无模型预测控制及在溴化锂机组控制中的应用

为解决带有时滞特性的制冷系统的控制问题，提出了一种改进的无模型自适应预测控制算法，并将其应用到制冷系统控制方案中。首先，提出一种引入两个参数L1，L2的参数估计控制方案，改善了MFAPC( Model-Free Adaptive Predictive Control) 的伪偏导数参数估计过程，使算法在达到减参目的的同时提升了稳定效果; 之后在控制输入准则函数中加入了控制输出误差和。最后引入典型线性和非线性时滞系统、跟踪时变信号系统、溴化锂制冷系统，对其跟踪控制问题进行了仿真比较研究。仿真结果表明，改进的无模型预测控制算法能取得更稳定的输出结果，且有更快的响应速度和更好的控制性能，同时解决了带有时滞特性的制冷系统控制问题。

Model-Free Predictive Control and Its Application in Control of Lithium Bromide Unit

In order to solve the control problem of refrigeration system with time-delay characteristics，an improved model-free adaptive predictive control algorithm is proposed． The improved model-free adaptive predictive algorithm is applied to the refrigeration system control scheme． And in order to get more stable control effects，better performance of the algorithm，and make design of MFAPC ( Model-Free Adaptive Predictive Control) more flexible． Firstly，a parameter estimation control scheme that introduced two parameters L1 and L2 is proposed，It improves the pseudo-partial derivative parameter estimation process of the MFAPC，therefore the algorithm can improve the stability effect while achieving the goal of reducing reference． Then，The control output error sum is added to the control input criterion function． Finally，typical linear and nonlinear time-delay system，tracking time-varying signal system，lithium bromide refrigeration system are introduced． The tracking control problems are simulated and compared． The simulation results show that the improved model-free predictive control algorithm can achieve more stable output result，with faster response speed and better control performance，solving the refrigeration system control problem of time-delay characteristics．