Resource Type

Journal Article 994

Year

2024 1

2023 74

2022 102

2021 74

2020 77

2019 67

2018 45

2017 59

2016 33

2015 46

2014 40

2013 37

2012 30

2011 29

2010 25

2009 36

2008 39

2007 58

2006 26

2005 20

open ︾

Keywords

control 40

neural network 32

artificial neural network 21

Neural network 11

Artificial intelligence 8

vector control 8

convolutional neural network 7

genetic algorithm 7

maximum power point tracking (MPPT) 7

neural networks 7

optimization 7

quality control 7

robust control 7

COVID-19 6

Deep learning 6

Multi-agent systems 6

artificial neural network (ANN) 6

simulation 6

temperature control 6

open ︾

Search scope:

排序： Display mode:

Design, analysis, and neural control of a bionic parallel mechanism

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 3,   Pages 468-486 doi: 10.1007/s11465-021-0640-8

Abstract: movement coordination and versatile locomotion of mammals, the structural design and neuromechanical controlThe neural control of the parallel mechanism is realized by constructing a neuromechanical network, which

Keywords： neural control     behavior network     rhythm     motion pattern    

HTML PDF Collect

PID neural network control of a membrane structure inflation system

Qiushuang LIU, Xiaoli XU

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 4,   Pages 418-422 doi: 10.1007/s11465-010-0117-7

Abstract: Because it is difficult for the traditional PID algorithm for nonlinear time-variant control objectsto obtain satisfactory control results, this paper studies a neuron PID controller.The PID controller is used to control a nonlinear time-variant membrane structure inflation system.Results show that the neural network PID controller can adapt to the changes in system structure parametersand fast track the changes in the input signal with high control precision.

Keywords： PID     neural network     membrane structure    

HTML PDF Collect

Frequency domain a9ctive vibration control of a flexible plate based on neural networks

Jinxin LIU, Xuefeng CHEN, Zhengjia HE

Frontiers of Mechanical Engineering 2013, Volume 8, Issue 2,   Pages 109-117 doi: 10.1007/s11465-013-0252-z

Abstract:

A neural-network (NN)-based active control system was proposed to reduce the low frequency noise radiationFeedback control system was built, in which neural network controller (NNC) and neural network identifierMulti-frequency control in frequency domain was achieved by simulation through the NN-based control systemsA pre-testing experiment of the control system on a real simply supported plate was conducted.The NN-based control algorithm was shown to perform effectively.

Keywords： active vibration control (AVC)     neural network (NN)     low frequency noise     frequency domain control     multi-frequencycontrol    

HTML PDF Collect

Neural network control for earthquake structural vibration reduction using MRD

Khaled ZIZOUNI, Leyla FALI, Younes SADEK, Ismail Khalil BOUSSERHANE

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 5,   Pages 1171-1182 doi: 10.1007/s11709-019-0544-4

Abstract: intended for exposure to strong earthquake loads are designed and equipped with high technologies of controlOne of these technologies used in the protection of structures is the semi-active control using a MagnetoIn this study, a neural network controller is proposed to control the MR damper to eliminate vibrationsThe proposed controller is derived from a linear quadratic controller designed to control an MR damperEquipped with a feedback law the proposed control is coupled to a clipped optimal algorithm to adapt

Keywords： MR damper     semi-active control     earthquake vibration     neural network     linear quadratic control    

HTML PDF Collect

Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 2,   Pages 149-156 doi: 10.1007/s11465-010-0008-y

Abstract: technology has been gradually employed to increase the automation and intelligence degree in quality controlusing statistical process control (SPC) method.In this paper, an SPC method based on a fuzzy adaptive resonance theory (ART) neural network is presentedThe fuzzy ART neural network is applied to recognize the special disturbance of the manufacturing processesnetwork can also be utilized to adaptively detect the abnormal patterns in the control chart.

