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遗传算法 17

神经网络 16

仿真 7

质量控制 6

控制 5

模糊控制 5

鲁棒性 5

人工智能 4

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主动控制 3

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Application of fuzzy logic control algorithm as stator power controller of a grid-connected doubly-fed

Ridha CHEIKH, Arezki MENACER, Said DRID, Mourad TIAR

《能源前沿（英文）》 2013年 第7卷 第1期   页码 49-55 doi: 10.1007/s11708-012-0217-7

摘要： This paper discusses the power outputs control of a grid-connected doubly-fed induction generator (DFIG) for a wind power generation systems. The DFIG structure control has a six diode rectifier and a PWM IGBT converter in order to control the power outputs of the DFIG driven by wind turbine. So, to supply commercially the electrical power to the grid without any problems related to power quality, the active and reactive powers ( , ) at the stator side of the DFIG are strictly controlled at a required level, which, in this paper, is realized with an optimized fuzzy logic controller based on the grid flux oriented control, which gives an optimal operation of the DFIG in sub-synchronous region, and the control of the stator power flow with the possibility of keeping stator power factor at a unity.

关键词： doubly-fed induction generator (DFIG)     vector control     fuzzy logic controller     optimization     power factor unity     active and reactive power    

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Semi-active fuzzy control of Lali Cable-Stayed Bridge using MR dampers under seismic excitation

Sajad JAVADINASAB HORMOZABAD, Amir K. GHORBANI-TANHA

《结构与土木工程前沿（英文）》 2020年 第14卷 第3期   页码 706-721 doi: 10.1007/s11709-020-0612-9

摘要： Seismic control of cable-stayed bridges is of paramount importance due to their complex dynamic behavior, high flexibility, and low structural damping. In the present study, several semi-active Fuzzy Control Algorithms (FCAs) for vibration mitigation of Lali Cable-Stayed Bridge are devised. To demonstrate the efficiency of the algorithms, a comprehensive nonlinear 3-D model of the bridge is created using OpenSees. An efficient method for connecting MATLAB and OpenSees is devised for applying FCAs to the structural model of the bridge. Two innovative fuzzy rule-bases are introduced. A total of six different fuzzy rule-bases are utilized. The efficiency of the FCAs is evaluated in a comparative manner. The performance of fuzzy control systems is also compared with a sky-hook and a passive-on system. Moreover, the sensitivity of efficiency of control systems to the peak ground acceleration is evaluated qualitatively. In addition, the effect of time lag is also investigated. This study thoroughly examines the efficiency of the FCAs in different aspects. Therefore, the results can be regarded as a general guide to design semi-active fuzzy control systems for vibration mitigation of cable-stayed bridges.

关键词： semi-active control     Fuzzy Control Algorithm     cable-stayed bridge     MR damper     Lali Bridge    

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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

《机械工程前沿（英文）》 2007年 第2卷 第2期   页码 168-174 doi: 10.1007/s11465-007-0028-4

摘要： To precisely implement the force control of robot manipulators in an unknown environment, a control strategy based on fuzzy prediction of the reference trajectory in the impedance model is developed. The force tracking experiments are executed in an open-architecture control system with different tracking velocities, different desired forces, different contact stiffnesses and different surface figurations. The corresponding force control results are compared and analyzed. The influences of unknown parameters of the environment on the contact force are analyzed based on experimental data, and the tunings of predictive scale factors are illustrated. The experimental results show that the desired trajectory 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 environment.

关键词： predictive     tracking     corresponding     stiffness     algorithm    

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Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing

Reza TEIMOURI, Hamed SOHRABPOOR

《机械工程前沿（英文）》 2013年 第8卷 第4期   页码 429-442 doi: 10.1007/s11465-013-0277-3

摘要：

Electrochemical machining process (ECM) is increasing its importance due to some of the specific advantages which can be exploited during machining operation. The process offers several special privileges such as higher machining rate, better accuracy and control, and wider range of materials that can be machined. Contribution of too many predominate parameters in the process, makes its prediction and selection of optimal values really complex, especially while the process is programmized for machining of hard materials. In the present work in order to investigate effects of electrolyte concentration, electrolyte flow rate, applied voltage and feed rate on material removal rate (MRR) and surface roughness (SR) the adaptive neuro-fuzzy inference systems (ANFIS) have been used for creation predictive models based on experimental observations. Then the ANFIS 3D surfaces have been plotted for analyzing effects of process parameters on MRR and SR. Finally, the cuckoo optimization algorithm (COA) was used for selection solutions in which the process reaches maximum material removal rate and minimum surface roughness simultaneously. Results indicated that the ANFIS technique has superiority in modeling of MRR and SR with high prediction accuracy. Also, results obtained while applying of COA have been compared with those derived from confirmatory experiments which validate the applicability and suitability of the proposed techniques in enhancing the performance of ECM process.

