ABSTRACT
Multivariable control is an important issue in industry, where multiple variables often need to be controlled at the same time and interaction effects may exist among the cross-coupled system input=output variables. Most of the existing conventional control techniques rely on the availability of an accurate quantitative model of the system to be controlled, which is not always obtainable for complex real-world applications. Therefore, effective intelligent control methods for such complicated multi-input multi-output (MIMO) systems have been active research topics for decades in both academia and industry.
