摘要
针对结晶器出口温度和液位控制问题,提出了一种基于改进的偏好多目标粒子群优化的非线性预测控制算法(IMPSO-NPC)。改进的偏好多目标粒子群优化算法(IP-MPSO)将参考点偏好算法和参考区域偏好算法融合在一起,在参考点和参考区移动过程中动态调整参考区,控制解集的偏好范围。另外,为了选取粒子群全局最优粒子,提出一种球扇占优的策略,提高了粒子群的搜索能力。将改进算法应用于结晶器的控制过程,仿真结果证明了其有效性和可行性。
A nonlinear predictive control algorithm based on a preference multi-objective particle swarm optimiza- tion algorithm （IMPSO-NPC） has been proposed in an attempt to control problems of mold level and temperature at the mold. An improved preference multi-objective particle swarm optimization （IP-MPSO） algorithm combines a reference region with a reference point in order to guarantee the preference direction. In the process of moving refer- ence regions and reference points, IMPSO-NPC dynamically adjusts the reference regions and controls the prefer- ence range. In order to further improve the search performance, spherical sector dominance is proposed for gBest of PSO. The proposed method can be applied to mold control systems and simulation results show that the new method is feasible and effective.
作者
戴永彬
吕旭
DAI YongBin, LV Xu(College of Software, Liaoning University of Technology, Jinzhou, Liaoning 121001, Chin)
出处
《北京化工大学学报（自然科学版）》
CAS
CSCD
北大核心
2018年第2期82-88,共7页
Journal of Beijing University of Chemical Technology(Natural Science Edition)
基金
辽宁省自然科学基金(2013020036)
关键词
粒子群优化
非线性预测
偏好算法
结晶器
particle swarm optimization
nonlinear predictive
preference algorithm
mold
