摘要
预测控制中,对控制量/控制增量加权因子λ和设定值柔化因子α的调节影响到控制系统的性能.调整预测控制器中控制量/控制增量加权因子λ对调节系统上升时间和超调量的作用是相反的.而且λ影响系统矩阵的条件数,存在模型失配时,对系统鲁棒性有很大的影响.设定值柔化因子α对于系统的动态响应也有很大的影响,调整λ和α对于系统的动态响应有类似的效果.因此,为了使闭环系统具有更好的控制性能,将参数λ设计成满足系统矩阵条件数的要求,并通过在线调整α以获得满意的动态性能.仿真结果表明了该方法的有效性.
For predictive control, the tuning of weighting factor λ and set-point softening factor α greatly influences the performance of control systems. Tuning of A in a model predictive controller had negative effects on the regulation of overshoot and ascending time of the system. Moreover, λ has an effect on the condition number of the system matrix. Thus, λ has a great effect on the robustness of the system when model mismatch occurs. Set-point softening factor λ also has a large effect on the dynamic response of the control system. Tuning of both a and λ produces similar effects on the dynamic response of the control system. Hence, in order to achieve better control performance, λ was designed to satisfy the need of the condition number and a was assigned as an online tuning parameter. Simulations verified the effectiveness of this approach.
出处
《智能系统学报》
2009年第5期433-440,共8页
CAAI Transactions on Intelligent Systems
基金
国家自然科学基金资助项目(60825302
60774015)
国家"863"计划资助项目(2007AA041403)
关键词
预测控制
系统矩阵条件数
设定值柔化因子
参数在线调整
model predictive control
condition number of system matrix
setpoint softening factor
online tuning
