基于改进粒子群优化模糊控制的MPPT算法研究

在光照强度和温度变化时,常规的最大功率点跟踪(MPPT)算法难以快速准确地跟踪光伏系统最大功率点。针对此问题,设计了一种改进粒子群优化算法(PSO)的模糊控制器。首先,依据常规MPPT特性,设计了一种带调整因子的模糊控制算法以快速收敛到最大功率点；然后,采用参数自适应PSO对设计的模糊控制器调整因子进行动态优化。仿真结果表明:所设计的参数自适应PSO优化模糊控制器能快速准确地跟踪最大功率点,保证了MPPT的动态响应速度和稳态精度,提高了光伏系统的工作效率。     

基于预测电流控制的光伏并网系统最大功率点跟踪算法

针对光伏发电的突变性及昼发夜停特性提出一种新型的基于预测电流控制的光伏并网系统最大功率点跟踪(MPPT)算法。根据实际情况考虑光伏阵列的非线性特性,最大功率点周围光伏电压的振荡及逆变器、滤波器的设计等。为了确保系统采用控制算法的稳定性,MPPT的设计应运而生,在此基础上通过改进算法从光伏系统的电压与电流预测基准电流进而控制光伏并网系统。通过与传统的波动相关控制方法对比给出了仿真结果。仿真结果表明:在光照发生突变时,与传统的波动相关控制法相比,提出的改进算法的跟踪速度较之提升9.3%,并能够准确跟踪光伏并网系统最大功率点,且性能稳定可靠。     

永磁直驱风电系统中最大功率点跟踪控制优化的仿真研究

分析了风力机特性、永磁直驱电机模型、变换器控制策略及各种功率跟踪控制算法优缺点,并提出一种基于爬山搜索法的最大功率点跟踪(MPPT)控制方法的优化。在MATLAB/Simulink环境下搭建了永磁直驱风力发电系统模型,仿真分析了控制方法对最大功率点的跟踪效果,结果表明当风机起动及风速变化时MPPT控制方法能够使系统快速稳定在新的工作点,捕获得最大功率。由此验证了改进优化后的控制方法及所搭建模型的准确性与有效性。     

交流光伏水泵系统控制策略

光伏水泵系统具有无污染、全自动等优点,且应用的场合较多,为此设计了一种以TMS320F28335为主控制器的光伏水泵控制系统。控制系统中的三相异步电机调速部分采用基于空间矢量脉宽调制(SVPWM)方式的变压变频(VVVF)控制,最大功率点跟踪部分采用恒定电压法(CVT)和扰动观察法结合最大功率点跟踪(MPPT)技术。试验结果表明系统实现最大功率点跟踪并稳定运行。     

基于变步长与非对称模糊的光伏MPPT控制策略

针对于光伏发电系统的输出特性,容易受到外界变数的影响而出现非对称的强非线性特征,输出的功率会偏离最大输出功率点的现象。分析了最大功率点跟踪的几种常用控制策略的优缺点,对PU曲线进行了分析,提出了非对称模糊与变步长电导增量法相结合的控制策略。这里的变步长电导增量法可以在远离最大功率点两侧时,快速靠近最大功率点,当进一步靠近最大功率点区间附近时,采取非对称模糊控制进行寻优,能够较好地削弱系统在最大功率点周围的振荡现象,提升整个系统的稳定性能。通过MATLAB/Simulink进行建模仿真对比,得出所提的方法有较好的动态性能。     

快速伺服刀架神经网络自适应PID控制

为了提高快速伺服刀架的控制性能,减小跟踪误差,实现正弦网格表面精密加工,提出了基于RBF和BP神经网络的自适应PID控制策略.由仿真结果可以看出,采用基于神经网络的自适应控制算法,使跟踪误差的最大值降低为1.37μm,跟踪误差的绝对均值降低为0.52μm.这两项指标相对与传统PID控制分别降低了28%和40%.     

