期刊文献+
共找到1,032篇文章
< 1 2 52 >
每页显示 20 50 100
ADAPTIVE GENETIC ALGORITHM BASED ON SIX FUZZY LOGIC CONTROLLERS 被引量:3
1
作者 朱力立 张焕春 经亚枝 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2003年第2期230-235,共6页
The performance of genetic algorithm(GA) is determined by the capability of search and optimization for satisfactory solutions. The new adaptive genetic algorithm(AGA) is built for inducing suitable search and optimiz... The performance of genetic algorithm(GA) is determined by the capability of search and optimization for satisfactory solutions. The new adaptive genetic algorithm(AGA) is built for inducing suitable search and optimization relationship. The use of six fuzzy logic controllers(6FLCs) is proposed for dynamic control genetic operating parameters of a symbolic-coded GA. This paper uses AGA based on 6FLCs to deal with the travelling salesman problem (TSP). Experimental results show that AGA based on 6FLCs is more efficient than a standard GA in solving combinatorial optimization problems similar to TSP. 展开更多
关键词 adaptive genetic algorithm fuzzy controller dynamic parameters control TSP
下载PDF
FUZZY GLOBAL SLIDING MODE CONTROL BASED ON GENETIC ALGORITHM AND ITS APPLICATION FOR FLIGHT SIMULATOR SERVO SYSTEM 被引量:14
2
作者 LIU Jinkun HE Yuzhu 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2007年第3期13-17,共5页
To alleviate the chattering problem, a new type of fuzzy global sliding mode controller (FGSMC) is presented. In this controller, the switching gain is estimated by fuzzy logic system based on the reachable conditio... To alleviate the chattering problem, a new type of fuzzy global sliding mode controller (FGSMC) is presented. In this controller, the switching gain is estimated by fuzzy logic system based on the reachable conditions of sliding mode controller(SMC), and genetic algorithm (GA) is used to optimize scaling factor of the switching gain, thus the switch chattering of SMC can be alleviated. Moreover, global sliding mode is realized by designing an exponential dynamic sliding surface. Simulation and real-time application for flight simulator servo system with Lugre friction are given to indicate that the proposed controller can guarantee high robust performance all the time and can alleviate chattering phenomenon effectively. 展开更多
关键词 Sliding mode control Chattering free fuzzy control genetic algorithm Flight simulator
下载PDF
Genetic algorithm and particle swarm optimization tuned fuzzy PID controller on direct torque control of dual star induction motor 被引量:13
3
作者 BOUKHALFA Ghoulemallah BELKACEM Sebti +1 位作者 CHIKHI Abdesselem BENAGGOUNE Said 《Journal of Central South University》 SCIE EI CAS CSCD 2019年第7期1886-1896,共11页
This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different he... This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance. 展开更多
关键词 dual star induction motor drive direct torque control particle swarm optimization (PSO) fuzzy logic control genetic algorithms
下载PDF
Fuzzy-second order sliding mode control optimized by genetic algorithm applied in direct torque control of dual star induction motor 被引量:1
4
作者 Ghoulemallah BOUKHALFA Sebti BELKACEM +1 位作者 Abdesselem CHIKHI Moufid BOUHENTALA 《Journal of Central South University》 SCIE EI CAS CSCD 2022年第12期3974-3985,共12页
The direct torque control of the dual star induction motor(DTC-DSIM) using conventional PI controllers is characterized by unsatisfactory performance, such as high ripples of torque and flux, and sensitivity to parame... The direct torque control of the dual star induction motor(DTC-DSIM) using conventional PI controllers is characterized by unsatisfactory performance, such as high ripples of torque and flux, and sensitivity to parametric variations. Among the most evoked control strategies adopted in this field to overcome these drawbacks presented in classical drive, it is worth mentioning the use of the second order sliding mode control(SOSMC) based on the super twisting algorithm(STA) combined with the fuzzy logic control(FSOSMC). In order to realize the optimal control performance, the FSOSMC parameters are adjusted using an optimization algorithm based on the genetic algorithm(GA). The performances of the envisaged control scheme, called G-FSOSMC, are investigated against G-SOSMC, G-PI and BBO-FSOSMC algorithms. The proposed controller scheme is efficient in reducing the torque and flux ripples, and successfully suppresses chattering. The effects of parametric uncertainties do not affect system performance. 展开更多
关键词 double star induction machine direct torque control fuzzy second order sliding mode control genetic algorithm biogeography based optimization algorithm
下载PDF
Manipulator Neural Network Control Based on Fuzzy Genetic Algorithm 被引量:1
5
作者 崔平远 Yang Guojun 《High Technology Letters》 EI CAS 2001年第1期63-66,共4页
The three-layer forward neural networks are used to establish the inverse kinematics models of robot manipulators. The fuzzy genetic algorithm based on the linear scaling of the fitness value is presented to update th... The three-layer forward neural networks are used to establish the inverse kinematics models of robot manipulators. The fuzzy genetic algorithm based on the linear scaling of the fitness value is presented to update the weights of neural networks. To increase the search speed of the algorithm, the crossover probability and the mutation probability are adjusted through fuzzy control and the fitness is modified by the linear scaling method in FGA. Simulations show that the proposed method improves considerably the precision of the inverse kinematics solutions for robot manipulators and guarantees a rapid global convergence and overcomes the drawbacks of SGA and the BP algorithm. 展开更多
