摘要
为了解决带有纯滞后的监控AGC系统的控制问题,提出了基于RBF神经网络的PID控制器与Smith预估器相结合的智能PID控制系统,并对传统监控AGC、应用Smith预估器的监控AGC及应用智能PID控制的监控AGC系统进行了仿真.结果表明,应用智能PID控制的监控AGC系统收敛速度明显加快,适应能力与鲁棒性比常规PID控制要好.
A PID control strategy based on RBF network and combining with Smith estimator was proposed for dead-time monitor AGC system. Simulations on classical monitor AGC, Smith estimator-based AGC and intelligent PID-based AGC were done. The simulation results indicate that the convergent speed of the intelligent PID-based AGC is faster than the others, and it has satisfied adaptability and robustness.
出处
《北京科技大学学报》
EI
CAS
CSCD
北大核心
2005年第1期119-122,共4页
Journal of University of Science and Technology Beijing
关键词
监控AGC
纯滞后
SMITH预估器
智能PID
Computer simulation
Convergence of numerical methods
Delay control systems
Radial basis function networks
Thickness control
Thickness gages
