中文摘要：

火电厂锅炉燃烧过程是一个复杂的多输入/多输出系统,具有高度非线性、强耦合的特点。借助燃烧特性试验数据,利用最小二乘支持向量机（LSSVM）建立锅炉燃烧模型,使用非线性模型预测控制（MPC）算法对锅炉燃烧过程进行优化和控制。提出一种改进蚁群算法用于求解预测控制算法中的非线性优化问题,采用动态随机抽取方法来确定目标个体引导蚁群进行全局搜索,同时在最优蚂蚁邻域内进行小步长局部搜索。实例表明,该方法对锅炉燃烧过程具有较好的控制效果。

英文摘要：

The boiler combustion process of coal-fired power plant is a very complicated MIMO system with high nonlinearity and strong coupling.The LSSVM（Least Square Support Vector Machine） is applied to build the boiler combustion model based on the property test data and the nonlinear MPC（Model Predictive Control） is applied to optimize the control of boiler combustion process.The improved ACO（Ant Colony Optimization） is proposed to solve the nonlinear optimization problem of MPC algorithm,which extracts the target individuals dynamically and stochastically to lead the global search of ant colony while carries out the small step search nearby the optimal ant.Case study indicates its effectiveness.