摘要
针对由被控对象非线性和优化目标函数非凸性带来的建模与实时优化问题求解的困难,提出一种基于相关向量机(RVM)的非线性多步模型预测控制算法.采用RVM建立非线性预测模型,并将差分进化算法引入非线性预测控制中发挥其全局最优、鲁棒、快速收敛等优点,在线求解多变量、多约束的非线性规划问题.利用实际生产数据进行聚丙烯牌号切换仿真,结果表明,该算法可大幅度减少切换时间,降低过渡料产量,提高经济效益.
Based on the relevance vector machine（RVM）,a nonlinear model predictive control algorithm is developed to deal with the difficulties in the modeling and real-time optimization problem for the controlled plant with nonlinearity and the optimization objective function with non-convexity.The nonlinear predictive model is established by RVM,the nonlinear constrained programming is on-line performed by employing differential evolution（DE） algorithm which possesses the advantages such as global optimum,robust and fast convergence.The proposed algorithm is applied in the polypropylene process,and the simulation results show that the performance of the grade transition control can be greatly improved.
出处
《控制与决策》
EI
CSCD
北大核心
2010年第8期1241-1245,共5页
Control and Decision
基金
国家863计划项目(2006AA04Z178)
关键词
非线性预测控制
相关向量机
差分进化
聚丙烯
牌号切换
Nonlinear predictive control
Relevance vector machine
Differential evolution
Polypropylene
Grade transition
