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。
Abstract
Model predictive control is based on the discrete model of the system to predict the future behavior of the inverter. The optimal voltage is determined by calculation of the cost function of every voltage vector. Then the optimal switching state is achieved according the selected voltage vector. The paper analyzes the principles of model predictive control for the three-phase voltage source inverter in the stationary coordinate system. And the model is developed under the environment of MATLAB/Simulink. Then the characteristics of the evaluation function are presented. And the effects of parameter error on the control performance are discussed. The steady-state and dynamic performance on model predictive control of a three-phase inverter are shown considering the influence of different sampling frequency. The experimental platform is developed and dSPACE/DS1104 is used as a controller for the model predictive control. The simulation and experimental results show that model predictive control is simple, with good dynamic response and high efficiency compared with other control strategies.
关键词
模型预测控制 /
逆变器 /
评估函数 /
dSPACE
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Key words
model predictive control /
inverter /
cost function /
dSPACE
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参考文献
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