电压源型三相逆变器的模型预测控制策略

为了提高电压源型三相逆变器的控制性能,设计了一种新颖的模型预测控制(MPC)策略.新型MPC控制器使用三相逆变器系统的离散时间域模型来预测所有可能电压矢量生成的负载电流,并选择使所设计的成本函数最小的矢量作为最优矢量输出.成本函数中主要考虑的指标是下一个采样周期的电流误差.利用仿真软件和搭建的三相逆变器样机测试平台开展...     

三电平ANPC逆变器优化开关序列模型预测控制

针对三电平有源中点箝位型(ANPC)逆变器提出一种优化开关序列的模型预测控制(MPC)策略,根据逆变器拓扑结构建立了数学模型,选择最优的开关序列对逆变器进行控制。所提方法改善了传统MPC开关频率不固定和采样频率较高的缺点,构建了包含电流偏差和中点电压偏移量的价值函数,选择使价值函数最小的开关序列和时间序列作为输出。仿真和实验结果表明,所提优化开关序列的控制策略具有有效性与可行性。     

三相并网逆变器状态反馈模型预测控制策略

在三相并网逆变器中,由于传统的电流模型预测控制(MPC)系统中存在建模误差等因素,导致评估函数选出的预测值在应用时不一定仍具最优性。基于传统比例积分(PI)调节对给定电流良好的跟踪性基础上,提出了一种具有状态反馈、误差补偿的MPC算法,根据前一时刻电流预测值与实际电流采样值的偏差补偿当前时刻预测函数模型系统的输出,从而减少由建模误差造成的预测值与实际值的偏差。仿真和实验结果表明:加入反馈校正后,模型电流预测算法的控制性能大大提高,有效减少了谐波含量。从而验证了该方案的可行性和有效性。     

模型预测控制三相逆变器的研究

模型预测控制利用系统离散模型预测负载电流,根据评估函数选择电压矢量,进而选择最优开关状态。评估函数用来判断最优电压矢量和开关状态,以达到最佳预测效果。本文在静止坐标系下分析三相逆变器的模型预测控制(MPC)原理,讨论了评估函数、参数误差、采样频率对模型预测控制的影响,最后通过dSPACE/DS1104作为控制器搭建了MPC实验平台。结果显示,相比于其他控制策略,模型预测控制具有控制简单、动态响应好、效率高等优点。     

基于模型预测控制的开关电感准Z源逆变器研究

近年来,模型预测控制(MPC)因其良好的控制特性受到广泛关注。本文研究一种应用于开关电感型准Z源逆变器(SL-qZSI)的模型预测控制(MPC)算法。首先建立开关电感准Z源逆变器的状态变量及输出变量预测模型,基于该模型计算准Z源网络电感电流,电容电压和负载电流下一采样时刻的预测值。根据多变量控制目标,得到损失函数并令其最小,得到所对应的开关状态作为下一时刻的开关状态。仿真结果验证了所研究控制方法的正确性及有效性。     

基于无谐波检测三相四开关APF模型预测控制

提出一种基于无谐波检测技术的三相四开关并联有源电力滤波器(TFSAPF)模型预测控制(MPC),该控制取代了传统四开关逆变器空间矢量脉宽调制(SVPWM)算法,无需扇区判断和电压基矢量作用时间计算,避免了因母线中点电位偏移导致扇区误判断及合成零电压矢量存在误差。分析了传统SVPWM算法和MPC对系统的补偿效果,得出在预测允许误差范围内,提前预测两个采样周期的指令信号具有更好的补偿性能。新型控制方案省略了谐波检测相关运算,简化了调制算法。仿真结果验证了该方法的有效性与实用性。     

级联多电平并网逆变器简化模型预测控制研究

传统的模型预测控制(MPC)策略在实时控制过程中需要较多的时间进行预测和优化,因此在采样和输出之间具有一定的延时,故此处提出一种简化MPC策略。采用TMS320F28335型DSP作为控制器,以级联H桥多电平并网逆变器为控制对象,分析了该简化MPC策略下并网电流的稳态与动态性能。仿真和实验结果验证了该简化MPC策略应用在级联H桥多电平并网逆变器中的可行性。     

基于开关状态函数计算的改进模型预测控制

传统有限状态模型预测控制(FCS-MPC)利用枚举法选择最优电压矢量,数字控制器运算量大,有学者提出简化的MPC方法,在保持控制系统动稳态性能的同时降低数字计算复杂度,但这些方法均存在采样频率高、稳态功率误差大等缺点。在分析三相AC-DC变换器离散预测模型的基础上,提出一种基于开关状态函数直接计算的模型预测控制方法,以同步坐标系下功率的负共轭为控制变量,根据功率控制误差矢量的长度和所处的扇区,直接计算出各相开关状态函数,经过调制过程完成系统功率的精确跟踪控制。该方法不但保留了传统模型预测控制快速动态响应特性,而且实现了功率跟踪误差最小化。仿真和实验结果均证明了所提方法的有效性和正确性。     

