基于MATLAB的DSTATCOM控制器仿真研究

配电网电能质量问题日益严重,开发和研制能有效提高供电质量的补偿装置是电力系统研究领域的新热点。针对配电网静止同步补偿器(DSTATCOM)的核心部分——控制器,本文提出了基于d-q变换矢量控制理论的双环控制方法。同时利用MATLAB中的动态仿真工具SIMULINK。建立了配电网静止同步补偿器(DSTATCOM)控制嚣的仿真模型。以含有DSTATCOMM的10／0．4kv的配电系统为例,用S-Function仿真分析了DSTATCOM在负荷变化过程中的动态补偿作用。仿真结果验证了本文所设计的控制方法的可行性及实时性。     

An expert system based on S-transform and neural network for automatic classification of power quality disturbances

In this paper, an S-transform-based neural network structure is presented for automatic classification of power quality disturbances. The S-transform (ST) technique is integrated with neural network (NN) model with multi-layer perceptron to construct the classifier. Firstly, the performance of ST is shown for detecting and localizing the disturbances by visual inspection. Then, ST technique is used to extract the significant features of distorted signal. In addition, an optimum combination of the most useful features is identified for increasing the accuracy of classification. Features extracted by using the S-transform are applied as input to NN for automatic classification of the power quality (PQ) disturbances that solves a relatively complex problem. Six single disturbances and two complex disturbances as well pure sine (normal) selected as reference are considered for the classification. Sensitivity of proposed expert system under different noise conditions is investigated. The analysis and results show that the classifier can effectively classify different PQ disturbances.     

Hybrid signal processing and machine intelligence techniques for detection,quantification and classification of power quality disturbances

This paper presents an advanced signal processing technique known as S-transform (ST) to detect and quantify various power quality (PQ) disturbances. ST is also utilized to extract some useful features of the disturbance signal. The excellent time–frequency resolution characteristic of the ST makes it an attractive candidate for analysis of power system disturbance signals. The number of features required in the proposed approach is less than that of the wavelet transform (WT) for identification of PQ disturbances. The features extracted by using ST are used to train a support vector machine (SVM) classifier for automatic classification of the PQ disturbances. Since the proposed methodology can reduce the features of disturbance signal to a great extent without losing its original property, it efficiently utilizes the memory space and computation time of the processor. Eleven types of PQ disturbances are considered for the classification purpose. The simulation results show that the combination of ST and SVM can effectively detect and classify different PQ disturbances.     

RCMAC-based adaptive control design for brushless DC motors

This paper proposes a recurrent cerebellar model articulation controller (RCMAC)-based adaptive control for brushless DC motors. This control system is composed of a RCMAC and a compensation controller. RCMAC is used to mimic an ideal controller, and the compensation controller is designed to compensate for the approximation error between the ideal controller and RCMAC. The Lyapunov stability theory is utilized to derive the parameter tuning algorithm, so that the uniformly ultimately bound stability of the closed-loop system can be achieved. For comparison, a fuzzy control, an adaptive fuzzy control and the developed RCMAC-based adaptive control are implemented on a field programmable gate array chip for controlling a brushless DC motor. Experimental results reveal that the proposed RCMAC-based adaptive control system can achieve the best tracking performance. Moreover, since the developed RCMAC-based adaptive control scheme uses a hyperbolic tangent function to compensate for the approximation error, there is no chattering phenomenon in the control effort. Thus, the proposed control method is more suitable for real-time practical control applications.     

Hybrid Renewable Energy Source Combined Dynamic Voltage Restorer for Power Quality Improvement

In this paper, the hybrid photovoltaic-thermoelectric generator (PV-TEG) combined dynamic voltage restorer (DVR) system is proposed for the power quality disturbances compensation in a single-phase distribution system. The stable and precise level of input voltage is essential for the smooth and trouble-free operation of the electrically sensitive loads which are connected at the utility side to avoid system malfunctions. In this context, the hybrid PV-TEG energy module combined DVR system is proposed in this paper. With the support of the hybrid energy module, the DVR will perform the power quality disturbances compensation effectively with needed voltage and /or power. In the proposed system, the PV and TEG energy sources are connected electrically in series to produce adequate voltage for the DVR operation and the fractional factor-based variable incremental conduction (FFVINC) maximum power point tracking (MPPT) control algorithm is employed to extract the possible maximum power from the PV array. The intelligent fuzzy logic controller (FLC) is chosen for implementing the MPPT control algorithm. The half-bridge voltage source inverter (VSI) circuit and in-phase voltage compensation technique are used in the DVR for better power quality disturbances compensation. The performance and usefulness of the proposed DVR system are investigated by an extensive simulation study with four different modes of operation, the study results are confirmed that the proposed system promptly identifies the power quality disturbances for compensation. Moreover, the investigation proved that the combined PV and TEG energy module can provide better energy efficiency in converting solar irradiation into electricity.     

