基于多模型切换的过热汽温自适应预测控制

为了克服电厂过热汽温对象大惯性、大滞后及参数随负荷显著变化对系统控制带来的困难,采用了一种基于多模型切换的自适应预测控制策略.采用多个固定模型和2个自适应模型并行辨识过热汽温对象的动态特性.在每个采样时刻基于切换性能指标选出最优的局部模型作为当前模型,并据此设计预测控制器,从而实现全工况运行的自适应控制.同时证明了所提出的多模型控制策略可以保证闭环系统输入输出有界稳定.仿真结果表明该控制策略在大工况范围具有良好的动态调节品质和鲁棒性能.

Adaptive predictive control for superheated steam temperature based on multiple models switching

To deal with the effect of the superheated steam temperature object's outstanding inertial behavior and its parameters time-varying on control quality of the system,an adaptive predictive control method based on multi-model switching is adopted.Multiple fixed models and two adaptive models are established to identify the dynamic characteristic of the superheater in parallel.At each sampling time,according to the switching index a best model is selected and the predictive controller is designed accordingly.Consequently,the full-range operation adaptive control is achieved.The bounded-input and bounded-output stability of closed-loop system are proved.Simulation results show that the proposed method have good control performance and strong robustness within a wide operating range.