# Precise Mission Process Control Based on a Novel Dual-Code Group Network Plan Diagram
## 6 Results and Discussion
### Experiment Results and Discussion
#### 6.3.3 Experiment 3: With Disturbance and with Control
In order to satisfy the demand for D3, a control quantity \(u_{D_{2}}(30)=-3\) is generated; in order to satisfy the demand for C3, a control quantity \(u_{C_{2}}(30)=-1\) is generated; and in order to satisfy the demand for F3, a control quantity \(u_{F_{2}}(30)=-1\) is generated. As illustrated in Figure 20f, the system error is zero at \(t=31\), and the plan start time of E7 is postponed to 110 min. From the entire control process, it can be observed that the control strategy is adept at skillfully associating seemingly unrelated missions, effectively determining controlled missions, and eliminating errors. Furthermore, after applying the control quantity, we compare Figure 20b with Figure 20c. Two new critical paths are added to the network plan diagram at \(t=31\), but the critical paths at \(t=30\) still exist. This also verifies the correctness of the core path conservation theorem given in Theorem 6. The application of a control quantity may result in the addition of new critical paths, but the original critical paths do not disappear. As shown in Figure 20g, there are two critical paths in the network plan diagram when \(t=42\). At this moment, missions C2, C3, E1, F1, F2, and F3 are parallel to each other. E1 is in a delayed state, and as shown in Figure 20h, the delayed E1 mission is finished at \(t=43\), but compared to the last moment, the critical path has changed. This is due to the delay of E1, which leads to an increase in the E1 mission duration, and the sum of the E1, F1, and F2 mission durations exceeds the sum of the C2 and C3 mission durations. Therefore, C2 and C3 are no longer critical missions. Consequently, delays in mission execution may result in a change to the critical path. Figure 20i shows the mission process at \(t=110\). As can be seen from the graphs, there are a total of seven delays at the E7 plan start time, but each time \(y(t)\) deviates from \(y(e)\), the system always calculates the adjustment of the plan and pulls \(y(t)\) back to \(y(e)\). This is because, as shown in \(y_{\max}\) throughout the execution of the plan as illustrated in Figure 20i, the error is consistently within the system's controllable capacity since \(y(t)\) is always smaller than \(y_{\max}\). Moreover, the elimination of all seven errors can be accomplished with one plan adjustment, demonstrating the effectiveness of the control strategy. Table 4 lists the control quantity generated by the system for each controllable moment. We can see that only the controllable missions: G2, D2, C2, F2, E4, and E6, are able to generate control quantities. Additionally, the control quantities are all negative, which means that the duration of the corresponding missions should be compressed in order to eliminate the delay disturbance. With the control strategy shown in Figure 16, the system is able to select the appropriate controllable missions and generate the appropriate control quantities. Figure 21 shows the calculation time of \(u_{i}(t)\) in each time step of Experiment 3. From Figure 21, we can see that the average time is approximately 30+ ms for calculating the control quantity when disturbances are generated, and 130+ ms for calculating the control quantity to remove the perturbation. Therefore, our control strategy can support a mission process with a second step size, which is a high accuracy control level. Figure 20: Diagram of the mission process in the case with disturbance and with control. (**a**-**c**) illustrate the mission process at \(t=3\), \(t=4\), and \(t=5\), respectively. (**d**–**f**) illustrate the mission process at \(t=29\), \(t=30\), and \(t=31\), respectively. (**g**–**i**) show the mission process at \(t=42\), \(t=43\) and \(t=110\), respectively.