Indirect Vector Control of Linear Induction Motors Using Space Vector Pulse Width Modulation

Vector control schemes have recently been used to drive linear induction motors(LIM)in high-performance applications.This trend promotes the development of precise and efficient control schemes for individual motors.This research aims to present a novel framework for speed and thrust force control of LIM using space vector pulse width modulation(SVPWM)inverters.The framework under consideration is developed in four stages.To begin,MATLAB Simulink was used to develop a detailed mathematical and electromechanical dynamicmodel.The research presents a modified SVPWM inverter control scheme.By tuning the proportional-integral(PI)controller with a transfer function,optimized values for the PI controller are derived.All the subsystems mentioned above are integrated to create a robust simulation of the LIM’s precise speed and thrust force control scheme.The reference speed values were chosen to evaluate the performance of the respective system,and the developed system’s response was verified using various data sets.For the low-speed range,a reference value of 10m/s is used,while a reference value of 100 m/s is used for the high-speed range.The speed output response indicates that themotor reached reference speed in amatter of seconds,as the delay time is between 8 and 10 s.The maximum amplitude of thrust achieved is less than 400N,demonstrating the controller’s capability to control a high-speed LIM with minimal thrust ripple.Due to the controlled speed range,the developed system is highly recommended for low-speed and high-speed and heavy-duty traction applications.

Recognition Analysis and Simulation Implementation Based on High-Order Cumulants of Wireless Digital Modulation Mode

This paper mainly studies the data characteristics of high order cumulants using digitally modulated signals, and constructs the identification feature parameters that can distinguish the signal modulation type by the high-order cumulants data of the digital modulation signal. Set the identification signal modulation type determination threshold based on the value of the identification feature parameter. The identification feature parameter value of the signal modulation type is compared with the set determination threshold, to realize the recognition of digital modulation signal. This identification method is implemented based on MATLAB design, with a 2ASK (2-ary Amplitude Shift Keying) signal, 4ASK (4-ary Amplitude Shift Keying) signal, 2PSK (2-ary Phase Shift Keying) signal, 4PSK (4-ary Phase Shift Keying) signal, 2FSK (2-ary Frequency Shift Keying) signal, 4FSK (4-ary Frequency Shift Keying) signal. The second, fourth and sixth order cumulants of the six signals were analyzed. Calculate the selected identification feature parameter value and the determination threshold to identify the six signals. The six signals have made MATLAB identification simulation. Simulation results show that this method is feasible and has high recognition rate. Simulation results verify that such recognition methods maintain a high recognition rate under conditions with low signal-to-noise ratio. This identification method can be extended to more MASK (M-ary Amplitude Shift Keying), MPSK (M-ary Phase Shift Keying), MFSK (M-ary Frequency Shift Keying), MQAM (M-ary Quadrature Amplitude Modulation) signal identification.

Cross-phase modulation instability in optical fibres with exponential saturable nonlinearity and high-order dispersion

Utilizing the linear-stability analysis, this paper analytically investigates and calculates the condition and gain spectra of cross-phase modulation instability in optical fibres in the ease of exponential saturable nonlinearity and high-order dispersion. The results show that, the modulation instability characteristics here are similar to those of conventional saturable nonlinearity and Kerr nonlinearity. That is to say, when the fourth-order dispersion has the same sign as that of the second-order one, a new gain spectral region called the second one which is far away from the zero point may appear. The existence of the exponential saturable nonlinearity will make the spectral width as well as the peak gain of every spectral region increase with the input powers before decrease. Namely, for every spectral regime, this may lead to a unique value of peak gain and spectral width for two different input powers. In comparison with the case of conventional saturable nonlinearity, however, when the other parameters are the same, the variations of the spectral width and the peak gain with the input powers will be faster in case of exponential saturable nonlinearity.

