Fuzzy Adaptive Variable Structure Control of Speed Process of DC Motor

The load changed of motor affects normal run. If it is not adjusted, the state of motor will become poor, while it affects steady of the system. This paper presents an efficient method for the motor speed controlling, it applies Tacagi-Sugeno's method that each linear submodels are connected for fuzzy algorithm, an algorithm of the fuzzy model identifying and fuzzy control is fulfilled through whole nonlinear model which are replaced with local linear models. It makes speed of motor to maintain steady, and variable structure control is applied to guarantee performance of dynamic flowing for process controlled, the design of stability and robustness is proposed in the scheme. Practice running results show that it is efficient that uncertain dynamic processes are controlled.     

A fuzzy fusion approach to gabor transform optimal channels for facial expression recognition

According to its characteristics of multi-direction and multi-scale, Gabor wavelet is divided into 13 channels. Due to different contributions of different channels to the recognition rate, a fuzzy integral fusion approach for facial expression recognition is proposed based on optimal channels. Firstly, three optimal channels are selected according to three proposed principles. And then Gabor features of facial expressional images through those optimal channels are extracted with the dimensions reduction. Finally, each optimal channel is used as a classifier and three classifiers are fused based on multi-classifier combination with fuzzy integral. With the results on JAFFE database, it is found that the recognition rate of the proposed algorithm is 94.41%, which verifies the effectiveness of the proposed algorithm.     

插电式混合动力汽车纯电动行进间启动发动机的平顺性控制

针对单电机插电式混合动力汽车在纯电动行进间电动机启动发动机时由于系统输出转矩变化进而引起整车冲击的问题,分析得到发动机点火时刻的不同及离合器接合状态的不同是造成转矩波动的原因。在此基础上,提出了基于离合器主、从动盘转速差和电机角加速度为输入量的离合器压力模糊控制的混合动力汽车模式切换动态协调控制策略,并对比了发动机目标转速点火和怠速转速点火的控制效果。最后通过台架试验以及实车道路试验对提出的控制策略进行了验证。结果表明,基于目标转速点火的协调控制策略能减小整车的冲击度。     

Fuzzy webpage text classification algorithm combined with improved NMF

An item-document weight matrix representing the web pages could be generated by constructing the vector space model. Since the efficiency of direct classification through the high-dimensional matrix is relatively low, a fuzzy webpage text classification algorithm combined with improved nonnegative matrix factorization (NMF) is presented. Firstly, the original high-dimensional data are mapped into the low-dimensional semantic space via an iterative normalized compression NMF(NCMF) to reduce the complexity of the problem. Secondly, in order to solve the problem of categorizing ambiguous words by using deterministic matrices, fuzzy logic is incorporated into the classification model, where the fuzzy categorization set of the document is constructed with the fuzzy membership degree between features and categories. Comparative experiment results demonstrate the proposed classification algorithm possesses higher accuracy and better time performance.     

Image edge detection algorithm in fuzzy domain

An image edge detection algorithm in fuzzy domain is proposed, which combines adaptive fuzzy enhancement and multi direction fuzzy morphology to detect the edges of fuzzy image. The adaptive fuzzy enhancement method enhances the fuzzy image within blocks with sliding windows to avoid losses of the real edges resulting from enhancing with single threshold for the whole image and lead strong adaptive ability to image region variance. The multi direction fuzzy mathematical morphology operates on the enhanced fuzzy image with structure elements of multiple different directions to extract the real edges with directionality and restrain non directional noise. Experiments show the algorithm can detect fuzzy image edge effectively with strong antinoise ability.     

An edge detection method based on a good point set genetic algorithm

In order to improve the convergence rate of genetic algorithms based on edge detection, a novel edge detection method based on a good point set genetic algorithm (GGA) was proposed. The proposed method designed the crossover operation with the theory of good point set in which the progeny inherits the common genes of the parents which represent its family so as to improve the convergence rate of the genetic algorithm. Furthermore, before the algorithm was used for edge detection, the feature space of the image grey level was transformed into the feature space of the fuzzy entropy. Dissimilarity enhancement processing next was applied to the image by using a fuzzy entropy theory to filter the non edge pixels so as to reduce the scale of the solution domain. This approach offered another efficient way to improve the convergence rate. Experimental results show the proposed algorithm performs very well in terms of convergence rate. The detected edge image is well localized, thin, and robustly resistant to noise.     