Keywords： statistical process control (SPC)     fuzzy adaptive resonance theory (ART)     histogram     control chart     time    

HTML PDF Collect

Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural faulttolerant control

Hamed HABIBI, Hamed RAHIMI NOHOOJI, Ian HOWARD

Frontiers of Mechanical Engineering 2017, Volume 12, Issue 3,   Pages 377-388 doi: 10.1007/s11465-017-0431-4

Abstract: This paper studies the control methodology for variable-speed variable-pitch wind turbines includinguncertainties, the unknown nonlinearities of the wind turbine are estimated by utilizing radial basis function neuralThe adaptive neural fault tolerant control is designed passively to be robust on model uncertainties,

Keywords： wind turbine nonlinear model     maximum power tracking     passive fault tolerant control     adaptive neural control    

HTML PDF Collect

A modified neural learning algorithm for online rotor resistance estimation in vector controlled induction

A. CHITRA,S. HIMAVATHI

Frontiers in Energy 2015, Volume 9, Issue 1,   Pages 22-30 doi: 10.1007/s11708-014-0339-1

Abstract: In this paper, a novel modified neural algorithm has been identified for the online estimation of rotorNeural based estimators are now receiving active consideration as they have a number of advantages overThe training algorithm of the neural network determines its learning speed, stability, weight convergenceIn this paper, the neural estimator has been studied with conventional and proposed learning algorithms

Keywords： neural networks     back propagation (BP)     rotor resistance estimators     vector control     induction motor    

HTML PDF Collect

QPSO-ILF-ANN-based optimization of TBM control parameters considering tunneling energy efficiency

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 1,   Pages 25-36 doi: 10.1007/s11709-022-0908-z

Abstract: However, the TBM control parameters set based on operator experience may not necessarily be suitableHence, a method to optimize TBM control parameters using an improved loss function-based artificial neuralInspired by the regularization technique, a custom artificial neural network (ANN) loss function based

Keywords： tunnel boring machine     control parameter optimization     quantum particle swarm optimization     artificialneural network     tunneling energy efficiency    

HTML PDF Collect

Adaptive robust neural control of a two-manipulator system holding a rigid object with inaccurate base Research

Fan XU, Jin WANG, Guo-dong LU

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 11,   Pages 1316-1327 doi: 10.1631/FITEE.1601707

Abstract:

The problem of self-tuning control with a two-manipulator system holding a rigid object in the presenceAn adaptive robust neural controller is proposed to cope with inaccurate translational base frame parametersA radial basis function neural network is adopted for all kinds of dynamical estimation, including undesired

Keywords： Cooperative manipulators     Neural networks     Inaccurate translational base frame     Adaptive control     Robustcontrol    

HTML PDF Collect

Research on fuzzy neural network control method for high-frequency vacuum drying of wood

Jiang Bin,Sun Liping,Cao Jun and Zhou Zheng

Strategic Study of CAE 2014, Volume 16, Issue 4,   Pages 17-20

Abstract: theoretical analysis with high frequency in wood vacuum drying process，the fuzzy controller and fuzzy neuralnetwork controller of wood drying are designed in view of the neural network method to establish modelThe simulation experiment results show that fuzzy neural network control is better，such as the temperaturerising fast，high control precision，good stability.The method to realize the automatic control of timber drying process has important research significance

Keywords： high-frequency vacuum     wood drying     fuzzy neural network    

HTML PDF Collect

Comparative study of various artificial intelligence approaches applied to direct torque control of induction

Moulay Rachid DOUIRI, Mohamed CHERKAOUI

Frontiers in Energy 2013, Volume 7, Issue 4,   Pages 456-467 doi: 10.1007/s11708-013-0264-8

Abstract: In this paper, three intelligent approaches were proposed, applied to direct torque control (DTC) ofto replace conventional hysteresis comparators and selection table, namely fuzzy logic, artificial neuraldemonstrate the feasibility of the adaptive network-based fuzzy inference system based direct torque controlCompared with the classical direct torque control, fuzzy logic based direct torque control (FL-DTC),and neural networks based direct torque control (NN-DTC), the proposed ANFIS-based scheme optimizes the

