boundary control of a flexible marine riser system with output constraints Research Article

Chuyang YU, Xuyang LOU, Yifei MA, Qian YE, Jinqi ZHANG,sunrise_ycy@stu.jiangnan.edu.cn,Louxy@jiangnan.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 8,   Pages 1229-1238 doi: 10.1631/FITEE.2100586

Abstract: In this study, we develop an adaptive based method for a flexible with unknown nonlinear disturbances

Keywords： Marine riser system     Partial differential equation     Neural network     Output constraint     Boundary control     Unknown    

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Generalized labeled multi-Bernoulli filter with signal features of unknown emitters Research Article

Qiang GUO, Long TENG, Xinliang WU, Wenming SONG, Dayu HUANG

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12,   Pages 1871-1880 doi: 10.1631/FITEE.2200286

Abstract:

A novel algorithm that combines the (GLMB) filter with signal features of the unknown emitter is proposedIn complex electromagnetic environments, emitter features (EFs) are often unknown and time-varying.Aiming at the unknown feature problem, we propose a method for identifying EFs based on of data fieldsBecause EFs are time-varying and the probability distribution is unknown, an improved algorithm is proposed

Keywords： Multi-target tracking     Generalized labeled multi-Bernoulli     Signal features of emitter     Fuzzy C-means     Dynamic clustering    

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ApproximateGaussian conjugacy: parametric recursive filtering under nonlinearity,multimodality, uncertainty, and constraint, and beyond Review

Tian-cheng LI, Jin-ya SU, Wei LIU, Juan M. CORCHADO

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 12,   Pages 1913-1939 doi: 10.1631/FITEE.1700379

Abstract: arising from nonlinearity, multimodality (including target maneuver), intractable uncertainties (such as unknownobservation, multimodal systems including Gaussian mixture posterior and maneuvers, and intractable unknown

Keywords： estimation     Bayesian filtering     Nonlinear filtering     Constrained filtering     Gaussian mixture     Maneuver     Unknown    

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Title Author Date Type Operation

Fuzzy force control of constrained robot manipulators based on impedance model in an unknown environment

LIU Hongyi, WANG Fei, WANG Lei

Journal Article

Stability and agility: biped running over varied and unknown terrain

Yang YI,Zhi-yun LIN

Journal Article

A robot fuzzy motion planning approach in unknown environments

FU Yi-li, JIN Bao, LI Han, WANG Shu-guo

Journal Article

The problems about the theory of “Known for unknown”

Zhu Xun

Journal Article

High-order moment methods for LRFD including random variables with unknown probability distributions

Zhao-Hui LU, Yan-Gang ZHAO, Zhi-Wu YU

Journal Article

New decentralized control technique based on substructure and LQG approaches

Ying LEI, Ying LIN,

Journal Article

Convergence of time-varying networks and its applications

Qingling Wang,qlwang@seu.edu.cn

Journal Article

Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and

Journal Article

Indirect adaptive fuzzy-regulated optimal control for unknown continuous-time nonlinear systems

Haiyun Zhang, Deyuan Meng, Jin Wang, Guodong Lu,gray_sun@zju.edu.cn,tinydreams@126.com,dwjcom@zju.edu.cn,lugd@zju.edu.cn

Journal Article

Decentralized Searching of Multiple Unknown and Transient Radio Sources with Paired Robots

Chang-Young Kim, Dezhen Song, Jingang Yi, Xinyu Wu

Journal Article

Enhanced Autonomous Exploration and Mapping of an Unknown Environment with the Fusion of Dual RGB-D Sensors

Ningbo Yu, Shirong Wang

Journal Article

Target detection for multi-UAVs via digital pheromones and navigation algorithm in unknown environments

Yan Shao, Zhi-feng Zhao, Rong-peng Li, Yu-geng Zhou,shaoy@zju.edu.cn,zhaozf@zhejianglab.com,lirongpeng@zju.edu.cn,yugeng.zhou@wfjyjt.com

Journal Article

Adaptive neural network based boundary control of a flexible marine riser system with output constraints

Chuyang YU, Xuyang LOU, Yifei MA, Qian YE, Jinqi ZHANG,sunrise_ycy@stu.jiangnan.edu.cn,Louxy@jiangnan.edu.cn

Journal Article

Generalized labeled multi-Bernoulli filter with signal features of unknown emitters

Qiang GUO, Long TENG, Xinliang WU, Wenming SONG, Dayu HUANG

Journal Article

ApproximateGaussian conjugacy: parametric recursive filtering under nonlinearity,multimodality, uncertainty, and constraint, and beyond

Tian-cheng LI, Jin-ya SU, Wei LIU, Juan M. CORCHADO

Journal Article