摘要
研究预测控制和PID控制在再热汽温系统控制中的应用。通过将神经网络作为预测模型,并用蚁群算法在线优化PID控制器参数。计算机仿真结果表明,基于蚁群算法的预测PID控制能够适应控制对象模型参数的时变,具有较好的鲁棒性,相对传统PID控制策略还表现出了良好的动态性能。
Predictive control combined with PID control was applied to the control of reheated steam temperature system. Artificial Neural Network （ ANN ） was used as the predictive model and ant colony algorithm （ACA） was adopted to optimize the PID controller parameters online. The simulation result shows that the predictive PID control based on ACA can track the change of controlled object model parameters. It has better robustness and dynamic performance than classic PID control.
出处
《化工自动化及仪表》
CAS
2008年第3期19-22,共4页
Control and Instruments in Chemical Industry