关键词 Inverse kinematics Neural networks fuzzy control genetic algorithm Fitness function
下载PDF
Type-2 Fuzzy Logic Controllers Based Genetic Algorithm for the Position Control of DC Motor 被引量:1
6
作者 Mohammed Zeki Al-Faiz Mohammed S. Saleh Ahmed A. Oglah 《Intelligent Control and Automation》 2013年第1期108-113,共6页
Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of ... Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of this article lies in the application of a genetic algorithm interval type-2 fuzzy logic controller (GAIT2FLC) in the design of fuzzy controller for the position control of DC Motor. The entire system has been modeled using MATLAB R11a. The performance of the proposed GAIT2FLC is compared with that of its corresponding conventional genetic algorithm type-1 FLC in terms of several performance measures such as rise time, peak overshoot, settling time, integral absolute error (IAE) and integral of time multiplied absolute error (ITAE) and in each case, the proposed scheme shows improved performance over its conventional counterpart. Extensive simulation studies are conducted to compare the response of the given system with the conventional genetic algorithm type-1 fuzzy controller to the response given with the proposed GAIT2FLC scheme. 展开更多
关键词 Type-2 fuzzy LOGIC controlLER genetic algorithm DC MOTOR
下载PDF
SELF-LEARNING FUZZY CONTROL RULES USING GENETIC ALGORITHMS
7
作者 方建安 邵世煌 《Journal of China Textile University(English Edition)》 EI CAS 1995年第1期7-13,共7页
This papcr presents a new genetic algorithms(GAs)-based method for self-learniag fuzzy control rules. An improved GA is used to learn to optimally select the fuzzy membership functions of the linguistic labels in the ... This papcr presents a new genetic algorithms(GAs)-based method for self-learniag fuzzy control rules. An improved GA is used to learn to optimally select the fuzzy membership functions of the linguistic labels in the condition portion of each rule, and to automatically generate fuzzy control actions under each condition. The dynamics of the controlled system is unknown to the GA. The only information for evaluating performance is a failure signal indicating that the controlled system is out of control. We compare its performance with that of other learning methods for the same problem. We also examine the ability of the algorithm to adapt to changing conditions. Simulation results show that such an approach for self-learning fuzzy control rules is both effective and robust. 展开更多
关键词 genetic algorithm SELF-LEARNING fuzzy control.
下载PDF
Optimization of Membership Function for Fuzzy Control Based on Genetic Algorithm and Its Applications
8
作者 Shi Fei Zheng Fangjing (School of Automation) 《Advances in Manufacturing》 SCIE CAS 1998年第4期37-42,共6页
In this paper, a simple and practicable algorithm for optimization of membership function (MF) is proposed. As it is known that MF is very important in the fuzzy control. Unfortunately, to find, especially to optimize... In this paper, a simple and practicable algorithm for optimization of membership function (MF) is proposed. As it is known that MF is very important in the fuzzy control. Unfortunately, to find, especially to optimize MF is always rather complex even difficult. So, to study and develop an effectual aglorithm for MF optimization is a good topic. Allow for the inner advantages of genetic algorithm (GA), it is adopted in the algorithm .The principle and executive procdeure are first presented. Then it is applied in the fuzzy control system of a typical plant. Results of real time run show that the control strategy is encouraging, and the developed algorithm is practicable. 展开更多
关键词 fuzzy control membership function (MF) genetic algorithm (GA) OPTIMIZATION
下载PDF
Fuzzy Control of Chaotic System with Genetic Algorithm
9
作者 方建安 郭钊侠 邵世煌 《Journal of Donghua University(English Edition)》 EI CAS 2002年第3期58-62,共5页
A novel approach to control the unpredictable behavior of chaotic systems is presented. The control algorithm is based on fuzzy logic control technique combined with genetic algorithm. The use of fuzzy logic allows fo... A novel approach to control the unpredictable behavior of chaotic systems is presented. The control algorithm is based on fuzzy logic control technique combined with genetic algorithm. The use of fuzzy logic allows for the implementation of human "rule-of-thumb" approach to decision making by employing linguistic variables. An improved Genetic Algorithm (GA) is used to learn to optimally select the fuzzy membership functions of the linguistic labels in the condition portion of each rule, and to automatically generate fuzzy control actions under each condition. Simulation results show that such an approach for the control of chaotic systems is both effective and robust. 展开更多
关键词 fuzzy control CHAOTIC system genetic algorithm reinforcement learning.
