## 4 Simulation and Experimental Validation
### Comparative Verification of Experimental Results  
Based on the above simulation parameters, a 72 W flyback converter experimental platform was established based on second-order LADRC and PID control. The DSP control board DS1102 from DSPACE company was used as the main control unit in the experiment. The second-order LADRC strategy and PID control proposed in this article are compiled into a DS1102 control program through a Simulink block diagram, generating PWM signals that directly control the power switch of the flyback converter through the driving circuit. The overall framework of the experimental platform is shown in Figure 8, and the flyback converter experimental platform based on dSPACE is shown in Figure 9.  
Figure 8: The overall framework of the experimental platform.  
The experimental parameters of the main circuit of the flyback converter are shown in Table 1; the digital controller parameters and simulation parameters are the same. The comparative experimental results are shown in Figures 10 and 11. Figure 10a,b show the waveform of the system output voltage during load sag under PID and second-order LADRC, respectively. The output voltage fluctuation under PID control is 3.4 V, which means the overshoot is 28.33%. Under second-order LADRC, the output voltage fluctuation is 2.8 V, which means the overshoot is 23.33%, and the overshoot is 5% smaller, which indicates a better anti-interference effect.  
Figure 11a,b show the waveform of the output voltage when the input voltage drops under PID and second-order LADRC, respectively. The output voltage drop under PID control is 1.5 V, accounting for 12.5% of the steady-state value. Under second-order LADRC, the output voltage drop is 1.1 V, accounting for 9.17% of the steady-state value, which is 3.33% less than the steady-state value. This shows less sensitivity to input voltage changes.  
Figure 10: Experimental waveform of the system output voltage during load sag. (**a**) PID control; (**b**) second-order LADRC.  
Figure 9: CCM flyback converter experimental platform based on dSPACE.  
Table 2 summarizes and compares the control effects of these two control methods. The proposed second-order LADRC has one more degree of freedom compared to the single degree of freedom PID control; thus, it can simultaneously balance tracking performance and anti-interference ability. The presence of an observer makes it less sensitive to changes in control object parameters and stronger adaptability to nonlinear systems.  
Table 3 summarizes the comparison between this study and studies using other control methods, including PID compensation control, BP neural network PID control, and LMI-Fuzzy control. The control methods in references [34,35] are similar, both based on a one degree of freedom PID controller and utilizing intelligent algorithms for parameter optimization. Reference [36] uses fuzzy control, which is also an intelligent algorithm that requires two sensors for measurement. Compared to these three types of control, the control proposed in this study is an algorithm for offline adjustment of controller parameters. Compared to the proposed intelligent algorithm, it has less computational complexity and lower processor requirements, making it easy to implement in practical applications.