Investigation of Mode and Modulation Responses in Semiconductor PS-DFB Lasers:Use of a Vector-Newton Method

A numerical model for steady state analysis and analytical expressions for the AM and FM modulation responses of DFB lasers are presented.The small signal modulation responses of 3 phase shift(PS) DFB is investigated for the first time.A new method(Vector Newton method) to obtain multiple longitudinal mode of DFB lasers is used.It is demonstrated that this method is suitable for obtaining multiple solution of high nonlinear equations.Longitudinal photon density distribution and multiple longitudinal mode of 3PS DFB and simple DFB lasers are analyzed.The results show that modulation response characteristics of 3PS DFB laser is as good as that of DFB,and PS can weaken the longitudinal spatial hole burning (LHSB) effect and is in favor of single longitudinal mode operating of lasers.

Classification using wavelet packet decomposition and support vector machine for digital modulations

To make the modulation classification system more suitable for signals in a wide range of signal to noise rate （SNR）, a feature extraction method based on signal wavelet packet transform modulus maxima matrix （WPTMMM） and a novel support vector machine fuzzy network （SVMFN） classifier is presented. The WPTMMM feature extraction method has less computational complexity, more stability, and has the preferable advantage of robust with the time parallel moving and white noise. Further, the SVMFN uses a new definition of fuzzy density that incorporates accuracy and uncertainty of the classifiers to improve recognition reliability to classify nine digital modulation types （i.e. 2ASK, 2FSK, 2PSK, 4ASK, 4FSK, 4PSK, 16QAM, MSK, and OQPSK）. Computer simulation shows that the proposed scheme has the advantages of high accuracy and reliability （success rates are over 98% when SNR is not lower than 0dB）, and it adapts to engineering applications.

Research of the Unity Theory Between Three-level Space Vector and Carrier-based PWM Modulation Strategy

两电平空间矢量脉宽调制（space vector pulse widthmodulation,SVPWM）与正弦脉宽调制（sinusoidal pulse widthmodulation,SPWM）存有一定的本质关系,对于三电平,在常见的8段式SVPWM序列中可以证明,SVPWM与SPWM本质上也存在某种统一。实际的SVPWM调制中,由于要考虑中点电压平衡、减少谐波等其它性能问题,一般会利用开关冗余状态得到8段以上的开关调制序列。目前的文献中还未曾有对这些情况进行统一性地验证,因此三电平SVPWM与SPWM的统一理论存在一定的不足。研究发现,可通过严格地理论推导将传统意义上的调制波分解为2个子调制波,再进行SPWM调制,可以得到与SVPWM完全吻合的序列。该文在此方法基础上深入研究了8段以上（10、12、14段）的SVPWM调制序列与SPWM的统一。经过严格地理论推导,成功实现了含任意段数的SVPWM序列与SPWM的统一。仿真结果证明了该理论的正确性。

Signal Classification Method Based on Support Vector Machine and High-Order Cumulants

In this paper, a classification method based on Support Vector Machine (SVM) is given in the digital modulation signal classification. The second, fourth and sixth order cumulants of the received signals are used as classification vectors firstly, then the kernel thought is used to map the feature vector to the high dimensional feature space and the optimum separating hyperplane is constructed in space to realize signal recognition. In order to build an effective and robust SVM classifier, the radial basis kernel function is selected, one against one or one against rest of multi-class classifier is designed, and method of parameter selection using cross- validation grid is adopted. Through the experiments it can be concluded that the classifier based on SVM has high performance and is more robust.

Realization of Space Vector Pulse Width Modulation Method Based on DSP

In order to compensate for the deficiency of Sine Pulse Width Modulation（SPWM）, on the base of analyzing the principle of space w tot pulse width modulation and being compared with SPWM, the method of solving working time of adjacent vector and the method of generate space voltage vector were introduced. The experiment to the inverter which consists of IGBT proves that SVPWM centrol algorithm can reduce harmonic effectively, it is beneficial to enhancing the utilization rate of voltage source inverter direct current power supply.

ANFIS Based Space Vector Modulation-DTC for Switched Reluctance Motor Drive

Direct torque control (DTC) of Switched reluctance motor is known straightforward control structure with similar execution to that of field situated control strategies. In any case, the part of ideal determination of the voltage space vector is one of the weakest focuses in a routine DTC drive because of adjustable switching frequency and high torque ripple. In this paper, ideal choice of voltage space vectors is accomplished utilizing ANFIS (Adaptive Neuro Fuzzy Inference System) with space vector Modulation. SVM-DTC gives consistent switching frequency and the proposed ANFIS controller’s structure manages the torque and stator flux error signals through the fuzzy deduction to get a yield that takes the type of space voltage vector. Simulation results accept the proposed evolutionary system with quick torque and flux reaction with minimized torque ripple and flux ripple.

