Simulation of the constant modulus blind equilibrium algorithm with variable step size based on the mean square error

The mathematic models and basic theory of constant modulus algorithm (CMA) for blind channel equalization are introduced. An improved algorithm with variable step size is proposed based on CMA. The improved algorithm uses the mean square error (MSE) to obtain the new variable step size to solve the contradiction between the convergence rate and accuracy in traditional CMA with fixed step. To smooth the MSE learning curve for easy comparison, an ensemble average technique is used to analyze the performance of convergence with different step sizes. The theoretical analysis and the simulation results show that the improved algorithm is superior to the traditional constant modulus(CM) in terms of convergence speed and residual error.     

A preventive control model for static voltage stability considering the power constraints of weak branches

The voltage instability of power system often occurs when the active power on one or more weak branches exceeds its transfer capability. A preventive control model for static voltage stability is proposed using the active power transfer capability of weak branches as static voltage stability constraints. A local line based voltage stability index is used to determine the critical contingencies, weak branches and transfer capability of each weak branch. A static security analysis method, which is based on DC power flow equations, is used to establish the non linear active power flow expressions on weak branches following each critical contingency. The active power constraints on weak branches can be obtained from the active power flow expressions and transfer capabilities of weak branches. A quadratic optimal model for preventive control including the proposed active power constraints on weak branches is presented. The simulation results for IEEEE14 bus system and IEEE118 bus system demonstrate the correctness and effectiveness of the proposed preventive control model.     

OPTIMAL REACTIVE POWER FLOW BY SENSITIVITY METHOD

A new approach based on sensitivity method for the optimal power flow is presented in the paper. This method has the following advantages: it is suitable to solve a 200-node power system on the microcomputer; the convergence is easy to reach and the computation speed is quick; it is possible to reduce 8-14% power loss and to get maximum economic benefit by using this method; in power system dispatch center it can be used as an on-line voltage and reactive power control program to keep good voltage level. The proposed method has been proved successful by IEEE 118-node test system and the several real power systems such as 49-node, 61-node, 99-node and 200-node systems.     

Application of digital phase-locked loop and filtering technique in PWM rectifier

VHS-ADC high speed digital signal processing platform based on MATLAB and FPGA could be used to build three-phase voltage source rectifier with space voltage vector PWM(SVPWM).The initial phase of coordinate transformation from three phase static coordinate to two phase static coordinate which is called Park transformation and from two phase rotating reference frame to two phase static coordinate is uncertain. There existed noise in acquiring grid voltage and current. Digital phase-locked loop is added to follow the frequency and phase of grid voltage, FIR filter is added to process signal and reduce the interference. External voltage control loop, internal current control loop and the model of coordinate transformation are designed on the VHS-ADC platform. The small power experiment is conducted to verify the stability and feasibility of the control system. The experimental results show that the digital phase-locked loop and FIR digital filter can be applied to three-phase voltage source rectifier.     

PID Control for Multivariable System Based on Ameliorative RBF Neural Networks

Aiming at systems which are of characteristics of multi-input and multi-output, nonlinearity and time-variation in the industrial control fields, this paper presents a intelligent PID control method based on ameliorative RBF neural networks, which constructs RBF neural networks identifier on-line and identifies a controlled object on-line by means of adopting the nearest neighbor-clustering algorithm, and adjusts parameters of PID controller on-line and realizes decoupiing control of multivariable, nonlinear and time-variation system. The simulation result indicates that the controller can get parameters which are optimal under some control law, it makes the decoupled system, compared to the PID control method based on the conventional RBF neural networks, has perfect dynamic and static performances, possesses the advantages of high precision, quick response speed and is of great adaptability and robustness.     

Application of Wavelet & Multi-Resolution Analysis to Detection of the Time of PN Code Acquisition

In the field of CDMA system, DS-SS technology has been used widely. Thereby, a great deal research on acquisition method of PN code is based on DS-SS. In the traditional way, the power detection method of judgment is used widely. Based on the characteristic of PN code acquired signal (namely BPSK signal or QPSK signal) and characteristic of un acquired signal (namely white Gaussian noise), this paper introduces the wavelet detection method of PN code acquisition time. Meanwhile, the performance of wavelet threshold is also studied. In the end, the statistics of parameters in this detection method is made. The result indicates that the wavelet & multi resolution has practical value in the signal processing.     

