关键词：
Power line communication;De-noising;Spread spectrum;Chaotic parameter modulation;Wavelet transform
摘要：
As a medium of signal transmission, communication using power line offers a convenient and inexpensive solution for multimedia signal transmission and control applications. This paper aims to present a de-noising scheme which is a combination between chaotic parameter modulation and wavelet transform in power line communications (PLC). The proposed communication scheme is based on two key ideas. The first concept consists of the use of the parameter modulation based on chaotic sequence in order to minimize interference caused by the power line and to secure the transmission information. The second idea consists of the use of wavelet transform based on modulus maxima to reduce the noise from a chaotic sequence. Performance analyses such as signal-to-noise (SNR), root mean squared error (RMSE) and bit error rate (BER) illustrate the superior communication performance of the proposed PLC de-noising scheme based on chaotic parameter modulation and wavelet transform.
关键词：
active power filter (APF);compensation;genetic algorithm optimization method;harmonic current;internal model control;inverter;power electronics;power system;prediction control;support vector machine
摘要：
A new control method for active power filters using support vector machine (SVM) is presented. In the strategy, SVM is employed to model and predict future harmonic compensating current, it has the advantages of nonexistence of local minima solutions, automatic choice of model complexity and good generalization performance. Based on the model output, Genetic algorithm optimization method is adopted to produce proper value of control vector, this value is adequately modulated by means of a space vector PWM modulator which generate proper gating patterns of the inverter switches to maintain tracking of reference current. The SVM based predictive algorithm is used in internal model control scheme to compensate for process disturbances, measurement noise and modeling errors. The proposed method is applied to the control of a shunt active power filter, simulation results show SVM based predictive controller is more effective and feasible than PI control or digit adaptive control.
摘要：
Interfering noise of power line is one of the important factors, which affects the quality of power line communication. In wavelet denoising methods, the most popularly used is nonlinear wavelet transform thresholding method. But in some cases, such as in the neighborhood of discontinuities of signal, the wavelet transform thresholding methods may exhibit Pseudo-Gibbs phenomena. Translation invariant wavelet denoising is an improvement for this method. It can not only suppress Pseudo-Gibbs phenomena, but also diminish RMSE between original signal and improving SNR. Simulated experiment shows that translation invariant wavelet denoising method is better than thresholding denoising method.
会议名称：
2nd IEEE Conference on Industrial Electronics and Applications(ICIEA 2007)(第二届IEEE工业电子与应用国际会议)
会议时间：
2007-05-23
会议地点：
哈尔滨
摘要：
A novel approach for online measurement of fouling in condenser is proposed in this paper. In the approach, terminal temperature difference is chosen to reflect fouling state, diagonal recurrent neural network is employed to approximate off-design condition terminal temperature difference, which separates the influence imposed by fouling on terminal temperature difference from other factors. In order to make the measurement model more compact and accurate, an adaptive dynamic back propagation algorithm is proposed to obtain the optimum number of hidden layer neurons. Based on the approach, an experimental system is developed and experiment on an actual condenser is carried out. The results show the approach measures the fouling correctly, and is more effective than thermal resistance method or heat transfer coefficient method.
会议名称：
Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence
会议时间：
Beijing, China
会议论文集名称：
Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence
关键词：
equiripple FIR digital filters;linear-phase;neural network;optimal design
摘要：
An equiripple FIR linear-phase digital filters design approach is proposed based on a novel neural network optimization technique. Its goal is to minimize the weight square-error function in the frequency domain. The design solution is presented as a parallel algorithm to approximate the desired frequency response specification, and the weight coefficients are updated according to error function. Thus, the proposed approximation method can avoid the overshoot phenomenon which may happen near the pass-band and stop-band edge of the designed filter, and may make a fast calculation of the filter's coefficients possible. Several optimal design examples are given and the performance comparison between the proposed design approach with some conventional methods, and the results show that the proposed neural network method can easily achieve higher design accuracy.
