摘要
针对锅炉-汽轮机系统多输入多输出、非线性、强耦合等特点,采用非线性逆系统方法实现反馈线性化和解耦,利用径向基函数(RBF)神经网络方法来辨识逆系统,并通过在线学习减小了建模误差.对解耦后的锅炉-汽轮机系统设计终端滑模控制器,实现了有限时间收敛,采用Lyapunov方法进行了稳定性分析,保证了该控制系统的大范围稳定性.仿真结果表明:该控制系统能够在大范围运行工况下工作良好,优于经典逆系统控制方法设计的系统.
Aiming at the features of boiler-turbine unit, such as multiple inputs, multiple outputs, nonlinearity and strong coupling etc. , an inverse system method is used to achieve feedback linearization and decoupling of the unit, during which the inverse system is identified using radial basis function (RBF) neural network, while the modeling errors reduced through online learning. A terminal sliding mode controller is designed for the unit to reach finite time convergence, and its global stability is analyzed and guaranteed using Lyapunov approach. Simulation results show that the control system works well within a wide range of operation conditions, which is superior to the system designed based on classical inverse system method.
出处
《动力工程学报》
CAS
CSCD
北大核心
2012年第10期792-797,814,共7页
Journal of Chinese Society of Power Engineering
基金
河北省自然科学基金资助项目(F2012203088)