下载PDF
Self-learning Fuzzy Controllers Based On a Real-time Reinforcement Genetic Algorithm
10
作者 方建安 苗清影 +1 位作者 郭钊侠 邵世煌 《Journal of Donghua University(English Edition)》 EI CAS 2002年第2期19-22,共4页
This paper presents a novel method for constructing fuzzy controllers based on a real time reinforcement genetic algorithm. This methodology introduces the real-time learning capability of neural networks into globall... This paper presents a novel method for constructing fuzzy controllers based on a real time reinforcement genetic algorithm. This methodology introduces the real-time learning capability of neural networks into globally searching process of genetic algorithm, aiming to enhance the convergence rate and real-time learning ability of genetic algorithm, which is then used to construct fuzzy controllers for complex dynamic systems without any knowledge about system dynamics and prior control experience. The cart-pole system is employed as a test bed to demonstrate the effectiveness of the proposed control scheme, and the robustness of the acquired fuzzy controller with comparable result. 展开更多
关键词 fuzzy controller self-learning REAL time reinforcement genetic algorithm
下载PDF
Calculation of impact factor of vibrator oscillation in offset printing based on fuzzy controller and genetic algorithm
11
作者 初红艳 Yang Junjing Cai Ligang 《High Technology Letters》 EI CAS 2015年第1期15-21,共7页
In the inking system of an offset printing press,a vibrator roller distributes ink not only in the circumferential direction but also in the axial direction.In the control process,if ink amount is determined only by t... In the inking system of an offset printing press,a vibrator roller distributes ink not only in the circumferential direction but also in the axial direction.In the control process,if ink amount is determined only by the dot area coverage without considering the impact of vibrator roller's oscillation,the printing colour quality will be reduced.This paper describes a method of calculating the impact factor of vibrator roller' s oscillation.First,the oscillation performance is analyzed and sample data of impact factor is got.Then,a fuzzy controller used for the calculation of the impact factor is designed,and genetic algorithm is used to optimize membership functions and obtain the fuzzy control rules automatically.This fuzzy controller can be used to calculate impact factors for any printing condition,and the impact factors can be used for ink amount control in printing process and it is important for higher printing colour quality and lowering ink and paper waste. 展开更多
关键词 offset printing colour quality control impact factor fuzzy control genetic algorithm
下载PDF
Intelligent vehicle lateral controller design based on genetic algorithmand T-S fuzzy-neural network
12
作者 RuanJiuhong FuMengyin LiYibin 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2005年第2期382-387,共6页
Non-linearity and parameter time-variety are inherent properties of lateral motions of a vehicle. How to effectively control intelligent vehicle (IV) lateral motions is a challenging task. Controller design can be reg... Non-linearity and parameter time-variety are inherent properties of lateral motions of a vehicle. How to effectively control intelligent vehicle (IV) lateral motions is a challenging task. Controller design can be regarded as a process of searching optimal structure from controller structure space and searching optimal parameters from parameter space. Based on this view, an intelligent vehicle lateral motions controller was designed. The controller structure was constructed by T-S fuzzy-neural network (FNN). Its parameters were searched and selected with genetic algorithm (GA). The simulation results indicate that the controller designed has strong robustness, high precision and good ride quality, and it can effectively resolve IV lateral motion non-linearity and time-variant parameters problem. 展开更多
关键词 intelligent vehicle genetic algorithm fuzzy-neural network lateral control robustness.
