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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    

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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    

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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 undesiredUsing an adaptive engine, this approach permits accurate online calibration of the relative translational

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

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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: to replace conventional hysteresis comparators and selection table, namely fuzzy logic, artificial neuralnetwork and adaptive neuro-fuzzy inference system (ANFIS).The simulated results obtained demonstrate the feasibility of the adaptive network-based fuzzy inferenceCompared 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    

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An adaptive sliding mode control technology for weld seam tracking

Jie LIU,Youmin HU,Bo WU,Kaibo ZHOU,Mingfeng GE

Frontiers of Mechanical Engineering 2015, Volume 10, Issue 1,   Pages 95-101 doi: 10.1007/s11465-015-0332-3

Abstract:

A novel adaptive sliding mode control algorithm is derived to deal with seam tracking control problemenables better high-precision tracking performance with chattering-free than traditional sliding mode control

Keywords： weld seam tracking     welding robotic manipulator     adaptive control     sliding mode control    

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Obstacle-circumventing adaptive control of a four-wheeled mobile robot subjected to motion uncertainties

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 3, doi: 10.1007/s11465-023-0753-3

Abstract: collision-free trajectory tracking of the four-wheeled mobile robot (FMR), existing methods resolve the tracking controlTo address this challenge, this paper proposes an obstacle-circumventing adaptive control (OCAC) frameworkSpecifically, a novel anti-disturbance terminal slide mode control with adaptive gains is formulated,incorporating specified control laws for different stages.

Keywords： four-wheeled mobile robot     obstacle-circumventing adaptive control     adaptive anti-disturbance terminalsliding mode control     sub-target dynamic tracking regression obstacle avoidance    

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A model reference adaptive control based method for actuator delay estimation in real-time testing

Cheng CHEN, James M. RICLES

Frontiers of Structural and Civil Engineering 2010, Volume 4, Issue 3,   Pages 277-286 doi: 10.1007/s11709-010-0072-8

Abstract: The advances in compensation methods based on adaptive control theory enable researchers to accommodatevariable actuator delay and achieve good actuator control for real-time tests.However, these adaptive methods all require time duration for actuator delay adaptation.Experiments show that a good actuator delay estimate can help optimize the performance of the adaptiveThis paper presents a model reference adaptive control based method to identify the parameter of a simplified

Keywords： real-time testing     actuator delay     compensation     adaptive control     MIT rule     discrete transfer function    

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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    

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Predicting the yield of pomegranate oil from supercritical extraction using artificial neural networksand an adaptive-network-based fuzzy inference system

J. Sargolzaei, A. Hedayati Moghaddam

Frontiers of Chemical Science and Engineering 2013, Volume 7, Issue 3,   Pages 357-365 doi: 10.1007/s11705-013-1336-3

Abstract: Several simulation systems including a back-propagation neural network (BPNN), a radial basis functionneural network (RBFNN) and an adaptive-network-based fuzzy inference system (ANFIS) were tested and

Keywords： oil recovery     artificial intelligence     extraction     neural networks     supercritical extraction    

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Terrain classification and adaptive locomotion for a hexapod robot Qingzhui

Yue ZHAO, Feng GAO, Qiao SUN, Yunpeng YIN

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 2,   Pages 271-284 doi: 10.1007/s11465-020-0623-1

Abstract: The knowledge of various ground properties and adaptive locomotion based on different surface materialsA terrain classification and adaptive locomotion method for a hexapod robot named Qingzhui is proposedThen, an adaptive locomotion on different ground properties is proposed.The dynamic alternating tripod trotting gait is developed to control the robot, and the parameters ofactive compliance control change with the terrain.

Keywords： terrain classification     hexapod robot     legged robot     adaptive locomotion     gait control    

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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    

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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    

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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    

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High Precision Adaptive Predictive Control for Cruise Missile

Sun Mingwei,Chen Zengqiang,Yuan Zhuzhi,Ren Qiang,Yang Ming

Strategic Study of CAE 2005, Volume 7, Issue 10,   Pages 23-27

Abstract: are constructed for attitude control loop, and their discrete models are served as controlled plantfor recursive least square (RLS) based adaptive predictive control, thus the mass center control withslow response transforms into trajectory angle control with fast response and high precision.attitude loop, and an integral form of predictive control is adopted in outter trajectory loop.with mass center control.

Keywords： cruise missile     adaptive control     model based predictive control     robustness    

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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 disturbancesFinally, numerical simulations are given to demonstrate the effectiveness of the proposed control method

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

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Title Author Date Type Operation

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

Hamed HABIBI, Hamed RAHIMI NOHOOJI, Ian HOWARD

Journal Article

Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

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

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

Moulay Rachid DOUIRI, Mohamed CHERKAOUI

Journal Article

An adaptive sliding mode control technology for weld seam tracking

Jie LIU,Youmin HU,Bo WU,Kaibo ZHOU,Mingfeng GE

Journal Article

Obstacle-circumventing adaptive control of a four-wheeled mobile robot subjected to motion uncertainties

Journal Article

A model reference adaptive control based method for actuator delay estimation in real-time testing

Cheng CHEN, James M. RICLES

Journal Article

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

Journal Article

Predicting the yield of pomegranate oil from supercritical extraction using artificial neural networksand an adaptive-network-based fuzzy inference system

J. Sargolzaei, A. Hedayati Moghaddam

Journal Article

Terrain classification and adaptive locomotion for a hexapod robot Qingzhui

Yue ZHAO, Feng GAO, Qiao SUN, Yunpeng YIN

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

High Precision Adaptive Predictive Control for Cruise Missile

Sun Mingwei,Chen Zengqiang,Yuan Zhuzhi,Ren Qiang,Yang Ming

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