Research on Parallel Interleaved Inverters with Discontinuous Space-Vector Modulation

Parallel converter can significantly increase the capacity of the converter and improve the power quality of AC side, but the circulation which can lead to high switching loss and even damage the devices will easily exist in the direct parallel converters. In this paper, the average model of parallel interleaved inverters system to analyze the circulation current is shown, and the cross current is relevant to DC-bus voltage and the overlap time of zero vectors in the switching period. Based on this observation, a discontinuous space vector modulation without using zero vectors (000) is eliminate and suppress the zero-sequence current to entire system. Finally, the effectiveness of modulation strategy is verified by the simulations in this paper.

Method of Modulation Recognition Based on Combination Algorithm of K-Means Clustering and Grading Training SVM

For the existing support vector machine, when recognizing more questions, the shortcomings of high computational complexity and low recognition rate under the low SNR are emerged. The characteristic parameter of the signal is extracted and optimized by using a clustering algorithm, support vector machine is trained by grading algorithm so as to enhance the rate of convergence, improve the performance of recognition under the low SNR and realize modulation recognition of the signal based on the modulation system of the constellation diagram in this paper. Simulation results show that the average recognition rate based on this algorithm is enhanced over 30% compared with methods that adopting clustering algorithm or support vector machine respectively under the low SNR. The average recognition rate can reach 90% when the SNR is 5 dB, and the method is easy to be achieved so that it has broad application prospect in the modulating recognition.

Modulation recognition of communication signals based on SCHKS-SSVM

A novel modulation recognition algorithm is proposed by introducing a Chen-Harker-Kanzow-Smale (CHKS) smooth function into the C-support vector machine deformation algorithm. A set of seven characteristic parameters is selected from a range of parameters of communication signals including instantaneous amplitude, phase, and frequency. And the Newton-Armijo algorithm is utilized to train the proposed algorithm, namely, smooth CHKS smooth support vector machine (SCHKS-SSVM). Compared with the existing algorithms, the proposed algorithm not only solves the non-differentiable problem of the second order objective function, but also reduces the recognition error. It significantly improves the training speed and also saves a large amount of storage space through large-scale sorting problems. The simulation results show that the recognition rate of the algorithm can batch training. Therefore, the proposed algorithm is suitable for solving the problem of high dimension and its recognition can exceed 95% when the signal-to-noise ratio is no less than 10 dB.

A novel adaptive classification scheme for digital modulations in satellite communication

To make the modulation classification system more suitable for signals in a wide range of signal to noise ratios （SNRs）, a novel adaptive modulation classification scheme is presented in this paper. Differ-ent from traditional schemes, the proposed scheme employs a new SNR estimation algorithm for small samples before modulation classification, which makes the modulation classifier work adaptively according to estimated SNRs. Furthermore, it uses three efficient features and support vector machines （SVM） in modulation classification. Computer simulation shows that the scheme can adaptively classify ten digital modulation types （i.e. 2ASK, 4ASK, 2FSK, 4FSK, 2PSK, 4PSK, 16QAM, TFM, π/4QPSK and OQPSK） at SNRS ranging from 0dB to 25dB and success rates are over 95% when SNR is not lower than 3dB. Accuracy, efficiency and simplicity of the proposed scheme are obviously improved, which make it more adaptive to engineering applications.

MODIFIED QUANTIZATION INDEX MODULATION WATERMARKING ADAPTIVE TO CONTRAST MASKING THRESHOLDS

In this paper,we suggest an adaptive watermarking method to improve both transparence and robustness of quantization index modulation(QIM) scheme. Instead of a fixed quantization step-size,we apply a step-size adapted to image content in each 8×8 block to make a balance of robust extraction and transparent embedding.The modified step-size is determined by contrast masking thresholds of Watson’s perceptual model.From a normalized crossed-correlation value between the original watermark and the detected watermark,we could observe that our method is robust to attacks of additive white Gaussian noise(AWGN),Salt and Pepper noise and Joint Photographic Experts Group(JPEG) compression than the original QIM.By taking into account the contrast insensitivity and visible thresholds of human visual system,the suggested improvement achieves a maximum embedding strength and an appropriate quantization step-size which is consistent with local values of a host signal.