作者机构：
[樊绍胜] College of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410077, China;[王耀南] College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
通讯机构：
College of Electrical and Information Engineering, Changsha University of Science and Technology, China
作者机构：
[樊绍胜; 王耀南] Coll. of Elec. and Info. Eng., Hunan Univ., Changsha 410082, China;[樊绍胜] Coll. of Elec. and Info. Eng., Changsha Univ. of Sci. and Technol., Changsha 410077, China
通讯机构：
Coll. of Elec. and Info. Eng., Hunan Univ., China
作者机构：
[樊绍胜] College of Electric and Information Eng., Changsha University of Sciences and Technology, Changsha 410077, China;[王耀南] College of Electric and Information Eng., Hunan University, Changsha 410082, China
通讯机构：
[Fan, S.-S.] C;College of Electric and Information Eng., Changsha University of Sciences and Technology, China
作者机构：
[樊绍胜] College of Electrical and Information Eng, Changsha University of Sciences and Technology, Changsha 410077, China;[王耀南] College of Electrical and Information Eng, Hunan University, changsha 410082, China
通讯机构：
[Fan, S.-S.] C;College of Electrical and Information Eng, Changsha University of Sciences and Technology, China
作者机构：
[王耀南; 樊绍胜] Coll. of Elec. and Info. Eng., Hu'nan Univ., Changsha 410082, China;[樊绍胜] Coll. of Elec. and Info. Eng., Changsha Univ of Sci. and Technol., Changsha 410077, China
通讯机构：
Coll. of Elec. and Info. Eng., Hu'nan Univ., China
摘要：
Viscosity is one of the key quantities in Rubber mixing process, online measurement of viscosity is very difficult to achieve. To cope with this problem, a soft sensing approach based on fuzzy modeling is proposed. During fuzzy modeling, T-S fuzzy model is employed to approximate the non-linearity of rubber mixing process, an improved Gustafon-Kessel fuzzy clustering algorithm based on similarity assessing is proposed to determine the optimum number of clusters. All these techniques make the fuzzy model simple and accurate. Based on it, test on BB370 internal mixer is carried out. The results show the proposed approach provides more accurate viscosity prediction than mathematical modeling approach. Compared with laboratory measurement, the error is small and acceptable. It improves production efficiency greatly and lays down the foundation for optimal control of viscosity.
关键词：
diagonal recurrent neural network;predictive control;branch-and-bound optimization;active power filter
摘要：
A diagonal recurrent neural network based predictive control strategy for active power filter is presented in this paper. In the strategy, diagonal recurrent neural network is employed to predict future harmonic compensating current. In order to make the predictive model compact and accurate, an adaptive dynamic back propagation algorithm is proposed to obtain the optimum number of hidden layer neurons. Based on the model output, branch-and-bound optimization method is adopted, which generates proper gating patterns of the inverter switches to maintain tracking of reference current without time delay. The model predictive algorithm is used in internal model control scheme to compensate for process disturbances, measurement noise and modeling errors. The proposed control strategy is applied to compensate the harmonic produced by the variable non-linear load. Simulation results show the diagonal recurrent neural network based predictive controller gives better harmonic compensation performance than digital adaptive controller.
会议名称：
4th International Power Electronics and Motion Control Conference (IPEMC 2004)
会议时间：
AUG 14-16, 2004
会议地点：
Xian Jiaotong Univ, Xian, PEOPLES R CHINA
关键词：
fuzzy model predictive control;T-S model;optimization;ACEG excitation control
摘要：
Alternating Current excitation generators (ACEG) can adjust the active power and inactive power flexibly and improve the stability of power system. The key to enhance the power system's stability is to choose appropriate ACEG's excitation control method. Conventional excitation controllers are unable to perform optimally over the full range of operation conditions and disturbances, due to the highly complex, non-linear nature of power systems. In this paper, Fuzzy model predictive control is proposed to cope with the problem. T-S fuzzy model is employed to appropriate the non-linear object. The fuzzy model is derived from input-output data by means of product-space fuzzy clustering, similarity driven rule base simplification is applied to detect and merges compatible fuzzy sets in the model and a new validity measure is adopted to determine the number of clusters. All these techniques make the fuzzy model transparent and accurate. The critical element in fuzzy model predictive control is the nonconvex optimization problem, iterative optimization techniques are mostly slow due to computational complexity, this hamper its application to fast system. In order to solve the problem, Branch-and-bound optimization method is adopted. The fuzzy model predictive algorithm is used in internal model control scheme to compensate for process disturbances, measurement noise and modeling errors. Simulation test under large disturbance at various operating points is made. The results show the fuzzy model based predictive controller is effective and feasible. It performs well over a wide range of system disturbance and improves dynamic characteristic of ACEG system.