基于STM32的在线绝缘监测装置的设计

针对直流电源系统绝缘状况监测不全的问题,提出了基于组合桥的在线绝缘检测方法,以STM32微处理器为核心,设计了硬件构架和软件构架,研制了在线式绝缘监测装置,在满足系统接地和绝缘降低的绝缘状况监测的基础上,实现了交流窜入、直流互窜、电容测量、绝缘预警、母线对地电压补偿和装置自检等功能,现场运行表明了其可行性和有效性。     

基于DSP的DSTATCOM触发系统的实现

基于DSP的SVPWM脉冲信号的产生,并以此脉冲信号触发DSTATCOM装置工作,从而产生期望的无功功率,实现无功补偿的目的。     

基于backstepping方法的电子节气门控制

针对汽车电子节气门的跟踪控制要求,建立了面向控制器设计的非线性模型.采用输入整形(input-shaping)技术对跟踪输入信号进行滤波,应用backstepping方法设计了电子节气门的非线性控制器.将建模误差等不确定性看做加性外部扰动,分析了跟踪误差系统的输入到状态稳定性(input-to-state-stability,ISS),并据此给出了选择控制器参数的指导性准则.仿真实验表明基于backstepping的控制方法能够很好的实现电子节气门的跟踪控制.     

Active disturbance rejection based load frequency control and voltage regulation in power systems

An active disturbance rejection controller (ADRC) is developed for load frequency control (LFC) and voltage regulation respectively in a power system. For LFC, the ADRC is constructed on a three area interconnected power system. The control goal is to maintain the frequency at nominal value (60Hz in North America) and keep tie line power flow at scheduled value. For voltage regulation, the ADRC is applied to a static var compensator (SVC) as a supplementary controller. It is utilized to maintain the voltages at nearby buses within the ANSI C84.1 limits (or ±5% tolerance). Particularly, an alternative ADRC with smaller controller gains than classic ADRC is originally designed on the SVC system. From power generation and transmission to its distribution, both voltage and frequency regulating systems are subject to large and small disturbances caused by sudden load changes, transmission faults, and equipment loss/malfunction etc. The simulation results and theoretical analyses demonstrate the effectiveness of the ADRCs in compensating the disturbances and achieving the control goals.     

Neural-network hybrid control for antilock braking systems

The antilock braking systems are designed to maximize wheel traction by preventing the wheels from locking during braking, while also maintaining adequate vehicle steerability; however, the performance is often degraded under harsh road conditions. In this paper, a hybrid control system with a recurrent neural network (RNN) observer is developed for antilock braking systems. This hybrid control system is comprised of an ideal controller and a compensation controller. The ideal controller, containing an RNN uncertainty observer, is the principal controller; and the compensation controller is a compensator for the difference between the system uncertainty and the estimated uncertainty. Since for dynamic response the RNN has capabilities superior to the feedforward NN, it is utilized for the uncertainty observer. The Taylor linearization technique is employed to increase the learning ability of the RNN. In addition, the on-line parameter adaptation laws are derived based on a Lyapunov function, so the stability of the system can be guaranteed. Simulations are performed to demonstrate the effectiveness of the proposed NN hybrid control system for antilock braking control under various road conditions.     

基于DSP2812的静止无功补偿控制器

针对电力系统中无功补偿装置发展的现状,介绍了一种基于DSP2812的静止无功补偿装置控制器的设计.该控制器充分利用了DSP2812内部资源丰富的特点,即响应速度快、动态性能好,系统结构简单、可靠性高、成本低.试验结果表明,该控制器具有优异的性能,可用于低压系统的动态无功补偿.     

基于扰动补偿的无微分模型参考自适应控制系统设计

针对一类含有参数不确定性和未知非线性扰动的系统,本文提出一种基于扰动补偿的无微分模型参考自适应控制方法,实现系统输出对参考模型输出信号的高精度跟踪.首先,利用被控对象模型信息设计扰动估计器,对系统非线性扰动进行在线估计;其次,基于非线性扰动估计值设计参考模型和无微分参数更新律,构建无微分模型参考自适应控制器,建立基于扰动补偿和状态反馈的自适应控制律,以消除参数不确定性和非线性扰动对系统输出的影响,保证系统输出对参考模型输出的准确跟踪;然后,给出闭环系统误差信号收敛条件和控制器参数整定方法;最后,通过数值仿真验证所提方法的有效性和优越性.     

Combined VMD-SVM based feature selection method for classification of power quality events

Power quality (PQ) issues have become more important than before due to increased use of sensitive electrical loads. In this paper, a new hybrid algorithm is presented for PQ disturbances detection in electrical power systems. The proposed method is constructed based on four main steps: simulation of PQ events, extraction of features, selection of dominant features, and classification of selected features. By using two powerful signal processing tools, i.e. variational mode decomposition (VMD) and S-transform (ST), some potential features are extracted from different PQ events. VMD as a new tool decomposes signals into different modes and ST also analyzes signals in both time and frequency domains. In order to avoid large dimension of feature vector and obtain a detection scheme with optimum structure, sequential forward selection (SFS) and sequential backward selection (SBS) as wrapper based methods and Gram–Schmidt orthogonalization (GSO) based feature selection method as filter based method are used for elimination of redundant features. In the next step, PQ events are discriminated by support vector machines (SVMs) as classifier core. Obtained results of the extensive tests prove the satisfactory performance of the proposed method in terms of speed and accuracy even in noisy conditions. Moreover, the start and end points of PQ events can be detected with high precision.     

