This study presents an adaptive sliding mode type-2 neuro-fuzzy controller for power control of doubly fed induction generators (DFIGs). DFIG-based wind turbine system is variable-speed constant-frequency wind energy conversion system. In this proposed control scheme, in order to enhance its performance, sliding mode control (SMC) theory is used for online training the parameters of type-2 fuzzy system membership functions. To regulate the antecedent and consequent part parameters, the SMC adaptive technique is used according to the controller inputs. These inputs are active and reactive power errors and their time derivative, which applied to the structure of T2NF system. The proposed controller employs an interval type-2 fuzzy system because of the uncertainties of the wind speed and variation in parameters in the wind power conversion system. The simulations carried out for a DFIG-based 1.5 MW wind turbine. The results of simulation are compared with the classical proportional-integral controller to confirm the effectiveness of this control scheme. This comparison is carried out between the cut-in and rated region wind speeds. The results of simulation show that the proposed control scheme has better performance to track the peak power and is more robust to machine parameter variations.

Hybrid Free Space Optics (FSO)/Radio Frequency (RF) communication systems have emerged as a way to improve network performance by providing enhanced availability and reliability. In an effort to mitigate individual drawbacks in the optical link during adverse weather conditions, network traffic flows simultaneously between channels. Based on the Shannon-Hartley theorem, channel capacity is dependent, among others, on both the signal to noise ratio (SNR) and channel bandwidth. As such, combined link throughput may be affected by channel state conditions. Because atmosphere turbulence can be modeled as a time-varying fading channel, capacity analysis can be investigated. In this paper, authors apply various availability scenarios of channel state information (CSI) on the optical link to derive closed-form expressions for combined link capacity. Numerical simulation provides a comparison to the results.Keywords-Hybrid FSO/RF link, channel capacity, channel state information (CSI), reconfiguration, and lognormal fading.

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