PWM逆变器MPCC的矢量优化方法研究

三相电压型脉宽调制(PWM)逆变器由于电压矢量个数少,传统模型预测电流控制(MPCC)下的系统性能需依赖较高的采样频率。此处提出离散PWM方法,通过插入零矢量来调节矢量作用时间,减小指标函数控制误差,从而在不增加采样频率的情况下提高电流控制效果。为解决矢量作用时间短而引起的窄脉冲问题,提出一种简单实用的抑制方法。实验显示结果与传统MPCC相比,此处提出的新型MPCC方法动态性能良好,稳态性能得到显著提高。     

一种采样模型预测控制的动态电压恢复器控制方法

针对目前动态电压恢复器(DVR)多采用根据当前状态做出未来动作的控制方法，从微观上看总会因为采样和反馈信息与控制动作之间存在时间延迟而产生误差的问题，提出一种通过预测下一控制周期的输出从而确定下一控制周期控制动作的闭环结构的模型预测控制(MPC)方法。该方法基于前向欧拉法建立控制预测模型，通过反馈校正的方法减少预测误差，并通过建立合适的目标函数，确定应用于下一控制周期的最佳开关组合。利用MATLAB/Simulink软件搭建所提控制方法的仿真模型，仿真结果表明，提出的MPC方法能有效减少DVR的补偿误差，具有响应速度快、谐波含量低、设计简单等优点。     

High Performance Modified Model Predictive Control of a Voltage Source Inverter

This paper proposes a modified model predictive control (MMPC) method for a two-level voltage source inverter (VSI) by applying ‘Midpoint Euler's Approximation’ technique to achieve a high performance. Therefore, a new predictive mathematical modeling is derived and presented in this paper to predict the future behavior of the inductive load model, which is compared with the reference signal to determine the cost function of the system. In this MMPC method, all the possible switching vectors of the converter are utilized to obtain the cost functions, and the corresponding switching vector for minimum cost function is selected to actuate the power converter in the next sampling time interval. The proposed MMPC method and the traditional MPC schemes are verified in MATLAB-Simulink. The experimental validation is performed in DS1104 R&D Controller Board to justify and confirm the performance of the system. Simulation and experimental results validate the robustness of the proposed MMPC method, and improve the results compared to traditional MPC method in terms of total harmonic distortion (THD) and current reference tracking mean error.     

A Simplified Model Predictive Control of Four-Leg Two-Level Inverter

Abstract

This article proposes current control strategy for four-leg two-level voltage source inverters (VSI). This strategy is based on model predictive control (MPC) approach and presents its comparison with finite control set (FCS) model technique. Besides providing a fast dynamic response, proposed technique replaces complex modulation stage and PI controller being used in earlier classical control techniques. Moreover, the proposed methodology selects the switching sequence which reduces tracking error between output and applied reference currents using cost function optimization. This shows the improvement of system response like FCS model technique. However, FCS model technique results in calculation stress and computation burden; resulting computational delay and extra power consumption by the processor. This problem is solved with the help of proposed single predictive technique which makes the inverter more suitable for large time horizon operations and small sampling time instants. The computational delay is reduced up to 6% compared to the case of FCS-MPC controlled inverter. Performance of proposed simplified technique is analyzed and compared with FCS-MPC controlled system with the help of different types of reference signals. This work will boost the industrial application of four-leg two-level VSI by increasing dynamic response and removing complex modulation stage.     

Model predictive control of grid-connected PV power generation system considering optimal MPPT control of PV modules

Because of system constraints caused by the external environment and grid faults, the conventional maximum power point tracking (MPPT) and inverter control methods of a PV power generation system cannot achieve optimal power output. They can also lead to misjudgments and poor dynamic performance. To address these issues, this paper proposes a new MPPT method of PV modules based on model predictive control (MPC) and a finite control set model predictive current control (FCS-MPCC) of an inverter. Using the identification model of PV arrays, the module-based MPC controller is designed, and maximum output power is achieved by coordinating the optimal combination of spectral wavelength and module temperature. An FCS-MPCC algorithm is then designed to predict the inverter current under different voltage vectors, the optimal voltage vector is selected according to the optimal value function, and the corresponding optimal switching state is applied to power semiconductor devices of the inverter. The MPPT performance of the MPC controller and the responses of the inverter under different constraints are verified, and the steady-state and dynamic control effects of the inverter using FCS-MPCC are compared with the traditional feedforward decoupling PI control in Matlab/Simulink. The results show that MPC has better tracking performance under constraints, and the system has faster and more accurate dynamic response and flexibility than conventional PI control.     