下载PDF
Neutrosophic Adaptive Clustering Optimization in Genetic Algorithm and Its Application in Cubic Assignment Problem 被引量:1
13
作者 Fangwei Zhang Shihe Xu +2 位作者 Bing Han Liming Zhang Jun Ye 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第3期2211-2226,共16页
In optimization theory,the adaptive control of the optimization process is an important goal that people pursue.To solve this problem,this study introduces the idea of neutrosophic decision-making into classical heuri... In optimization theory,the adaptive control of the optimization process is an important goal that people pursue.To solve this problem,this study introduces the idea of neutrosophic decision-making into classical heuristic algorithm,and proposes a novel neutrosophic adaptive clustering optimization thought,which is applied in a novel neutrosophic genetic algorithm(NGA),for example.The main feature of NGA is that the NGA treats the crossover effect as a neutrosophic fuzzy set,the variation ratio as a structural parameter,the crossover effect as a benefit parameter and the variation effect as a cost parameter,and then a neutrosophic fitness function value is created.Finally,a high order assignment problem in warehousemanagement is taken to illustrate the effectiveness of NGA. 展开更多
关键词 Neutrosophic fuzzy set heuristic algorithm genetic algorithm intelligent control warehouse operation
下载PDF
A Fuzzy-based Adaptive Genetic Algorithm and Its Case Study in Chemical Engineering 被引量:5
14
作者 杨传鑫 颜学峰 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2011年第2期299-307,共9页
Considering that the performance of a genetic algorithm (GA) is affected by many factors and their rela-tionships are complex and hard to be described,a novel fuzzy-based adaptive genetic algorithm (FAGA) combined... Considering that the performance of a genetic algorithm (GA) is affected by many factors and their rela-tionships are complex and hard to be described,a novel fuzzy-based adaptive genetic algorithm (FAGA) combined a new artificial immune system with fuzzy system theory is proposed due to the fact fuzzy theory can describe high complex problems.In FAGA,immune theory is used to improve the performance of selection operation.And,crossover probability and mutation probability are adjusted dynamically by fuzzy inferences,which are developed according to the heuristic fuzzy relationship between algorithm performances and control parameters.The experi-ments show that FAGA can efficiently overcome shortcomings of GA,i.e.,premature and slow,and obtain better results than two typical fuzzy GAs.Finally,FAGA was used for the parameters estimation of reaction kinetics model and the satisfactory result was obtained. 展开更多
关键词 fuzzy logic controller genetic algorithm artificial immune system reaction kinetics model
下载PDF
Fuzzy Control System of Hydraulic Roll Bending Based on Genetic Neural Network 被引量:2
15
作者 JIAChun-yu LIUHong-min ZHOUHui-feng 《Journal of Iron and Steel Research International》 SCIE CAS CSCD 2005年第3期22-27,共6页
For nonlinear hydraulic roll bending control, a new fuzzy intelligent control method was proposed based on the genetic neural network. The method taking account of dynamic and static characteristics of control system ... For nonlinear hydraulic roll bending control, a new fuzzy intelligent control method was proposed based on the genetic neural network. The method taking account of dynamic and static characteristics of control system has settled the problems of recognizing and controlling the unknown, uncertain and nonlinear system successfully, and has been applied to hydraulic roll bending control. The simulation results indicate that the system has good performance and strong robustness, and is better than traditional PID and neural-fuzzy control. The method is an effective tool to control roll bending force with increased dynamic response speed of control system and enhanced tracking accuracy. 展开更多
关键词 genetic algorithm neural network fuzzy control hydraulic roll bending SHAPE
下载PDF
Genetic-fuzzy HEV control strategy based on driving cycle recognition 被引量:1
16
作者 邢杰 He Hongwen Zhang Xiaowei 《High Technology Letters》 EI CAS 2010年第1期39-44,共6页
A genetic-fuzzy HEV control strategy based on driving cycle recognition (DCR) was built. Six driving cycles were selected to represent different traffic conditions e.g. freeway, urban, suburb. A neural algorithm was... A genetic-fuzzy HEV control strategy based on driving cycle recognition (DCR) was built. Six driving cycles were selected to represent different traffic conditions e.g. freeway, urban, suburb. A neural algorithm was used for traffic condition recognition based on ten parameters of each driving cycle. The DCR was utilized for optimization of the HEV control parameters using a genetic-fuzzy approach. A fuzzy logic controller (FLC) was designed to be intelligent to manage the engine to work in the vicinity of its optimal condition. The fuzzy membership function parameters were optimized using the genetic algorithm (GA) for each driving cycle. The result is that the DCR_ fuzzy controller can reduce the fuel consumption by 1. 9%, higher than only CYC _ HWFET optimized fuzzy (0.2%) or CYC _ WVUSUB optimized fuzzy (0.7%). The DCR_ fuzzy method can get the better result than only optimizing one cycle on the complex real traffic conditions. 展开更多
