The problem of improvement of existing approaches for evaluation of inferential models used in the advanced process control systems is considered. The method of finding the identifiability index limit, based on the physically-chemical essence of the industrial distillation process, for the inferential models containing nonlinear transformations of measured inputs is given. The problem of handli...

Two multivariable inferential feed-forward control strategies are proposed in this paper. In the first strategy, the effects of disturbances on the primary process variables are inferred from uncontrolled secondary process variables that are measured on-line. In the second approach, the effects of disturbances on the primary process variables are inferred from the manipulated variables for thos...

Certain control applications require that performance variables are explicitly distinguished from measured variables. The performance variables are not available for real-time feedback. Instead, they are often available after a task. This enables the application of batch-tobatch control strategies such as Iterative Learning Control (ILC) to the performance variables. The aim of this paper is fi...

in general, the objective of distillation control is to maintain the desired products quality. in this paper, the performances of different one point control strategies for an aromatic distillation column have been compared through dynamic simulation. these methods are: a) composition control using measured composition directly. this method sufferes from large sampling delay of measuring device...

The combination of feedback control with inverse model feedforward control or iterative learning control is known to yield high performance. The aim of this paper is to clarify the role of feedback in the design of feedforward controllers, with specific attention to the inferential situation. Recent developments in optimal feedforward control are combined with feedback control to jointly optimi...

Previous research demonstrated that inferential sensors-based control technology can significantly improve the energy efficiency of space heating systems. However, the performance strongly relies on the accuracy and robustness of the dynamic model upon which the inferential model is built. Traditional methods, such as simplified physical model, adaptive neurofuzzy inferential sensor(ANFIS-) bas...