传统有限控制集的模型预测控制(finite control set model predictive control,FCS-MPC)在一个控制周期内输出单一的开关状态,当采样频率较低时,控制精度较差,且开关频率不固定导致交流侧滤波器难以设计。针对上述问题,在传统FCS-MPC的...传统有限控制集的模型预测控制(finite control set model predictive control,FCS-MPC)在一个控制周期内输出单一的开关状态,当采样频率较低时,控制精度较差,且开关频率不固定导致交流侧滤波器难以设计。针对上述问题,在传统FCS-MPC的基础上,为三相脉冲宽度调制(pulsewidth modulation,PWM)整流器提出一种基于功率跟踪目标函数的定频模型预测控制。首先基于FCS-MPC的功率跟踪目标函数最小值求解,精确计算变换器输出电压矢量的扇区,接着根据扇区确定控制周期作用的两个有效矢量和零矢量,最后利用3个矢量的功率跟踪差值计算各电压矢量的作用时间。通过仿真验证,与传统FCS-MPC相比,所提方法能实现开关频率的固定,减小功率脉动,提高整流器的输出性能。展开更多
A prediction control algorithm is presented based on least squares support vector machines (LS-SVM) model for a class of complex systems with strong nonlinearity. The nonlinear off-line model of the controlled plant i...A prediction control algorithm is presented based on least squares support vector machines (LS-SVM) model for a class of complex systems with strong nonlinearity. The nonlinear off-line model of the controlled plant is built by LS-SVM with radial basis function (RBF) kernel. In the process of system running, the off-line model is linearized at each sampling instant, and the generalized prediction control (GPC) algorithm is employed to implement the prediction control for the controlled plant. The obtained algorithm is applied to a boiler temperature control system with complicated nonlinearity and large time delay. The results of the experiment verify the effectiveness and merit of the algorithm.展开更多
文摘传统有限控制集的模型预测控制(finite control set model predictive control,FCS-MPC)在一个控制周期内输出单一的开关状态,当采样频率较低时,控制精度较差,且开关频率不固定导致交流侧滤波器难以设计。针对上述问题,在传统FCS-MPC的基础上,为三相脉冲宽度调制(pulsewidth modulation,PWM)整流器提出一种基于功率跟踪目标函数的定频模型预测控制。首先基于FCS-MPC的功率跟踪目标函数最小值求解,精确计算变换器输出电压矢量的扇区,接着根据扇区确定控制周期作用的两个有效矢量和零矢量,最后利用3个矢量的功率跟踪差值计算各电压矢量的作用时间。通过仿真验证,与传统FCS-MPC相比,所提方法能实现开关频率的固定,减小功率脉动,提高整流器的输出性能。
基金This work has been supported by the National Outstanding Youth Science Foundation of China (No. 60025308) and the Teach and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of MOE,China.
文摘A prediction control algorithm is presented based on least squares support vector machines (LS-SVM) model for a class of complex systems with strong nonlinearity. The nonlinear off-line model of the controlled plant is built by LS-SVM with radial basis function (RBF) kernel. In the process of system running, the off-line model is linearized at each sampling instant, and the generalized prediction control (GPC) algorithm is employed to implement the prediction control for the controlled plant. The obtained algorithm is applied to a boiler temperature control system with complicated nonlinearity and large time delay. The results of the experiment verify the effectiveness and merit of the algorithm.
