Abstract: The outer relationship was projected to inner latent variables space with orthogonal components by the partial least squares（PLS）algorithm while simultaneously compressing data blocksSome advantages of using this approach as part of control system design include automatic decoupling and efficient loop pairingWhile the method could not erase the correlation of latent variables completely，PID controller would not be competent enough to handle the controlA methodology was proposed for controller design with optimization and control algorithm in the subspace defined by dynamic latent variable models，and its application to a pressurized breast box and a distiller was illustrated to show how this strategy works.

摘要： 基于偏最小二乘（PLS）隐变量空间的控制利用PLS算法内部关系主元独立的结构，可以实现自动解耦多变量之间的严重相关性，且自动实现隐变量变量配对，从而使得MIMO控制简化为SISO控制。由于PLS为稳态算法，要进行动态PLS算法才能与控制要求相符。但是因为PLS隐变量之间并不能完全消除相关性，因此如果采用PID控制器，在整定时回路之间将相互影响且控制器参数不稳定，由此进行了基于动态PLS隐变量空间模型的最优化控制。同时就加压网前箱和一个蒸馏器给出了该控制方法的仿真应用，显示了该方法的特性。