Adaptive Trigger Compensation Neural Network for PID Tuning in Virtual Autopilot Heading Control
Abstract
1. Introduction
2. Preliminaries
3. Methodology
3.1. Adaptive Trigger Filtering
3.2. Dynamic Parameter Updating
3.3. Error-Based Compensation Synthesizing
Algorithm 1 Q-waypoint flight mission using ATC-NN-PID method |
4. Experiments and Discussion
4.1. Even-Waypoint Simulation
4.2. Odd-Waypoint Simulation
4.3. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Waypoint | Latitude (°) | Longitude (°) | Altitude (m) |
---|---|---|---|
0 | 56.42 | 163.00 | 5000.00 |
1 | 57.00 | 164.55 | 5000.00 |
Method | AFT (s) | AFD (m) | AHAT (Times) | AEM (m) | AEStd (m) | R |
---|---|---|---|---|---|---|
753.62 | 112,642.64 | 17 | 686.90 | 333.03 | 0.84 | |
753.83 | 112,665.83 | 10 | 614.65 | 347.32 | 0.86 | |
752.90 | 112,629.55 | 10 | 535.54 | 302.36 | 0.99 | |
744.29 | 112,613.97 | 6 | 562.97 | 324.05 | 0.98 | |
754.37 | 112,624.83 | 9 | 556.06 | 247.38 | 0.99 | |
753.02 | 112,627.48 | 5 | 518.67 | 238.82 | 0.99 | |
754.08 | 112,633.67 | 21 | 533.46 | 336.87 | 0.98 | |
753.97 | 112,638.00 | 18 | 614.27 | 286.01 | 0.98 | |
753.77 | 112,632.98 | 12 | 533.78 | 244.10 | 0.96 |
Method | NFT | NFD | NHAT | NEM | NEStd |
---|---|---|---|---|---|
11.64 | 11.27 | 1.84 | 5.92 | 5.24 | |
11.15 | 13.02 | 1.65 | 5.65 | 5.23 | |
11.06 | 12.78 | 1.37 | 5.64 | 5.13 | |
11.32 | 12.99 | 1.50 | 5.63 | 4.95 | |
11.42 | 12.85 | 0.72 | 5.69 | 4.83 | |
11.02 | 12.96 | 1.49 | 5.61 | 4.65 | |
12.38 | 11.36 | 2.28 | 5.63 | 5.29 | |
12.96 | 11.34 | 2.15 | 5.64 | 5.02 | |
13.03 | 11.31 | 1.26 | 5.62 | 4.67 |
Waypoint | Latitude (°) | Longitude (°) | Altitude (m) |
---|---|---|---|
0 | 30.50 | 127.00 | 5000.00 |
1 | 31.25 | 126.50 | 5000.00 |
2 | 32.15 | 125.95 | 5000.00 |
3 | 32.90 | 125.50 | 5000.00 |
4 | 33.75 | 126.25 | 5000.00 |
Method | AFT (s) | AFD (m) | AHAT (Times) | AEM (m) | AEStd (m) | R |
---|---|---|---|---|---|---|
3010.40 | 419,704.13 | 77 | 2518.51 | 1151.65 | 0.77 | |
3005.91 | 419,197.00 | 76 | 1577.62 | 951.20 | 0.78 | |
2999.03 | 418,132.58 | 48 | 1097.12 | 846.06 | 0.86 | |
3001.63 | 418,482.46 | 72 | 1042.42 | 770.71 | 0.89 | |
3004.79 | 419,120.52 | 116 | 1085.30 | 608.11 | 0.83 | |
3043.90 | 424,571.25 | 98 | 880.43 | 606.60 | 0.94 | |
3057.99 | 427,338.67 | 93 | 927.25 | 715.48 | 0.80 | |
3019.01 | 421,028.54 | 79 | 1418.08 | 897.77 | 0.68 | |
3063.99 | 427,907.67 | 98 | 940.59 | 650.94 | 0.93 |
Method | NFT | NFD | NHAT | NEM | NEStd |
---|---|---|---|---|---|
13.65 | 11.81 | 3.97 | 7.41 | 6.34 | |
13.59 | 11.77 | 3.12 | 7.06 | 6.58 | |
14.09 | 12.25 | 3.00 | 7.02 | 6.56 | |
12.00 | 13.97 | 3.68 | 6.43 | 6.37 | |
14.39 | 12.39 | 4.37 | 6.72 | 5.96 | |
14.43 | 12.46 | 3.73 | 5.84 | 5.84 | |
14.18 | 12.22 | 3.84 | 5.90 | 5.99 | |
14.18 | 12.19 | 3.52 | 6.74 | 6.35 | |
13.84 | 11.91 | 3.83 | 6.04 | 5.68 |
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Zhou, Y.; Fu, S. Adaptive Trigger Compensation Neural Network for PID Tuning in Virtual Autopilot Heading Control. Machines 2025, 13, 933. https://doi.org/10.3390/machines13100933
Zhou Y, Fu S. Adaptive Trigger Compensation Neural Network for PID Tuning in Virtual Autopilot Heading Control. Machines. 2025; 13(10):933. https://doi.org/10.3390/machines13100933
Chicago/Turabian StyleZhou, Yutong, and Shan Fu. 2025. "Adaptive Trigger Compensation Neural Network for PID Tuning in Virtual Autopilot Heading Control" Machines 13, no. 10: 933. https://doi.org/10.3390/machines13100933
APA StyleZhou, Y., & Fu, S. (2025). Adaptive Trigger Compensation Neural Network for PID Tuning in Virtual Autopilot Heading Control. Machines, 13(10), 933. https://doi.org/10.3390/machines13100933