饲草高粱区域试验新杂交种综合评价

采用模糊数学综合评判方法,综合评价了2003年国家饲草高粱杂交种区域试验材料。结果表明,6个饲草高粱杂交种中,其中晋草1号、健宝两个品种以每公顷产量、丰产素质为主,包括抗病性、抗倒性、株高在内的综合性状明显优于对照皖草2号,达到优良的评价标准,其综合指标值分别比对照增加17.51％和15.95％。辽草1号、苏波丹综合性状比对照稍有减产,但减产幅度不大;综合评价为较好或一般,润宝1号、润宝2号比对照减产幅度很大,综合评价为较差。模糊数学评判方法,客观的反映了品种的综合特性,克服了仅用产量指标评价品种优劣的不足,对新品种的审定、推广都具有积极重要的意义。     

Application of fuzzy Neural Networks to Evaluation of Transversal Economic Benefits

A new method for evaluation of transversal economic benefits is researched by fuzzy neural networks, BP algorithm is used to learn the connection weights of the fuzzy neural networks and partitions of fuzzy subsets. It has been shown by the modeling and evaluating results about the economic benefit index system of ten enterprises that the method has reinforcement learning properties and universalized capabilities. with respect to modeling and evaluating of nonlinear systems which have some uncertainties, the method is available.     

Application and Research on Fuzzy Cluster with Sintering Quanlity

The sintering parameters, such as sinter trolley speed, stuff thickness and ignition temperature etc. have important influence on sinter section image character distribution, and the sinter chemical ingredient have complicated nolinear relation with sintering section image characters. The paper applied Mixed-F statistic analysis to determine the optimal class number of Fuzzy cluster of sintering section radiant image, and fuzzy partition entropy analysis to verify whether the class number is optimal. It is be proved that the algorithm is right and effective, and its application is helpful for the online forecasting sintering FeO range.     

An ALgorithm of the Second Kind Fuzzy Reliability

Based on L.A.Zadeh's idea of fuzzy probability operation in his language probability which space is fuzzy probability,the concrete algorithm of the second kind fuzzy reliability of engineering structure/system is researched.The calculating equation of the fuzzy probabiliy of the second kind fuzzy reliability is given out by using the extension principle for fuzzy sets.The fuzzy set decompose theorem,which satesfies the closed probability operation,is given out and proved.The method calculating fuzzy reliability of that structure/system is studied,where the resistance and load effect of the structure/system have probability.The analysis indicates that the calculation of the second kind fuzzy reliability for a structure/system can be transformed into a series of solving optimum programming.The result of the example indicates the rationality of above algorithm.     

A fuzzy logic multicasting algorithm for ad hoc networks

To increase the multicasting efficiency of Ad hoc networks, a fuzzy logic multicasting algorithm (FLMA) is proposed. FLMA adopts the fuzzy logic to tolerate the imprecise information caused by dynamic network topology. The two input variables of the fuzzy logic system are the relative degree of the additional coverage node number and the relative degree of the residual energy. The deferring time of rebroadcast is the output variable of the fuzzy logic system, which is used to optimize the priority of the nodes to rebroadcast. FLMA reduces the redundant retransmission and the chance of the contention and collision, while balances the energy consumption of the nodes. Simulation results reveal that the FLMA achieves better performance than BCAST in terms of the network lifetime, average end-to-end delay, the average number of drops per node and the throughput.     

模糊控制系统的垂直切换判决算法分析

针对模糊控制系统中切换时延较长和切换次数较多的问题,研究了一种基于模糊控制系统的垂直切换判决算法。在基于信号强度判决时将RSS作为门限值,提高系统判决能力;同时,将网络参数和服务类型作为判决因素,结合层次分析法引入并行的模糊控制系统,缩短了切换判决的时间、选择适合用户的最佳网络,做出垂直切换。仿真结果表明,该算法减少了切换次数,降低了切换时延,增强了系统的性能。与传统的切换算法相比较,该算法对切换的判决因素考虑的更全面,兼顾了用户终端的使用环境及成本问题,有效地保证了网络的服务质量。     

Generalized Damage Reliability and Sensitivity Analysis on Rolled-Concrete Gravity Dam

Based on fuzzy self-adapting stochastic damage model, the characteristics of generalized damage stress field on material crack tip are studied. The results express that the numerical algorithm is reliable. Sensitivity of rolled-concrete gravity dam under fuzzy-stochastic damage gaining is implemented by considering the spatial variation of material parameters. It is found that the compression strength of rolled-concrete is the governing index on gravity dam reliability. The activation simulations on fuzzy self-adapting stochastic damage model were carried by adopting different fuzzy distributions, which indicated the governing characteristics of the distribution on generalized damage evolution of rock-like material.     

