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We present a fuzzy approach to design a robust suboptimal control for decentralized interconnected system. We denote the non-linear interactions between the sub-systems are uncertain and in many real-life situation it can be represented by the differences of actual behavior from nominal description of sub-systems (e, é). Fuzzy sliding mode control is designed hr sub-system to track the prespecified trajectory in phase plane (e, é) according it’s states (x,x´). Fuzzy adaptation is proposed for tuning closed-related control subsystem on the sliding surface toward new equilibrium points. The adaptation strategy is determined by rule bases based on considering controller as PID controller with variable structure, switching between different PID settings with different inputs (e, é).

Wireless ad hoc network is a self-configurable and dynamically distributed network in which stations can move freely. In the ad hoc network, some flows have difficulty in accessing the channel due to contention at both the medium-access control (MAC) and link layers. The IEEE 802.11 protocol is currently the de facto standard for wireless networks. It uses enhanced distributed channel access (EDCA) method to access the transmission environment of each type of data flow. The size of the contention window (CW) in EDCA is related to the probability of accessing the channel of each flow. In our approach, useful information is obtained from the physical, MAC, and link layers. A fuzzy logic system is then used to adjust the size of CW to rely on such value, thereby improving the fairness index of data flows (voice, video, best effort) in IEEE 802.11 EDCA. The simulation results show that the proposed method can improve the throughput and fairness index of data flows.

A modern electric power plant is typically considered to be a large-scale system. Due to continual and random occurrence of load changes, maintenance of network frequency (or load frequency control LFC) at its nominal value is one of the most crucial control problems in order to ensure the stability and reliability of such an electric power grid. This study investigates a new efficient integration of fuzzy logic controllers based on PD principle and superconducting magnetic energy storage (SMES) devices in an effort to protect the system frequency from the load variations. It is well known that the PD-based fuzzy logic controllers, when applied to an LFC strategy, are capable of damping quickly the oscillations of both the system frequency and tie-line power deviations. In addition, the load disturbances can be compensated if the network is applying the SMES devices. Therefore, the integration between them might become an efficiently feasible solution for the LFC issue. The superiority of the proposed control methodology over conventional regulators is verified through a number of numerical simulations which will be implemented in this study for a five-area electric power grid model.