关键词： electrochemical machining process (ECM)     modeling     adaptive neuro-fuzzy inference system (ANFIS)     optimization     cuckoo optimization algorithm (COA)    

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智能自主寻迹小车测控系统的研究与设计

王玲,张强,李雪梅

《中国工程科学》 2014年 第16卷 第3期   页码 92-98

摘要：

智能小车的测控系统是小车设计中的关键技术之一，灵敏完备的测控系统可以有效提高智能小车运行的稳定性，介绍了智能自主寻迹小车测控系统的整体架构和软硬件设计过程。以飞思卡尔M9S12XS128微处理器作为小车的控制核心，采用红外光电传感器采集路径信息，微处理器根据路径信息和小车当前状态采用脉冲宽度调制（PWM）方式对驱动电机和舵机进行控制。优良的控制算法对智能小车寻迹的准确性和稳定性起着关键的作用，文中采用模糊比例-积分-微分（PID）控制策略对直流电机的转速进行控制，利用双P控制算法控制智能小车舵机的转向；测试结果表明，智能小车运行快速平稳，能够自主准确寻迹。

关键词： 智能小车     测控系统     模糊PID控制     双P控制算法    

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Application of a Novel Fuzzy Clustering Method Based on Chaos Immune Evolutionary Algorithm for Edge

《机械工程前沿（英文）》 2006年 第1卷 第1期   页码 85-89 doi: 10.1007/s11465-005-0023-6

摘要：

A novel fuzzy clustering method based on chaos immune evolutionary algorithm (CIEFCM) is presented to solve fuzzy edge detection problems in image processing. In CIEFCM, a tiny disturbance is added to a filial generation group using a chaos variable and the disturbance amplitude is adjusted step by step, which greatly improves the colony diversity of the immune evolution algorithm (IEA). The experimental results show that the method not only can correctly detect the fuzzy edge and exiguous edge but can evidently improve the searching efficiency of fuzzy clustering algorithm based on IEA.

关键词： disturbance amplitude     disturbance     diversity     generation     processing    

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Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

《机械工程前沿（英文）》 2010年 第5卷 第2期   页码 149-156 doi: 10.1007/s11465-010-0008-y

摘要： With the automation development of manufacturing processes, artificial intelligence technology has been gradually employed to increase the automation and intelligence degree in quality control using statistical process control (SPC) method. In this paper, an SPC method based on a fuzzy adaptive resonance theory (ART) neural network is presented. The fuzzy ART neural network is applied to recognize the special disturbance of the manufacturing processes based on the classification on the histograms, which shows that the fuzzy ART neural network can adaptively learn the features of the histograms of the quality parameters in manufacturing processes. As a result, the special disturbance can be automatically detected when a feature of the special disturbance starts to appear in the histograms. At the same time, combined with spectrum analysis of the autoregressive model of quality parameters, the fuzzy ART neural network can also be utilized to adaptively detect the abnormal patterns in the control chart.

关键词： statistical process control (SPC)     fuzzy adaptive resonance theory (ART)     histogram     control chart     time series analysis    

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Gained switching-based fuzzy sliding mode control for a discrete-time underactuated robotic system with

Hui LI, Ruiqin LI, Jianwei ZHANG

《机械工程前沿（英文）》 2021年 第16卷 第2期   页码 353-362 doi: 10.1007/s11465-020-0620-4

摘要： This study proposes a gained switching-based discrete-time sliding mode control method to address the chattering issue in disturbed discrete-time systems, which suffer from various unknown uncertainties. Through the new structure of the designed reaching law, the proposed method can effectively increase the convergence speed while guaranteeing chattering-free control. The performance of controlling underactuated robotic systems can be further improved by the adoption of fuzzy logic to perform adaptive online hyper-parameter tuning. In addition, an underactuated robotic system with uncertainties is studied to validate the effectiveness of the proposed reaching law. Results reveal the dynamic performance and robustness of the proposed reaching law in the studied system and prove the proposed method’s superiority over other state-of-the-art methods.

