## 4 Results and Discussion
### Experimental Verification  
In addition to computer simulation experiments, in order to verify the effective application of the master and auxiliary composite control strategy proposed in this paper in the MCCS system, a physical test platform is built in the laboratory. In the experiment, the AMESim simulation model is replaced by a physical test platform, and the LabVIEW programming controller in the simulation model is modified. Combined with a National Instruments (NI) acquisition card and output card, a 4-20 mA analog quantity is used to simulate the signal of the field sensor and the control signal of the adjusting ball valve. Through the co-simulation technology, the control parameters of the smooth switching process of the MCCS system are obtained, and are fine-tuned during the experiment process. Finally, the following control parameters are obtained: initial PID parameters \(K_{p0}\) = 4.86, \(K_{i0}\) = 3.375 and \(K_{d0}\) = 11; scale factor \(K_{Kp}\) = 0.5, \(K_{Ki}\) = 0.7 and \(K_{kd}\) = 1.67; quantization factor \(K_{e}\) = 165 and \(K_{sc}\) = 40. According to this parameter, the two-channel smooth switching is carried out in the test platform. The specific process is as follows: channel 1, channel 2 and channel 4 are connected in parallel for water supply, and channel 3 is in standby; after the start is stable, the pipeline pressures are set for the main pipe, channel 1 and  
Figure 15: Anti-interference performance curve: (a) Delay time 4 s; (b) Delay time 10 s.  
channel 4; the switch is started between channel 2 and channel 3, while channel 2 delays the switch 4 s. The opening degrees of the load simulation ball valve are 100%, 75% and 50%, respectively. Finally, the analysis experimental data are recorded, as shown in Figure 16 and Table 7.  
The following points can be identified in Figure 16.  
In different load simulations of the main pipe, adaptive fuzzy PID, variable universe fuzzy PID and master and auxiliary composite control can reduce the maximum deviation of the main pipe pressure, and the performance of the master and auxiliary composite control has a slight advantage. With the increase in the simulated load of the main pipe, the three control methods have improved the control of the deviation rate. This can be inferred from Table 7. However, the basic function of the \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Load Simulation**} & \multicolumn{5}{c}{**Maximum Deviation Rate**} \\ \cline{2-6}  & & \multicolumn{1}{c}{**No Control**} & \multicolumn{1}{c}{**Adaptive Fuzzy PID**} & \multicolumn{1}{c}{**Variable**} & \multicolumn{1}{c}{**Master and**} \\ \cline{2-6}  & & \multicolumn{1}{c}{**No Control**} & \multicolumn{1}{c}{**Analytive Fuzzy PID**} & \multicolumn{1}{c}{**Universe**} & \multicolumn{1}{c}{**Auxiliary**} \\ \hline
100\% & 0.037 & 28.9\% & 22.4\% & 20\% & 16.2\% \\
75\% & 0.05 & 26.4\% & 19.2\% & 16\% & 8\% \\
50\% & 0.127 & 15.03\% & 9.05\% & 6.45\% & 4.17\% \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Maximum deviation rates of main pipe pressures of different control methods during the switching process. Figure 16: Pressure change curve of main pipe with smooth switching under different loads: (**a**) Load simulation ball valve opening 100%; (**b**) Load simulation ball valve opening 75%; (**c**) Load simulation ball valve opening 50%. combined multi-channel concentrated water supply system is to superimpose the water supply and increase the water supply capacity. The simulated load of the main pipe cannot be too large, and the flow rate of the main pipe is lower than the flow rate provided before the aggregation. Comparing the control effect of the same main pipe load (Figures 15a and 16a), it can be seen that the adaptive fuzzy PID, the variable universe fuzzy PID and the master and auxiliary composite control are not as good as the simulation result, that is, the controlled main pipe pressure fluctuation amplitude is higher than the simulation result.