基于模拟退火粒子群算法的波浪发电系统最大功率跟踪控制

波浪发电系统最大功率点跟踪控制中,传统粒子群算法存在早熟收敛和局部搜索能力不足问题,为此提出基于模拟退火算法的粒子群优化方案。该算法每次更新粒子的速度和位置时,通过比较当前温度下各个粒子的适配值与随机数的大小,从所有粒子中确定全局最优解的替代值,从而使粒子群算法在发生早熟收敛时能够跳出局部最优并快速找到全局最优解。仿真结果表明,与传统粒子群优化算法相比,模拟退火粒子群算法可有效避免波浪发电系统陷入局部最大功率点,并快速实现全局最大功率跟踪,提高了波浪能捕获率。     

导弹气动力/直接力自适应控制分配及优化设计

 建立了具有气动力和直接侧向力混合控制的导弹动力学模型，提出了模糊自适应控制分配与复合控制器优化集成设计方案。设计了基于参考模型的模糊自适应控制分配策略，使气动力/直接力动态分配过程中复合执行机构等效动态特性与参考模型一致。采用进化策略对导弹复合控制系统参数进行了多目标优化设计。仿真结果表明：导弹复合控制系统具有很好的快速大机动跟踪能力，实现了导弹气动力和直接侧向力之间合理的自适应控制分配。     

基于自适应神经模糊推理系统的导弹直/气复合控制系统设计

针对导弹直/气复合控制问题,提出了一种基于自适应神经模糊推理系统的导弹直/气复合控制系统设计方法.首先,建立了直/气复合导弹数学模型.然后,针对常规模糊控制设计严重依赖经验的问题,在模糊控制的基础上引入神经网络,通过样本数据学习建立自适应神经模糊推理系统(ANFIS),并设计了脉冲调宽调频调制器.最后,通过仿真试验验证了所提的控制系统设计方法.仿真结果表明,基于ANFIS的导弹直/气复合控制系统能够快速精确地跟踪加速度指令.     

基于RBF网络辨识的航空发动机模糊神经网络解耦控制

对航空发动机的多变量解耦控制方法进行了研究,提出了一种基于RBF网络辨识的航空发动机模糊神经网络解耦控制方法。该方法利用RBF网络辨识航空发动机的实时模型,为模糊神经网络控制器参数的调整提供了Jacobian信息,解决了模糊神经网络自适应控制器在被控对象不能精确建模情况下应用的问题。仿真结果表明,系统鲁棒性强．在设计点和偏离设计点处,均具有良好的动态特性和解耦特性。     

MPPT of photovoltaic systems using extremum - seeking control

A stability analysis for a maximum power point tracking (MPPT) scheme based on extremum-seeking control is developed for a photovoltaic (PV) array supplying a dc-to-dc switching converter. The global stability of the extremum-seeking algorithm is demonstrated by means of Lyapunov's approach. Subsequently, the algorithm is applied to an MPPT system based on the "perturb and observe" method. The steady-state behavior of the PV system with MPPT control is characterized by a stable oscillation around the maximum power point. The tracking algorithm leads the array coordinates to the maximum power point by increasing or decreasing linearly with time the array voltage. Off-line measurements are not required by the control law, which is implemented by means of an analog multiplier, standard operational amplifiers, a flip-flop circuit and a pulsewidth modulator. The effectiveness of the proposed MPPT scheme is demonstrated experimentally under different operating conditions.     

Feedforward maximum power point tracking of PV systems using fuzzy controller

A feedforward maximum power (MP) point tracking scheme is developed for the interleaved dual boost (IDB) converter fed photovoltaic (PV) system using fuzzy controller. The tracking algorithm changes the duty ratio of the converter such that the solar cell array (SCA) voltage equals the voltage corresponding to the MP point at that solar insolation. This is done by the feedforward loop, which generates an error signal by comparing the instantaneous array voltage and reference voltage. The reference voltage for the feedforward loop, corresponding to the MP point, is obtained by an off-line trained neural network. Experimental data is used for off-line training of the neural network, which employs back-propagation algorithm. The proposed fuzzy feedforward peak power tracking effectiveness is demonstrated through the simulation and experimental results, and compared with the conventional proportional plus integral (PI) controller based system. Finally, a comparative study of interleaved boost and conventional boost converter for the PV applications is given and their suitability is discussed.     