Influence of MUD on the System Capability of CDMA

In CDMA communication system, the relativities between users result in Multiple Access Interference (MAI). With the increase of users, MAI becomes the main jam of broadband CDMA communication system. Multi-User Detection (MUD) is the most important technology of anti-jamming in the broadband CDMA communication system, which can eliminates MAI effectively by using the information of all user signals to detection single. This paper analyze the expression of system capability without MUD and with MUD, and puts forward the way to increase system capability by using MUD. Then the influence of MUD on CDMA system capability is discussed by MATLAB emulation. Basing analysis and emulation, the conclusion is got: the higher the MUD efficiency, the better the improvement of CDMA system capability; under the same MUD efficiency, the lower data rate, the smaller inter-cell interference, the lower the ratio of bit energy to power spectrum, the better the improvement of CDMA system capability.     

Distributed Power Flow Method Based on Ward Equivalent

With interconnecting and developing of power system, the problem of power flow computation on dispersed data resource need to be solved. A new distributed computation method of power flow based on Ward equivalent is presented. According to master-slaver splitting principle, multi-area interconnected power system is divided into master-slaver areas. Boundary buses in different areas are defined as different bus-types. Neighborhood areas are equivalent by Ward equivalent principle, and the equivalent injection power and equivalent impedance are worked out. Power flows from master area to slaver areas are solved by Newton method, and the equivalent injection power and equivalent impedance on the boundary are modified by their solutions. The process above repeats until to convergence. The proposed distributed power flow method takes full advantage of the information of power, voltage, network configuration in neighborhood areas, so it is better on convergence and quality of solution. The proposed algorithm is testified by IEEE 14-bus system and a practical 181-bus system.     

THE DECOUPLJNG CALCULATION OF MULTI-AREA POWER SYSTEM LOAD FREQUENCY CONTROL

The calculating burden of the decoupling judgement of multi-area power system load frequeney centrel is very large by tranditional methods. This paper changcs the decoupling judgement problem into a minimum cost network flow problem. The solution algorithm is out-of-kilter . algorithm which is characterized by simple manipaultion, fast and reliable convergence. In the paper, we discuss and calculate the decoupling problem of two arca power system load frequency control. The results show that the proposed approach is feasible and effective.     

Analysis on starting characteristic of continuously variable transmission system with reflux power

Considering on the characteristics of the transmission system and some key units of continuously variable transmission system with reflux power, a dynamic simulation model and a control strategy are established. The design method of the new continuously variable transmission system is verified by simulation. The simulation result on this continuously variable transmission system shows that the rotating speed of the driven plate can rise up rapidly during starting clutch engagement, and the sliding friction power is lower than 3 kJ which is nearly equal to one third of the friction power of the traditional vehicle.     

Design of Minitype Gas Dynamotor System Based on AVR

This paper introduces the software and hardware designs of minitype gas dynamotor system based on ATMEGA8L singlechip. Step motor is used as the executing equipment in the system. The maximum power of the dynamotor is 5 kW. First, the speed of the dynamotor is sampled, and then the signal is send to the ATMEGA8L singlechip, so as to drive the step motor, thus to control the accelerograph, and to control the frequency of the 9atput voltage, and the main arithmetic is the PID algorithm. The result shows that this technology can be used and extended in producion.     

A new pattern recognition method of gas sensor array detection

BP neural network based gas sensor array detection pattern recognition has some disadvantages, such as slow convergence and local minimum problem. A modified immune neural network model which combines BP algorithm and immune algorithm is proposed to enhance global search capability and improve the performance of the neural network model. Orthogonal test is adopted to design the study samples of neural network. This ensures the accuracy of neural network while reducing the number of samples. The simulation results show that the proposed pattern recognition method solves the cross sensitivity of gas sensor effectively, overcomes the disadvantages of traditional BP neural network and improves the learning speed and detection accuracy.     