Disturbance rejection of battery/ultracapacitor hybrid energy sources

This paper contributes an active control strategy to reject disturbances in hybrid energy source systems applied in hybrid electric vehicles. The disturbances include persistent disturbances introduced by engine torque ripples compensation, and transient disturbances caused by transient load power demands. The disturbance rejection is achieved via singular perturbation theory. The original system is a Port-Controlled Hamiltonian (PCH) system, and the controller is designed based on interconnection and damping assignment. Experimental results verify the effectiveness of the disturbance rejection control.     

PI controller design using ABC algorithm for MPPT of PV system supplying DC motor pump load

Maximum power point tracking (MPPT) is used in photovoltaic (PV) systems to maximize its output power. A new MPPT system has been suggested for PV–DC motor pump system by designing two PI controllers. The first one is used to reach MPPT by monitoring the voltage and current of the PV array and adjusting the duty cycle of the DC/DC converter. The second PI controller is designed for speed control of DC series motor by setting the voltage fed to the DC series motor through another DC/DC converter. The suggested design problem of MPPT and speed controller is formulated as an optimization task which is solved by artificial bee colony (ABC) to search for optimal parameters of PI controllers. Simulation results have shown the validity of the developed technique in delivering MPPT to DC series motor pump system under atmospheric conditions and tracking the reference speed of motor. Moreover, the performance of the ABC algorithm is compared with genetic algorithm for various disturbances to prove its robustness.

     

基于干扰补偿趋近律的离散滑模多周期重复控制

针对离散时间系统的多周期干扰抑制问题,提出一种离散滑模多周期重复控制器设计方法.利用非线性幂次函数设计新型离散趋近律,将周期差分等效干扰以加权形式嵌入到趋近律中,构造带干扰补偿作用的离散趋近律,并据此设计离散滑模多周期重复控制器.为了进行控制器参数整定和表征闭环系统的收敛性能,推导准滑模域边界层的表达式.所提出控制方法既能够消除多周期干扰信号,也能够减小准滑模域边界层.数值仿真验证了所提出控制方法的有效性.     

一种新型DSTATCOM用于电弧炉柔性供电的研究

本文研究一种新型DSTATCOM应用于三相交流电弧炉的柔性供电方法。运用dq矢量变换法,检测冲击性电弧炉负荷的瞬时无功电流;采用电流直接控制法,使DSTATCOM产生无功补偿电流,以此抑制电网电压波动与闪变。应用PI控制使逆变器直流侧电容电压保持稳定,保证DSTATCOM良好的电流跟踪性能。以某钢厂炼钢电弧炉供电系统为背景,在MAT-LAB下对此柔性供电系统进行了仿真。结果表明此新型柔性供电方法能有效地抑制电弧炉引起的电网电压波动与闪变,实现柔性供电的目的。     

RCMAC Hybrid Control for MIMO Uncertain Nonlinear Systems Using Sliding-Mode Technology

A hybrid control system, integrating principal and compensation controllers, is developed for multiple-input-multiple-output (MIMO) uncertain nonlinear systems. This hybrid control system is based on sliding-mode technique and uses a recurrent cerebellar model articulation controller (RCMAC) as an uncertainty observer. The principal controller containing an RCMAC uncertainty observer is the main controller, and the compensation controller is a compensator for the approximation error of the system uncertainty. In addition, in order to relax the requirement of approximation error bound, an estimation law is derived to estimate the error bound. The Taylor linearization technique is employed to increase the learning ability of RCMAC and the adaptive laws of the control system are derived based on Lyapunov stability theorem and Barbalat's lemma so that the asymptotical stability of the system can be guaranteed. Finally, the proposed design method is applied to control a biped robot. Simulation results demonstrate the effectiveness of the proposed control scheme for the MIMO uncertain nonlinear system     

基于FPGA的数字磁罗盘开发

针对电子罗盘的定位导航应用,开发了一种基于现场可编程门阵列(FPGA)作为微控制器的数字磁罗盘,具有成本低、速度快、功耗小的优点。FPGA负责完成对数字磁阻传感器和数字加速度计的数据采集、方位角计算、LED显示以及串口输出等处理。对罗盘的误差来源进行了分析,重点对其中的硬干扰误差进行了补偿修正。为了验证设计效果,对数字磁罗盘实物进行了测试,测试结果表明:磁罗盘在进行误差补偿后,精度范围能够达到1°～2°左右,且长期运行时稳定,可适用于普通导航领域。     

BUCK变换器带恒功率负载反馈精确线性化控制

对BUCK交换器带恒功率负载系统的非线性控制进行了研究.根据恒功率负载的非线性特性,推导出BUCK变换器带恒功率负载的精确线性化反馈控制规律,设计了系统非线性控制器.用SABER软件对控制律进行了仿真,结果表明反馈精确线性化技术可以实现对BUCK变换器带恒功率负载的控制,在电源及负载大范围变化时,保证系统的稳定运行,具有大信号稳定特性.