Model-Based and Model-Free Control of Autocorrelated Processes

A New Model-Free CuSum Procedure for Autocorrelated Processes

We present a new CuSum chart for monitoring shifts in the mean of autocorrelated data. The monitoring statistic is the plain cumulative sum of differences between the observations and the target value, and the control limits are a function of the asymptotic variance constant and target in-control average run length. Our method uses a variety of non-parametric techniques that are popular in the ...

mortality forecasting based on lee-carter model

over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...

Data mining model-based control charts for multivariate and autocorrelated processes

Process monitoring and diagnosis have been widely recognized as important and critical tools in system monitoring for detection of abnormal behavior and quality improvement. Although traditional statistical process control (SPC) tools are effective in simple manufacturing processes that generate a small volume of independent data, these tools are not capable of handling the large streams of mul...

Model- Based And Model - Free Schemes For Monitoring Mean And Variance Of Autocorrelated Process

Model-Free Learning Control of Chemical Processes

Learning is the nature for human being. For example, a school-student learns a subject by doing exercise and home-work. Then, a school-teacher grades the school-student’s works. From this student and teacher interaction, the ability of the student mastering the subject is a feedback that the previous teaching method is successful or failure. As a result, the teacher will change the teaching met...