## 5 Simulation Results
### Comparison with Some Other Sliding Surfaces  
A comparison with various sliding surfaces reported for non-minimum phase systems is performed to further confirm the performance of the proposed methodology. The study in [17] suggests the following surface of combinations of state variables with no coefficients. \[S_{1}=I_{Lref}V_{0}-V_{ref}I_{L} \tag{12}\]  
Another surface depicted in the literature [19] is given in (13). \[S_{2}=\lambda_{1}\Big{(}V_{ref}-V_{0}\Big{)}+\gamma_{1}\Big{(}I_{ref}-I_{L} \Big{)} \tag{13}\]  
In contrast to the surfaces suggested in this study, the reference value of the inductor current (\(I_{Lref}\)) in these two surfaces cannot be generated automatically; it must be input manually. This has negative effects on the system, which is portrayed in Figures 8 and 9. Figure 8 makes it clear that the proposed sliding surface has a better effect on the system dynamics than \(S_{1}\). During sliding motions on the surfaces, chattering occurs in the state variables for both \(S\) and \(S_{1}\). On the other hand, the dynamics of the system with \(S_{1}\) exhibit very high steady-state errors, such as a 20% inaccuracy in the output voltage. A similar comparison between \(S\) and \(S_{2}\) reveals that \(S\) provides b  
Figure 8: The motion of state variables on the proposed surface and \(S_{1}\). Figure 7: The effect of \(\gamma\) on state variables. as seen in Figure 9. To minimize the steady-state error in the system throughout the simulation of \(S_{2}\), the values of \(\lambda_{1}=500\) and \(\gamma_{1}=1000\) are purposefully maintained at high values, which can also be confirmed by the value of the inductor current in Figure 9. Despite the high values, the output voltage with \(S_{2}\) also exhibits a permanent steady-state error, whereas there is no error with the proposed one. In addition to a comparison with other SMC methods published in the literature, the proposed control mechanism is also tested under variations of the input voltage, load resistance and reference voltage in order to more thoroughly analyze and validate its efficacy. **Test-1:** First, the DC input voltage \(E\) is changed from 12 to 25 V at the time \(t=0.045\) s and back again at the time \(t=0.12\) s, resulting in a 108% step variation. Figure 10 exemplifies the outcomes of the recommended technique. During an increase in \(E\), an approximately 10% overshoot is produced. With the proposed procedure, the output voltage recovered to its previous value in 25 ms. In a similar fashion, the disruptive effect that occurred at \(t=0.12\) s and caused an 11.5% undershoot was also eliminated in about 25 ms by the proposed approach. On the other hand, (11) demonstrates that the source voltage (\(E\)) is an element that influences the switching frequency. Let us investigate the switching frequency in a closed loop and open loop under start-up and steady-state conditions before considering the impact of \(E\). With (11), \(f_{s}\) can be easily calculated by recalling the control parameters in (2) and converter specifications in Table 2. The \(\Delta\) value for the switching frequency is set to \(\Delta=22\), and the frequency is calculated as \(f_{s}=100\) kHz. During the start-up, it is obvious from Figure 11 that the interval type-2 fuzzy logic controlled \(f_{s}\) converges to the reference value of 100 kHz in a shorter amount of time in the case when \(f_{s}\) is not controlled. Furthermore, it should be emphasized that \(f_{s}\) is multi-oscillating and moves away from the reference orbit in an open loop. **Test-2:** Under the 50% step load test, the effectiveness of the offered control techniques is also examined.