## 6 Experimental Results  
The effectiveness of the proposed modified LFO is further tested with a prototype. The experimental prototype has a similar rated power as that in the simulation for fair comparison. The boost converter with the same component values as in the simulation is used here. The boost converter is used as the main component in searching for MPPT and also for supplying the optimum power to the load. The PV array output is generated by a PV simulator. Two sensors are used: LA-55p and LV-25. The Hall Effect current sensor, LA-55p, is used to measure the PV input current, while the voltage sensor, LV-25, is used to measure the PV input voltage. These measured signals are fed to the Analog-to-Digital converter (ADC) of DSP TMS320F28335. The signals are used as the input for MPPT algorithm execution. The Pulse Width Modulation (PWM) is the output signal produced by the MPPT algorithm. Typically, the PWM generated by DSP is in the range of 0-5 V; thus, a gate driver, HCPL 3120, is chosen. The driver HCPL 3120 boosts up the PWM signal to \(\pm\)15 V, sufficient to trigger the power switch in the boost converter. The resistive load is connected at the output. The waveforms are displayed and captured with a digital oscilloscope. The schemes of the experimental rig and experimental setup are shown in Figure 17a,b, respectively. Figure 16: Modified LFO at STC to PSC1. (**a**) power (**b**) voltage (**c**) current. Figure 17: _Cont._Firstly, the proposed modified LFO algorithm is experimentally tested under uniform irradiance. The numerical data of the I-V and P-V curves for high (1000 W/m\({}^{2}\)), medium (600 W/m\({}^{2}\)), and low (200 W/m\({}^{2}\)) irradiances at STC are loaded into the PV simulator. Once the respective numerical data are loaded, the patterns of the I-V and P-V curves are created as shown in Figure 18.  
Figure 19 shows experimental results for the proposed modified LFO algorithm tested at 1000 W/m\({}^{2}\) irradiance. Based on the results, the proposed algorithm is able to track LMPP, which is 50 W. From the results, the proposed modified LFO has excellent searching capability since it uses a random search. Once the optimum is found, the speed slows and reaches zero speed when all the particles have found the optimum point. Figure 17: Experimental (**a**) scheme (**b**) setup. Figure 18: Uniform pattern (STC) tested with the proposed modified LFO algorithm (**a**) I-V (**b**) P-V at 1000 W/m\({}^{2}\), 600 W/m\({}^{2}\), and 200 W/m\({}^{2}\). Figure 20 shows the experimental results of the proposed modified LFO tested at 600 W/m\({}^{2}\). Again, as can be noted, the proposed algorithm can track LMPP at 30 W. The proposed modified LFO shows excellent results in terms of stability and steady-state oscillation. Figure 19: Modified LFO at 1000 W/m\({}^{2}\), (a), (b), (c) reflect same result. Figure 20: _Cont._  
Figure 21 shows the experimental results of the proposed modified LFO tested at low irradiance, which is 200 W/m\({}^{2}\). Similarly, the proposed modified LFO shows excellent results in terms of stability and steady-state oscillation. Further testing is conducted under partial shading conditions. The same patterns as those used in the simulation are tested here. All the numerical data of the shading patterns given in Table 4 are loaded into the PV simulator. Three patterns are shown in Figure 22, i.e., PSC 1, PSC 2, and PSC 3. Figure 21: Modified LFO at 200 W/m\({}^{2}\), (a), (b), (c) reflect same result. Figure 20: Modified LFO at 600 W/m\({}^{2}\), (a), (b), (c) reflect same result. Figure 23 shows the experimental results for the proposed modified LFO tested under PSC 1. Based on the experimental results, the proposed algorithm is able to track GMPP at 17 W. It clearly shows that the proposed modified LFO has zero steady-state oscillation and it is stable. The proposed modified LFO is more stable due to its random searching behavior, where it has ability to control the speed, i.e., either longer or shorter jumps.