## 4 Results: MPPT Techniques Review
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\begin{tabular}{p{142.3 pt} p{142.3 pt}} \hline \hline
**Reference** & **Analysis of Results** \\ \hline [PERSON] and [PERSON], 2019 & Comparative experimental results with [67] demonstrates that the proposed controller possesses a remarkable learning capability of the RNN weights and can be used to maintain the optimum generator power. \\ \hline [PERSON] et al., 2019 & Results show that the flux linkage and turbine rotational speed tracking the reference value almost without oscillation and back to stable state, which indicates its highly acceptable tracking performance, considering the quick reaction and following-up time. \\ \hline [PERSON] et al., 2019 & With turbulent wind the standard deviation of generator shaft speed is 0.0206 rad/s for NN controller, and 0.0351 rad/s for the PI counterpart. The NN controller can produce smaller oscillation and provide electrical energy with higher quality for grid integration. \\ \hline [PERSON] et al., 2018 & The results are compared with a classical Perturb and Observe (P\&O) method. The overall performance comparison of the maximum power drawn was 7.28\% greater using the Boost converter, 3.68 with the SEPIC converter and 3.34 with the quadratic increase converter for wind speed below the rated speed. \\ \hline [PERSON] et al., 2017 & The proposed controller gives 2.021\%, 4.623\% and 9.893\% more power during below rated wind speed and during above rated wind speed it produces 0.187\%, 1.67\%, 3.67\% and 5.38\% of rated generator power than the BPN, FLC and PI controller respectively. \\ \hline [PERSON] et al., 2017 & A comparison is made between MLPNN controller and conventional PI regarding their performance in adjusting the pitch angle. The results approve the designed controller to be much faster and more accurate than the conventional PI. \\ \hline [PERSON] et al., 2017 & Compared with a well-designed PID controller the proposed adaptive controller shows less fluctuation in following the desired system power pattern and less rotor speed errors. \\ \hline [PERSON] et al., 2017 & Compared with a PI controller. Rotor speed is very stable and its fluctuation are considerably reduced. The pitch angle variations are much lower. The generator torque is very stable, the mean value is only 133.5-kNm than the 139.4 kNm given by PL. \\ \hline [PERSON] et al., 2017 & The baseline controller is compared with PI controller. The effectiveness of controller is evaluated based on the damage equivalent loads. The tower base fore–aft moment was reduced by 15.3\%, the tower base side-to-side moment was reduced by 9.8\%, and the tower base torsional moment was reduced by 10.4\%. \\ \hline [PERSON] et al., 2016 & The performance ANFIS controller is compared with ANN controller. The maximum power error is 0.0095 watts for ANN and 0.000123 watts for ANFIS. \\ \hline [PERSON] et al., 2016 & The proposed algorithm enables the PMSG to produce a total energy of about 8.4 kJ in the two minutes, which is 5\% more than 8 kJ energy produced by the PMSG with a conventional P\&O method. \\ \hline [PERSON] and [PERSON], 2016 & The simulation results are analyzed alongside a PI controller and the controller designed for [PERSON] et al. (2013). The proposed controller can precisely track the desired rotor speed in second region, but not the other controllers. The tracking error of the proposed controller is lower resulting in a lower generator torque. \\ \hline [PERSON] et al., 2016 & Graphic results show good behavior on the optimal rotor speed. Increased efficiency and performance of the turbine. The grid voltages and injected currents are in phase; therefore, unit power factor is reached. \\ \hline [PERSON] et al., 2014 & It was compared between traditional PID, PID-NN though standard PSO and adaptive PID-NN. Was documented the errors varied with time, with a time interval of 0.001 s. The adaptive PID-NN controller has fast convergence speed, high accuracy and stability. \\ \hline [PERSON] et al., 2013 & The proposed ELM wind speed estimation and sensorless control are proved effective. In most of the time, the wind speed error is less than 0.05 m/s. \\ \hline \hline \end{tabular}
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