Predictive & Adaptive MPPT Perturb and Observe Method

The perturb and observe (P&O) best operation conditions are investigated in order to identify the edge efficiency performances of this most popular maximum power point tracking (MPPT) technique for photovoltaic (PV) applications. It is shown that P&O may guarantee top-level efficiency, provided that a proper predictive (by means of a parabolic interpolation of the last three operating points) and adaptive (based on the measure of the actual power) hill climbing strategy is adopted. The approach proposed is aimed at realizing, in addition to absolute best tracking performances, high robustness and promptness both in sunny and cloudy weather conditions. The power gain with respect to standard P&O technique is proved by means of simulation results and experimental measurements performed on a low power system. Besides the performance improvements, it is shown that the proposed approach allows possible reduction of hardware costs of analog-to-digital (A/D) converters used in the MPPT control circuitry.     

基于模糊模型的鲁棒自适应重构飞行控制

提出了一种基于模糊模型的歼击机鲁棒自适应重构控制方案。整个控制方案基于T S模糊模型,将歼击机各飞行状态的局部线性调节器与鲁棒自适应神经网络重构控制器相结合,避免了传统的增益预置方法中控制律在不同工作点之间切换造成的参数突变对系统性能的影响,可以保证系统在全局上拥有局部工作点具有的期望性能,证明了重构系统的全局闭环渐近稳定性。所提出的带有补偿项的完全自适应RBF神经网络,通过在线自适应调整RBF神经网络的权重、函数中心和宽度,提高了神经网络的学习能力,同时通过自适应补偿项来在线估计神经网络的近似误差边界,可以有效地在线修正建模误差、外扰及操纵面故障等因素的影响,保证系统的操纵品质。仿真结果表明了所提出方法的有效性。     

Single-phase grid-connected PV system using three-arm rectifier-inverter

A grid-connected photovoltaic (PV) power supply system with on-line voltage regulation capability is presented. It employs the three-arm rectifier-inverter topology with PV modules connected directly on the dc-link. The common-arm is with line-frequency switching and synchronous to the input voltage, aiming for a lower switching loss and decoupling the control of rectifier and inverter portions. As a result, the rectifier and inverter portions can be controlled independently with the rectifier-arm and inverter-arm, respectively. For maximum power point tracking (MPFF) of the PV modules and balancing the power among utility, PV, and the load, a variable dc-link voltage is adopted and controlled by the rectifier-arm based on the MPPT control algorithm. The inverter-arm then regulates the load voltage with good regulation and low distortion. Due to large variation of the dc-link voltage, a feedforward plus feedback control technique with variable gain is developed to keep constant bandwidth of the current loop at any operation condition. Therefore, the performance of the rectifier and inverter portions can be ensured. A system containing a 2 kVA converter and a 1.2 kW PV module is set up, and some experimental results are provided for demonstrating the effectiveness of the proposed method.     

Optimized one-cycle control in photovoltaic grid connected applications

The use of one-cycle control (OCC) for maximum power point tracking (MPPT) and power factor correction (PFC) in grid connected photovoltaic (PV) applications is discussed. Circuit and operating parameters of the one cycle-based controller of a cost-effective single-stage inverter are optimized in order to obtain the best performances of the system under different irradiance levels. Firstly, design constraints are formulated which allow to get a very efficient OCC operation in terms of power extracted from the PV array, stability, and PFC. Afterwards, such constraints are used to perform the parametric optimization of the one cycle controller by means of suitable heuristic approaches. Various selection criteria of the best parameters set under different conditions are discussed and applied. Finally, a customized perturb and observe (P&O) control is applied to the optimized one cycle controlled single-stage inverter in order to perform a real MPPT in presence of varying irradiance conditions. Subjects described here are covered by the Italian Patent Application SA2005A000014-13.07.2005 and PCT Application PCT/IT2005/000747-20.12.2005     

Voltage-based maximum power point tracking control of PV system

Photovoltaic (PV) generators exhibit nonlinear v-i characteristics and maximum power (MP) points that vary with solar insulation. An intermediate converter can therefore increase efficiency by matching the PV system to the load and by operating the solar cell arrays (SCAs) at their maximum power point. An MP point tracking algorithm is developed using only SCA voltage information thus leading to current sensorless tracking control. The inadequacy of a boost converter for array voltage based MP point control is experimentally verified and an improved converter system is proposed. The proposed converter system results in low ripple content, which improves the array performance and hence a lower value of capacitance is sufficient on the solar array side. Simplified mathematical expressions for a PV source are derived. A signal flow graph is employed for modeling the converter system. Current sensorless peak power tracking effectiveness is demonstrated through simulation results. Experimental results are presented to validate the proposed method