关键词 HEV control strategy driving cycle recognition (DCR) fuzzy logic control (FLC) neural algorithm optimization genetic algorithm (GA) optimization
下载PDF
A New Fuzzy Adaptive Genetic Algorithm 被引量:6
17
作者 房磊 张焕春 经亚枝 《Journal of Electronic Science and Technology of China》 2005年第1期57-59,71,共4页
Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while kee... Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while keeping the overall population size constant. The simulation results of function optimization show that with the proposed algorithm, the phenomenon of premature convergence can be overcome effectively, and a satisfying optimization result is obtained. 展开更多
关键词 adaptive genetic algorithm fuzzy logic controller dynamic parameters control population sizes
下载PDF
LINGUISTIC SELF-ORGANIZING PROCESS CONTROLLER USING GENETIC ALGORITHM
18
作者 方远 丁纪凯 《Journal of China Textile University(English Edition)》 EI CAS 1997年第2期11-15,共5页
A linguistic self-organizing controller using genetic algorithm is presented, whose control policy is able to generate, develop and improve. The scaling factors can be chosen automatically.Optimizing the scaling facto... A linguistic self-organizing controller using genetic algorithm is presented, whose control policy is able to generate, develop and improve. The scaling factors can be chosen automatically.Optimizing the scaling factors by genetic algorithm instead of trial or experimental method which is often used in conventional linguistic self-organizing controller eliminates the drawback of an exhausive search of the GE*GC*GU space by human operator, and also produces the better system response and a set of better control rules. A number of simulations on linear dynamic systems as well as non-linear systems such as second order process with a random disturbance, third order process with time lags and the cart-pole balancing problem etc. are described in this paper, which shows that the controller has strong adaptive properties and gives better performance than that of the conventional linguistic self-organizing controller. 展开更多
关键词 geneticalgorithm fuzzyconlrol linguisticself-organizingcontrol
下载PDF
A New Neuro-Fuzzy Adaptive Genetic Algorithm
19
作者 ZHU Lili ZHANG Huanchun JING Yazhi(Faculty 302,Nanjing University of Aeronautics and Astronautics,Nanjing 210016 China) 《Journal of Electronic Science and Technology of China》 2003年第1期63-68,共6页
Novel neuro-fuzzy techniques are used to dynamically control parameter settings ofgenetic algorithms (GAs).The benchmark routine is an adaptive genetic algorithm (AGA) that uses afuzzy knowledge-based system to contro... Novel neuro-fuzzy techniques are used to dynamically control parameter settings ofgenetic algorithms (GAs).The benchmark routine is an adaptive genetic algorithm (AGA) that uses afuzzy knowledge-based system to control GA parameters.The self-learning ability of the cerebellar modelariculation controller (CMAC) neural network makes it possible for on-line learning the knowledge onGAs throughout the run.Automatically designing and tuning the fuzzy knowledge-base system,neuro-fuzzy techniques based on CMAC can find the optimized fuzzy system for AGA by the renhanced learningmethod.The Results from initial experiments show a Dynamic Parametric AGA system designed by theproposed automatic method and indicate the general applicability of the neuro-fuzzy AGA to a widerange of combinatorial optimization. 展开更多
关键词 genetic algorithm fuzzy logic control CMAC neural network adaptive parameter control
下载PDF
Fuzzy traffic signal control with DNA evolutionary algorithm 被引量:2
20
作者 毕云蕊 路小波 +1 位作者 孙哲 曾唯理 《Journal of Southeast University(English Edition)》 EI CAS 2013年第2期207-210,共4页
In order to optimize the signal control system, this paper proposes a method to design an optimized fuzzy logic controller (FLC) with the DNA evolutionary algorithm. Inspired by the DNA molecular operation character... In order to optimize the signal control system, this paper proposes a method to design an optimized fuzzy logic controller (FLC) with the DNA evolutionary algorithm. Inspired by the DNA molecular operation characteristics, the DNA evolutionary algorithm modifies the corresponding genetic operators. Compared with the traditional genetic algorithm (GA), the DNA evolutionary algorithm can overcome weak local search capability and premature convergence. The parameters of membership functions are optimized by adopting the quaternary encoding method and performing corresponding DNA genetic operators. The relevant optimized parameters are combined with the FLC for single intersection traffic signal control. Simulation experiments shows the better performance of the FLC with the DNA evolutionary algorithm optimization. The experimental results demonstrate the efficiency of the nrotmsed method. 展开更多
关键词 DNA evolutionary algorithm genetic algorithm(GA) fuzzy control traffic signal control
下载PDF
上一页 1 2 52 下一页 到第
使用帮助 返回顶部