in industrial robotic manipulator, due to the presence of quite nonlinear dynamic and structural and nonstructural uncertainties, a precise model is not easily obtained. as a result, designing a controller with a suitable function based on system model is a challenging issue. sliding mode control is a robust control with numerous applications which can overcome the aforementioned uncertainties....

In the past year I have been inundated with articles on fuzzy logic as well as encouraged to use it for control systems. After reading some articles on fuzzy logic control, listening to a seminar by Zadeh, and attending a one day course on Intelligent Control, I started forming an opinion about how fuzzy logic control works. I believe that there are some fundamental pieces of information not pr...

Normality is a common assumption for many quality control charts. One should expect misleading results once this assumption is violated. In order to avoid this pitfall, we need to evaluate this assumption prior to the use of control charts which require normality assumption. However, in certain cases either this assumption is overlooked or it is hard to check. Robust control charts and bootstra...

Standard control charts are based on the assumption that the observations are normally distributed. In practice, normality often fails and consequently the false alarm rate is seriously in error. Application of a nonparametric approach is only possible with many Phase I observations. Since nowadays such very large sample sizes are usually not available, there is need for an intermediate approac...

Industrial production requires multivariate control charts to enable monitoring of several components. Recently there has been an increased interest also in other areas such as detection of bioterrorism, spatial surveillance and transaction strategies in finance. In the literature, several types of multivariate counterparts to the univariate Shewhart, EWMA and CUSUM methods have been proposed. ...

Control charts such as X and R charts are widely used in industry to monitor quality. These charts are effective in detecting large departures from the in-control condition. Other process monitoring methods, such as Cumulative Sum (CUSUM) charts are sequential in nature as they accumulate information from previous observations. CUSUM charts are good at detecting more moderate presistent process...