Keywords： adaptive neuro-fuzzy inference system (ANFIS)     artificial neural network     direct torque control (DTC)     fuzzy    

HTML PDF Collect

Identification of Time-delay Systems and Correction of NARMA Model

Wng Dongqing

Strategic Study of CAE 2006, Volume 8, Issue 2,   Pages 39-43

Abstract: The neural networks predictive control of time-delay system is taken as an example to present the correctSimulation results verify that the advanced correction methods can obtain good control performance and

Keywords： identification     NARMA model     neural network     predictive control    

HTML PDF Collect

Multiscale computation on feedforward neural network and recurrent neural network

Bin LI, Xiaoying ZHUANG

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 6,   Pages 1285-1298 doi: 10.1007/s11709-020-0691-7

Abstract: The neural networks can be used to construct fully decoupled approaches in nonlinear multiscale methodsThis article intends to model the multiscale constitution using feedforward neural network (FNN) andrecurrent neural network (RNN), and appropriate set of loading paths are selected to effectively predict

Keywords： multiscale method     constitutive model     feedforward neural network     recurrent neural network    

HTML PDF Collect

A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 2, doi: 10.1007/s11465-022-0673-7

Abstract: Convolutional neural network (CNN) has achieved remarkable applications in fault diagnosis.

Keywords： deep reinforcement learning     hyper parameter optimization     convolutional neural network     fault diagnosis    

HTML PDF Collect

Automated classification of civil structure defects based on convolutional neural network

Pierclaudio SAVINO, Francesco TONDOLO

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 2,   Pages 305-317 doi: 10.1007/s11709-021-0725-9

Abstract: this paper presents a method for automating concrete damage classification using a deep convolutional neuralThe convolutional neural network was designed after an experimental investigation of a wide number of

Keywords： concrete structure     infrastructures     visual inspection     convolutional neural network     artificial intelligence    

HTML PDF Collect

Title Author Date Type Operation

Design, analysis, and neural control of a bionic parallel mechanism

Journal Article

PID neural network control of a membrane structure inflation system

Qiushuang LIU, Xiaoli XU

Journal Article

Frequency domain a9ctive vibration control of a flexible plate based on neural networks

Jinxin LIU, Xuefeng CHEN, Zhengjia HE

Journal Article

Neural network control for earthquake structural vibration reduction using MRD

Khaled ZIZOUNI, Leyla FALI, Younes SADEK, Ismail Khalil BOUSSERHANE

Journal Article

Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

Journal Article

Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural faulttolerant control

Hamed HABIBI, Hamed RAHIMI NOHOOJI, Ian HOWARD

Journal Article

A modified neural learning algorithm for online rotor resistance estimation in vector controlled induction

A. CHITRA,S. HIMAVATHI

Journal Article

QPSO-ILF-ANN-based optimization of TBM control parameters considering tunneling energy efficiency

Journal Article

Adaptive robust neural control of a two-manipulator system holding a rigid object with inaccurate base

Fan XU, Jin WANG, Guo-dong LU

Journal Article

Research on fuzzy neural network control method for high-frequency vacuum drying of wood

Jiang Bin,Sun Liping,Cao Jun and Zhou Zheng

Journal Article

Comparative study of various artificial intelligence approaches applied to direct torque control of induction

Moulay Rachid DOUIRI, Mohamed CHERKAOUI

Journal Article

Identification of Time-delay Systems and Correction of NARMA Model

Wng Dongqing

Journal Article

Multiscale computation on feedforward neural network and recurrent neural network

Bin LI, Xiaoying ZHUANG

Journal Article

A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Journal Article

Automated classification of civil structure defects based on convolutional neural network

Pierclaudio SAVINO, Francesco TONDOLO

Journal Article