关键词： sliding-mode control     robot control     discrete-time uncertain systems     fuzzy logic    

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Prediction of falling weight deflectometer parameters using hybrid model of genetic algorithm and adaptiveneuro-fuzzy inference system

《结构与土木工程前沿（英文）》   页码 812-826 doi: 10.1007/s11709-023-0940-7

摘要： A falling weight deflectometer is a testing device used in civil engineering to measure and evaluate the physical properties of pavements, such as the modulus of the subgrade reaction (Y1) and the elastic modulus of the slab (Y2), which are crucial for assessing the structural strength of pavements. In this study, we developed a novel hybrid artificial intelligence model, i.e., a genetic algorithm (GA)-optimized adaptive neuro-fuzzy inference system (ANFIS-GA), to predict Y1 and Y2 based on easily determined 13 parameters of rigid pavements. The performance of the novel ANFIS-GA model was compared to that of other benchmark models, namely logistic regression (LR) and radial basis function regression (RBFR) algorithms. These models were validated using standard statistical measures, namely, the coefficient of correlation (R), mean absolute error (MAE), and root mean square error (RMSE). The results indicated that the ANFIS-GA model was the best at predicting Y1 (R = 0.945) and Y2 (R = 0.887) compared to the LR and RBFR models. Therefore, the ANFIS-GA model can be used to accurately predict Y1 and Y2 based on easily measured parameters for the appropriate and rapid assessment of the quality and strength of pavements.

关键词： falling weight deflectometer     modulus of subgrade reaction     elastic modulus     metaheuristic algorithms    

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

Moulay Rachid DOUIRI, Mohamed CHERKAOUI

《能源前沿（英文）》 2013年 第7卷 第4期   页码 456-467 doi: 10.1007/s11708-013-0264-8

摘要： In this paper, three intelligent approaches were proposed, applied to direct torque control (DTC) of induction motor drive to replace conventional hysteresis comparators and selection table, namely fuzzy logic, artificial neural network and adaptive neuro-fuzzy inference system (ANFIS). The simulated results obtained demonstrate the feasibility of the adaptive network-based fuzzy inference system based direct torque control (ANFIS-DTC). Compared 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 electromagnetic torque and stator flux ripples, and incurs much shorter execution times and hence the errors caused by control time delays are minimized. The validity of the proposed methods is confirmed by simulation results.

关键词： adaptive neuro-fuzzy inference system (ANFIS)     artificial neural network     direct torque control (DTC)     fuzzy logic     induction motor    

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Load frequency control in deregulated power system with wind integrated system using fuzzy controller

Yajvender Pal VERMA, Ashwani KUMAR

《能源前沿（英文）》 2013年 第7卷 第2期   页码 245-254 doi: 10.1007/s11708-012-0218-6

摘要： This paper presents the analysis of load frequency control (LFC) of a deregulated two-area hydro-thermal power system using fuzzy logic controller, with doubly fed induction generators (DFIGs) integrated into both the control areas. The deregulation of power sector has led to the formation of new companies for generation, transmission and distribution of power. The conventional two-area power system is modified to study the effects of the bilateral contracts of companies on the system dynamics. Deregulation creates highly competitive and distributed control environment, and the LFC becomes even more challenging when wind generators are also integrated into the system. The overall inertia of the system reduces, as the wind unit does not provide inertia and isolates from the grid during disturbances. The DFIGs integrated provide inertial support to the system through modified inertial control scheme, and arrests the initial fall in frequency after disturbance. The inertial control responds to frequency deviations, which takes out the kinetic energy of the wind turbine for improving the frequency response of the system. To enhance the participation of the doubly fed induction generator (DFIG) in the frequency control, optimal values of the speed control parameters of the DFIG-based wind turbine have been obtained using integral square error (ISE) technique. The dynamics of the system have been obtained for a small load perturbation, and for contract violation using fuzzy controller.

关键词： frequency regulation     fuzzy controller     de-regulated power system     doubly fed induction generator (DFIG)     bilateral contract    

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Doubly-fed induction generator drive based WECS using fuzzy logic controller

Abdelhak DIDA,Djilani BEN ATTOUS

《能源前沿（英文）》 2015年 第9卷 第3期   页码 272-281 doi: 10.1007/s11708-015-0363-9

摘要： The purpose of this paper is to improve the control performance of the variable speed, constant frequency doubly-fed induction generator in the wind turbine generation system by using fuzzy logic controllers. The control of the rotor-side converter is realized by stator flux oriented control, whereas the control of the grid-side converter is performed by a control strategy based on grid voltage orientation to maintain the DC-link voltage stability. An intelligent fuzzy inference system is proposed as an alternative of the conventional proportional and integral (PI) controller to overcome any disturbance, such as fast wind speed variation, short grid voltage fault, parameter variations and so on. Five fuzzy logic controllers are used in the rotor side converter (RSC) for maximum power point tracking (MPPT) algorithm, active and reactive power control loops, and another two fuzzy logic controllers for direct and quadratic rotor currents components control loops. The performances have been tested on 1.5 MW doubly-fed induction generator (DFIG) in a Matlab/Simulink software environment.