Robust Quantzation Index Modulation VIA Adaptive Watermarking

In this paper,we suggest an adaptive watermarkingmethod to improve both transparence and robustnessof quantization index modulation(QIM)scheme.Instead of a fixed quantization step-size,we apply astep-size adapted to image content in each 8×8block to make a balance of robust extraction andtransparent embedding.The modified step-size isdetermined by contrast masking thresholds ofWatson’s perceptual model.From a normalizedcrossed-correlation value between the original watermarkand the detected watermark,we could observethat our method is robust to attacks of additivewhite Gaussian noise(AWGN),Salt and Peppernoise and Joint Photographic Experts Group(JPEG)compression than the original QIM.By taking intoaccount the contrast insensitivity and visible thresholdsof human visual system,the suggested improvementachieves a maximum embedding strength andan appropriate quantization step-size which is consistentwith local values of a host signal.

Modulation classification based on spectrogram

The aim of modulation classification （MC） is to identify the modulation type of a commtmication signal. It plays an important role in many cooperative or noncooperative communication applications. Three spectrogram-based modulation classification methods are proposed. Their recognition scope and performance are investigated or evaluated by theoretical analysis and extensive simulation studies. The method taking moment-like features is robust to frequency offset while the other two, which make use of principal component analysis （PCA） with different transformation inputs, can achieve satisfactory accuracy even at low SNR （as low as 2 dB）. Due to the properties of spectrogram, the statistical pattern recognition techniques, and the image preprocessing steps, all of our methods are insensitive to unknown phase and frequency offsets, timing errors, and the arriving sequence of symbols.

Lightwave Modulation Techniques for Advanced Modulation Formats

Arbitrary waveform can be synthesized by two orthogonal components: in-phase and quadrature components. Thus, if we can manipulate the two components independently, various complicated modulation can be achieved. This technique is called vector modulation, which is commonly used in wireless radio communication systems where the carrier frequency is lower than 100GHz. On the other hand, in lightwave transmission systems, the carrier frequency is higher than 100THz, and the stability of the signal sources would be much poorer than in radio systems, so that the simplest modulation format (on-off-keying) was often used in commercial systems. However, recently, various modulation techniques such as quadrature amplitude modulation, etc., have been demonstrated by using precise and rapid lightwave control. In this report, we review recent progress in optical vector modulation technologies which can generate highspeed and complicated optical signals. Integrated optical modulators can synthesize multi-level signals in photonic circuits.

Simple Bounded Weight Modules for the Vector Field Lie Algebras of Infinite Rank

In this paper,we classify the simple uniformly bounded weight modules for the vector eld Lie algebra W1 of in nite rank.It turns out that any such modules are intermediate series modules.This result is very di erent from the vector eld Lie algebra Wd of nite rank.

Photovoltaic Models Parameters Estimation Based on Weighted Mean of Vectors

Renewable energy sources are gaining popularity,particularly photovoltaic energy as a clean energy source.This is evident in the advancement of scientific research aimed at improving solar cell performance.Due to the non-linear nature of the photovoltaic cell,modeling solar cells and extracting their parameters is one of the most important challenges in this discipline.As a result,the use of optimization algorithms to solve this problem is expanding and evolving at a rapid rate.In this paper,a weIghted meaN oF vectOrs algorithm(INFO)that calculates the weighted mean for a set of vectors in the search space has been applied to estimate the parameters of solar cells in an efficient and precise way.In each generation,the INFO utilizes three operations to update the vectors’locations:updating rules,vector merging,and local search.The INFO is applied to estimate the parameters of static models such as single and double diodes,as well as dynamic models such as integral and fractional models.The outcomes of all applications are examined and compared to several recent algorithms.As well as the results are evaluated through statistical analysis.The results analyzed supported the proposed algorithm’s efficiency,accuracy,and durability when compared to recent optimization algorithms.