Dear Colleagues,

In 1965, Prof. L. Zadeh introduced the concept of Fuzzy Sets (FSs) to represent uncertain system parameters. However, in many real-world systems, uncertainty appears due to multiple reasons. In such a scenario, uncertainty modeling capabilities of the Type 1 (T1) or traditional FSs are quite limited. Due to this, Zadeh himself introduced the concept of Type-2 FSs in 1975. However, for more than a decade, these types of FSs received very little attention from the scientific community. Interestingly, from 1990, researchers started investigating T2 FSs, or more specifically Interval Type-2 (IT2) FSs, and successfully applied the same for realistic uncertainty modeling in a number of applications.

The aim of this Special Issue is to present the state-of-the-art results in the area of intelligent control theory and applications. Intelligent control is a technique of applying some methods to obtain a model of the process and using this model to design a controller. In particular, fuzzy control has been an important area of active research. Significant developments have been seen, including theoretical success and practical design. One of the reasons for the rapid growth of fuzzy control is its ability to control plants with uncertainties during its operation.

The papers in this Special Issue will present the most advanced techniques and algorithms of fuzzy control. These include various robust techniques, performance enhancement techniques, techniques with less a priori knowledge, and nonlinear intelligent adaptive control techniques. This Special Issue aims to provide an opportunity for international researchers to share and review recent advances in the foundations, integration architectures, and applications of hybrid and fuzzy systems in control.

The main aim of this Special Issue is to organize a forum to provide innovative approaches to handle various fuzzy controllers, adaptive control strategies, time-delay nonlinear systems, cooperative control, and hybrid intelligent control. We want to offer an opportunity for researchers and practitioners to identify new promising research directions in this area.

Prof. Dr. Oscar Castillo
Guest Editor

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• Type-1 fuzzy control
• Type-2 fuzzy control
• fuzzy neural networks in control
• metaheuristics in fuzzy control
• evolutionary fuzzy control
• genetic fuzzy control
• fuzzy PID control
• robot control