Event-based control is used to reduce bandwidth utilization and computational efforts in control systems and also to reduce data transmission between control system elements like sensor , controller and actuator . In event-based control , new control input is updated and computed if an event occurs in the control system . It means that the actuator signal is transmitted to the network only when a certain condition satisfies , otherwise in comparison with the last sample , control input stays constant . In this control system , event detection mechanism is the criteria of computing and updating control input . Event-triggering condition is designed such that the stability of the control system is satisfied . In this thesis , to improve the performance of the control system , basically three suggestions are proposed . First , a novel method for updating the center of the membership functions in fuzzy adaptive control is introduced . In the next step , instead of a constant maximum sampling time T max , a dynamically variable equation for T max is proposed which prevents updating control input when there is no necessity of it . At the end , assuming the proposed equation for T max , an upper bound for maximum error threshold e max in introduced , which guarantees the desired performance of the control system . Finally , event-based mechanism is combined with fuzzy adaptive control and applied to benzene alkylation process to improve the performance of this performance . Key word: event-based control, fuzzy model reference adaptive control, event-based fuzzy model reference adaptive control, benzene alkylation process, event, stability, maximum sampling time