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In this paper we present a real application of computational intelligence. Fuzzy control of a non-linear rotary chain pendulum is proposed and implemented on real prototypes. The final aim is to obtain a larger region of attraction for the stabilization of this complex system, that is, a more robust controller. As it is well-known, fuzzy logic exploits the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost when dealing with complex systems. In this case, the control strategy is based on a Takagi-Sugeno fuzzy model of the strongly non-linear multivariable system. Simulation and experimental results on the real plant have been obtained and tested in a rotary inverted pendulum and in a double rotary inverted pendulum. They have been compared to other feedback control strategies such as Full State Feedback or Linear Quadratic Regulator with encouraging results. Fuzzy control allows to enlarge the stability region of control. Indeed, the region of attraction and therefore the stabilization has been enlarged up to over 17% for the real system.

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The potential benefits of networked control systems are tremendous, as they can be easily upgraded by just including new components (i.e., sensors, actuators, or controllers), avoiding any further modifications to their structure. A critical approach to unleash such potential benefits is event-based control, where the system output turns to be sampled on demand, instead of being sampled constantly at rigid periods of time. This paper analyzes from a bibliometric point of view the literature published for the last twenty years on event-based control, identifying the most relevant articles, authors, institutions, and journals. Moreover, the principal topics, motivations, and problems faced by the researchers are discussed, identifying distinct challenges and opportunities for future research.