A Data Detector Based on Channel Equalizer Designed for the Downlink of CDMA Systems

In code-division multiple-access (CDMA) systems,sub-optimum multi-user or joint detection algorithms have been studied recently, which are mostly designed for the uplink situation. The algorithms are too complex to implement for the downlink situation. The conventional receiver consisting of matched filters is often inefficient in eliminating MAI. The authors propose a data detection algorithm designed for downlink of CDMA systems which introduce channel equalization to eliminate MAI. It consists of a channel equalizer and code matched filter. The equalization algorithm is based on zero forcing (ZF) criterion.The performance of the algorithm is better than metched filter's and its complexity is cower than tunt of sub-optimum multi-user detection.     

Simulation Research of Control Parameters in Induction Motor Vector Control System

In order to obtain the effect rules of control parameters of speed regulator on performance indexes of induction vector-controlled system and the setting rules of control parameters of speed regulator,according to rotor flux oriented control principle,a vector control model of induction motor is established and simulated with the software of Matlab/Simulink.This vector control system is proved that it possesses good static and dynamic performance.This paper analyzes the effect of control parameters' variations of speed regulator on performance indexes and gives simulation results.     

Optimization of power distribution with annealing genetic algorithm

The traditional genetic algorithm easily converges to slow speed, leads to a poor climbing ability and shows weak static stability and robustness when seeking a solution. On the basis of analyzing multi-constrained and multi-objective optimization model o     

Direction of Arrival Estimation for CDMA Communication Signal

MUSIC algorithm is often applied in direction of arrival estimation of communication signal or radar signal. But the traditional MUSIC algorithm is not applicable in the presence of the correlational signals. Combining with time average processing, an algotithm of two-dimensional space-time average is suggested on the base of space average technic especially for the DOA estimation of CDMA communication signal. A detaild analysis and a conclusion about this improved algorithm is presented. Ensuring the accurary of the estimation an efficient decrease in quantity of operation is achieved with the algorithm, so it is more suitable for real-time processing. The efficiency of the improved algorithm is attested by the emulating results.     

Self-adaptation Optimize BP Neural Network Design Based on the Genetic Algorithms

BP(Back Propagation) Neural networks is in the presence of the local optimization in the Neural networks training.The algorithm have slow convergence and the local convergence problem which impact the neural networks work performance.In order to cover these shortcomings and solves the size's hugeness and the low efficiency of the net problem in the traditional NN designing,the action principles of BP-Neural network's structure are analyzed,and a new method is formed which is confirmed from the Enhance genetic algorithms(EGA).The method can identify network configuration and network training methods.By adopting the number coding,self-adaptable multi-point variations operation,this method can effectively reduce the network size and the network convergence time,increase the network training speed.Tomatoes disease diagnosis examples illustrate the feasibility of this approach.     

Network Partitioning Based on Threshold Search and Dynamic Scatter for Voltage/Var Control

Secondary Voltage Control is a new way of voltage control,firstly the power system is divided into many control areas whose electric distance is remote.The partitioning method of secondary voltage control is studied and an algorithm that combination of the threshold search and dynamic scatter is presented.That is,the initial grouping scheme is obtained by searching the threshold value.The dynamic scatter method then is used to regulate and improve the initial results.The method is based on system's physical character,it's unnecessary to modify the network's model and analysis the eigenvalue,so the compute rate is fast.Through comparing the method and the traditional methods,this method is proved to be a reasonable and feasible partitioning scheme.     

Bit Allocation Algorithm OFDM Systems Based for Low Voltage Network Transmitted Efficiency

Selfadaptation OFDM is suitable for the low voltage network.To satisfy the request of high speed communication in low voltage network,this paper studies a bit allocation algorithm for low voltage network OFDM systems based transmitted efficiency.And compared with the fix modulate OFDM and fix power OFDM,this algorithm can allocate the power and modulate flexibly and increase the speed.It is very appropriate for the low voltage network application.     

An artificial immunity based predictive method for neural networks and its applications

A radial basis function (RBF) neural network learning algorithm based on immune recognition was proposed to improve the low forecast precision and the slow convergence speed of such networks. In the algorithm, artificial immunity was used to determine the center and width parameters of the Gauss basis function. The recognized data were regarded as antigens and the compression mapping of antigens were taken as antibodies, i.e., the centers of the hidden layer. The recursion least square algorithm (RLS) was employed to determine the output layer weights. The algorithm improved the convergence speed and precision of the RBF neural networks. The model was applied to the blast furnace of a large iron and steel company. The results show that the model has forecast precision far superior to existing models and requires less training time than they do.