关键词： fuzzy logic     wind turbine     vector control     doubly-fed induction generator (DFIG)    

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Control algorithm of a servo platform

Shouyong XIE, Xiwen LI, Shuzi YANG, Mingjin YANG,

《机械工程前沿（英文）》 2010年 第5卷 第3期   页码 353-355 doi: 10.1007/s11465-010-0098-6

摘要： According to the characteristics of the movement of a special-purpose three-axis servo platform, this paper presents an improved grey prediction proportional integral derivative (PID) control algorithm. Different weights at different time are given to different sampling moments in the algorithm, and the time meanings of the sample data are paid more attention. Simulation results show that the performance of response and stability of the platform of the improved algorithm is better than that of the traditional one. The control algorithm meets all requirements of the control system of the special-purpose three-axis servo platform.

关键词： grey prediction     proportional integral derivative (PID) control     improved algorithm     weight     servo platform    

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Fuzzy cascade control based on control’s history for superheated temperature

WANG Guangjun, LI Gang, SHEN Shuguang

《能源前沿（英文）》 2007年 第1卷 第3期   页码 285-289 doi: 10.1007/s11708-007-0040-8

摘要： To address the characteristics of the large delay and uncertainty of superheated temperature, a new cascade control system is presented based on control’s history. Based on the analysis of the control objects’ dynamic characteristics, historical control information (substituting for the deviation change rate) is used as the basis for decision-making of the fuzzy control. Therefore, the changing trend of the controlled variable can be accurately reflected. Furthermore, a proportional component is introduced, the advantages of PID and fuzzy controllers are integrated, and the structure weaknesses of conventional fuzzy controllers are overcome. Simulation shows that this control method can effectively reduce the adverse impact of the delay on control effects and, therefore, exhibit strong adaptability by comparing the superheated temperature control system by this controller with PID and conventional fuzzy controllers.
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Assessment of a fuzzy logic based MRAS observer used in a photovoltaic array supplied AC drive

Bhavnesh KUMAR, Yogesh K CHAUHAN, Vivek SHRIVASTAVA

《能源前沿（英文）》 2014年 第8卷 第1期   页码 81-89 doi: 10.1007/s11708-014-0295-9

摘要： In this paper a fuzzy logic (FL) based model reference adaptive system (MRAS) speed observer for high performance AC drives is proposed. The error vector computation is made based on the rotor-flux derived from the reference and the adaptive model of the induction motor. The error signal is processed in the proposed fuzzy logic controller (FLC) for speed adaptation. The drive employs an indirect vector control scheme for achieving a good closed loop speed control. For powering the drive system, a standalone photovoltaic (PV) energy source is used. To extract the maximum power from the PV source, a constant voltage controller (CVC) is also proposed. The complete drive system is modeled in MATLAB/Simulink and the performance is analyzed for different operating conditions.

关键词： induction motor drive     fuzzy logic (FL) control     model reference adaptive system (MRAS)     photovoltaic (PV) array     vector control    

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标题 作者 时间 类型 操作

Application of fuzzy logic control algorithm as stator power controller of a grid-connected doubly-fed

Ridha CHEIKH, Arezki MENACER, Said DRID, Mourad TIAR

期刊论文

Semi-active fuzzy control of Lali Cable-Stayed Bridge using MR dampers under seismic excitation

Sajad JAVADINASAB HORMOZABAD, Amir K. GHORBANI-TANHA

期刊论文

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

LIU Hongyi, WANG Fei, WANG Lei

期刊论文

Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing

Reza TEIMOURI, Hamed SOHRABPOOR

期刊论文

智能自主寻迹小车测控系统的研究与设计

王玲,张强,李雪梅

期刊论文

Application of a Novel Fuzzy Clustering Method Based on Chaos Immune Evolutionary Algorithm for Edge

期刊论文

Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

期刊论文

Gained switching-based fuzzy sliding mode control for a discrete-time underactuated robotic system with

Hui LI, Ruiqin LI, Jianwei ZHANG

期刊论文

Prediction of falling weight deflectometer parameters using hybrid model of genetic algorithm and adaptiveneuro-fuzzy inference system

期刊论文

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

Moulay Rachid DOUIRI, Mohamed CHERKAOUI

期刊论文

Load frequency control in deregulated power system with wind integrated system using fuzzy controller

Yajvender Pal VERMA, Ashwani KUMAR

期刊论文

Doubly-fed induction generator drive based WECS using fuzzy logic controller

Abdelhak DIDA,Djilani BEN ATTOUS

期刊论文

Control algorithm of a servo platform

Shouyong XIE, Xiwen LI, Shuzi YANG, Mingjin YANG,

期刊论文

Fuzzy cascade control based on control’s history for superheated temperature

WANG Guangjun, LI Gang, SHEN Shuguang

期刊论文

Assessment of a fuzzy logic based MRAS observer used in a photovoltaic array supplied AC drive

Bhavnesh KUMAR, Yogesh K CHAUHAN, Vivek SHRIVASTAVA

期刊论文