基于微粒群优化和模拟退火的约束广义预测控制算法  

Algorithm of Constrained Generalized Predictive Control Based on PSO-SA

作　　者：付秋峰[1] 肖军[1] 李书臣[1] 张勇强[1] 刘威[1] 

机构地区：[1]辽宁石油化工大学信息与控制工程学院,辽宁抚顺113001

出　　处：《石油化工高等学校学报》2010年第2期89-92,共4页Journal of Petrochemical Universities

基　　金：辽宁省教育厅科学研究计划资助(2004D031)

摘　　要：提出一种基于微粒群优化和模拟退火的约束广义预测控制算法,将微粒群优化和模拟退火引入到广义预测控制的滚动寻优过程中,增强对约束边界的搜索能力,并将约束条件构成约束违反度函数和适应度函数一起判断最优解的优劣,该算法可以有效地提高广义预测控制处理约束的能力。通过对一个工业对象的仿真,验证了该算法的可行性和有效性。An algorithm of constrained generalized predictive control was proposed based on partical swarm optimization(PSO) and simulated annealing(SA).PSO and SA were used for iterrative optimization to enhance the search capabilities for constraint boundary.Meanwhile,a violation function was constructed by constraints.This function and fitness function determined the optimal solution better or not.Constraint handling performance of GPC can be effectively improved by this algorithm.Its feasibility and efectiveness are verified via simulation study for an industrial object.

关 键 词：广义预测控制 约束 微粒群优化 模拟退火 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]