Wavelet Edge Detection Method Based-on Multi-scale Fuzzy Logic

A novel edge detection algorithm is proposed by implementing fuzzy image enhancement at different scales.The implement of this algorithm can reduce the negative influence bring from the non-maximum suppression algorithm which select only one threshold.The success of the approach depends on the selection of a general fuzzy operator(GFO) for the enhancement of contrast of region after smoothing of image at different scales.Consequently,it is more obvious that coarse intensity changes are obtained at a large scale whereas the fine details of intensity changes are obtained at a small scale.A pretty performance is obtained by used this work.     

Drift error compensation algorithm for fiber optic gyro based on T-S fuzzy modeling

A drift error nonlinear compensation algorithm for Fiber Optic Gyro (FOG) is presented based on T-S fuzzy model with the antecedent parameters identified by G-K clustering algorithm and the error model of T-S fuzzy model with the consequent parameters identified by least square algorithm. The computed results show that this model can compensate the original data effectively, while the error principles of FOG do not need to be understood well. Comparing with the original data, compensation with linear fitting and compensation with neural network, the absolute error of the proposed model reduces by 99%, 96% and 10%, respectively. The error variance reduces by 99%, 98% and 20%, respectively. The results indicate that this proposed algorithm can be simply operated with high precision and easy to realize in engineering.     

A New Method of Diesel Engine Fuel System Fault Diagnosis

A method of diesel engine fuel system fault diagnosis based on wavelet transform and fuzzy C-means clustering is presented. Five characteristic parameters of reflecting fault state are distilled with wavelet transform of pressure wave of high-pressure oil pipe of diesel. The theory and generic approach of fuzzy C-means clustering algorithm (FCM) is given, and the validity of evaluating fuzzy clustering making use of partition coefficient, partition entropy and parting coefficient is pointed out. Identification of fault mode can be completed utilizing standard fault character modes established by FCM algorithm, and calculating and comparing the similarity degree between this standard mode and sample. The arithmetic is applied to all kinds of typical faults diagnose in the diesel engine fuel system. Measuring results indicate that the precision of fault diagnosis is increased with the analysis of wavelet and FCM.     

Fuzzy Transportation Problem and Its Hybrid Intelligent Algorithm

The authors investigate a more practical transportation problem under fuzzy environment, that is , capacities of supplies and demands in the transportation problem are fuzzy variables. To obtain a directive decision, the authors construct a mathematical model for the fuzzy transportation problem based chance constrained programming and dependent chance programming in fuzzy environment. In addition, since there are many complex fuzzy variables in the mathematical model, the authors design the genetic algorithm to solve the model based on fuzzy simulation. Finally, they give a numerical example to show the efficiency of the algorithm.     

A Self-Learing Chinese Character Recognition System

A method using possibility theory and fuzzy logic is introduced. Possibility functions of each feature are determined during training. Methods of fuzzy logic are used to combine the possibility of different features. This Chinese character recognition system consists of a pre-classifier and a two-level fine classifier. In order to handle deviations of the characters,a fuzzification of features is introduced. This method is used to develop single-font classifiers. The whole system consists of a font-classifiers and four single-font-classifiers.     

Fault diagnosis of rotating machinery based on fuzzy clusteringoptimized by chaos embedded particle swarm optimization

A method of weighted fuzzy clustering optimized by chaos embedded particle swarm algorithm(CPSO) is put forward and applied in vibration fault diagnosis of rotating machinery. In the method, CPSO is used to displace the traditional stochastic-gradient algorithm to optimize parameters of weighted fuzzy C-means (WFCM). The best clustering num and clustering centers are automatically attained according to clustering validity function. The experimental results show that the method effectively increases the convergence velocity and precision of WFCM and so does the correctness rate of fault diagnosis for rotating machinery.     

Intelligent Control of the Nonlinear Seismic Response of a 3 Story Benchmark Building

Intelligent materials, control devices and intelligent control algorithm research and development in recent years have opened a new world for seismic resistance and disaster reduction in civil engineering. We designed and fabricated a new piezoelectric friction damper. In our research, we regarded the piezoelectric friction damper as the control device. We proposed a fuzzy control algorithm for reducing nonlinear seismic response of a 3 story benchmark building and established the interactive relationships between structural responses and fuzzifier factors, defuzzifier factor. A numerical simulation is carried out to analyze the nonlinear seismic responses of the controlled 3 story benchmark building. The simulation results are compared to those of other control strategies. The results show that the fuzzy control can reduce the nonlinear seismic response of 3 story benchmark building and minimize the structural damage caused by strong earthquakes.