Model predictive control of grid-connected PV power generation system considering optimal MPPT control of PV modules

Because of system constraints caused by the external environment and grid faults, the conventional maximum power point tracking (MPPT) and inverter control methods of a PV power generation system cannot achieve optimal power output. They can also lead to misjudgments and poor dynamic performance. To address these issues, this paper proposes a new MPPT method of PV modules based on model predictive control (MPC) and a finite control set model predictive current control (FCS-MPCC) of an inverter. Using the identification model of PV arrays, the module-based MPC controller is designed, and maximum output power is achieved by coordinating the optimal combination of spectral wavelength and module temperature. An FCS-MPCC algorithm is then designed to predict the inverter current under different voltage vectors, the optimal voltage vector is selected according to the optimal value function, and the corresponding optimal switching state is applied to power semiconductor devices of the inverter. The MPPT performance of the MPC controller and the responses of the inverter under different constraints are verified, and the steady-state and dynamic control effects of the inverter using FCS-MPCC are compared with the traditional feedforward decoupling PI control in Matlab/Simulink. The results show that MPC has better tracking performance under constraints, and the system has faster and more accurate dynamic response and flexibility than conventional PI control.     

基于扰动抑制的三相逆变器模型预测控制策略

为了提高三相逆变器的鲁棒性,设计了一种基于扰动抑制的模型预测控制(MPC)策略.新型MPC控制器采用了扰动观测器(DOB)以简化预测模型,同时具有无约束和有约束两种工作模式.无约束模式MPC控制下三相逆变器稳态电压可得到精准调节,而在约束模式下通过优化调制可使系统快速进入到无约束模式,这确保了在系统所有运行条件下的较优...     

Constrained MPC to track time‐varying reference signals: Online optimization of virtual reference signals and controller states

In this paper, we propose a model predictive control (MPC) algorithm for linear systems with constraints to track time‐varying reference signals. The proposed controller is assumed to have an integrator as a servo compensator. In the proposed control approach, the value of the integrator state is optimally initialized at each sampling time to improve tracking control performance until the cost function becomes sufficiently small. Moreover, while the cost function is sufficiently small, the integral action is used to achieve offset‐free tracking. The control algorithm is reduced to a convex optimization problem with linear matrix inequality constraints. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

一种单相光伏并网逆变器改进预测电流控制算法

光伏并网逆变器传统预测电流控制算法由于采样与计算延时会造成差一拍控制,使得逆变器并网电流不能很好地跟踪目标电流,同时逆变器滤波电感模型值与实际值有误差时会造成并网电流谐波大,还可能导致系统不稳定。为克服这些不足,提出了一种改进的预测电流控制方法,可提前一个采样周期对并网逆变器输出电压进行预测,同时利用递推最小二乘法对电感参数进行在线辩识。仿真和试验结果表明所提方法有效提高了逆变器并网电流对目标电流的跟踪精度,减小了并网电流的谐波分量,提高了由逆变器进网的电能的质量。     

火控雷达测量误差自相关时间分析

舰炮火控雷达跟踪精度试验时需要确定跟踪数据的采样时间间隔,采样时间间隔主要取决于雷达跟踪误差特性的自相关时间。数据采样时间间隔直接影响试验航次数的确定和试验效率。从基础自相关估计理论出发,给出通过协方差函数直接计算和利用FFT变换计算雷达误差自相关时间方法,实测数据结果验证了火控雷达误差数据序列的平稳性;分析得到了火控雷达对典型目标的跟踪误差弱相关时间并给出雷达精度试验对空中目标数据采样时间间隔先按距离和方位角弱相关系数K值确定,即1～2 s,数据处理时再对高低角误差数据进行取2～3倍间隔的建议。通过自相关时间分析发现雷达伺服系统对消舰艇摇摆存在剩余的技术问题,有助于雷达技术改进和跟踪误差源分析。     

感应电机无差拍模型预测转矩控制研究

传统模型预测控制（MPC）在三相两电平逆变器驱动感应电机系统中需对所有电压矢量进行滚动优化预测,计算成本高,实施难度大。为此,提出一种无差拍（DB）MPC,将滚动优化预测电压矢量从8个减少到3个。通过求解DB电压矢量和对DB扇区的划分,根据空间电压矢量位置确定扇区,只将扇区内矢量进行单步滚动优化预测,输出相对应的最优开关状态。仿真结果表明:DB预测转矩控制在减轻系统计算负担情况下,达到与传统MPC几乎相同的稳态跟踪性能。