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对精馏塔全阶模型进行了分析 ,设计了基于RBF神经网络的直接自适应控制器。采用双端控制 ,克服了单端控制的不足。网络权值的调整算法基于所选择的Lyapunov函数 ,这样可保证闭环系统的稳定性和权值参数的收敛性。仿真结果表明所设计闭环系统具有良好的跟踪性和鲁棒性。
The full-scale distillation column model was analyzed, and a direct adaptive controller based on RBF neural network was designed. Using double-ended control to overcome the lack of single-ended control. Network weight adjustment algorithm based on the selected Lyapunov function, so as to ensure the stability of the closed-loop system and the convergence of weight parameters. Simulation results show that the designed closed-loop system has good tracking and robustness.