Smart guided missile using accelerometer and gyroscope based on backpropagation neural network method for optimal control output feedback

Kamil Faqih, Sujito Sujito, Siti Sendari, Faiz Syaikhoni Aziz


As a maritime country with a large area, besides the need to defend itself with the military, it also needs to protect itself with aerospace technology that can be controlled automatically. This research aims to develop an air defense system that can control guided missiles automatically with high accuracy. The right method can provide a high level of accuracy in controlling missiles to the targeted object. With the backpropagation neural network method for optimal control output feedback, it can process information data from the radar to control missile’s movement with a high degree of accuracy. The controller uses optimal control output feedback, which is equipped with a lock system and utilizes an accelerometer that can detect the slope of the missile and a gyroscope that can detect the slope between the target direction of the missile to follow the target, control the position, and direction of the missile. The target speed of movement can be easily identified and followed by the missile through the lock system. Sampling data comes from signals generated by radars located in defense areas and from missiles. Each part’s data processing speed is calculated using a fast algorithm that is reliable and has a level of accuracy and fast processing. Data processing impacts on the accuracy of missile movements on any change in the position and motion of targets and target speed. Improved maneuvering accuracy in the first training system can detect 1000 files with a load of 273, while in the last training, the system can detect 1000 files without a load period. So the missile can be guided to hit the target without obstacles when maneuvering.


Smart missile; backpropagation; neural network; optimal control; output feedback; lock system

Full Text:



Anthony D’Amato, “Israel’s Air Strike Against the Osiraq Reactor: ARetrospective,” Northwest. Univ. Sch. Law Sch. Commons, vol. 10 Temp. Int'l & Comp. L.J. 259-264, 2010.

E. Garcia, D. W. Casbeer, Z. E. Fuchs, and M. Pachter, “Cooperative Missile Guidance for Active Defense of Air Vehicles,” IEEE Trans. Aerosp. Electron. Syst., vol. 54, no. 2, pp. 706–721, Apr. 2018, doi: 10.1109/TAES.2017.2764269.

M. J. Castro-Toscano et al., “A methodological use of inertial navigation systems for strapdown navigation task,” in 2017 IEEE 26th International Symposium on Industrial Electronics (ISIE), Jun. 2017, pp. 1589–1595, doi: 10.1109/ISIE.2017.8001484.

Zhang Hua and Hu Xiulin, “A height-measuring algorithm applied to TERCOM radar altimeter,” in 2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE), Aug. 2010, vol. 5, pp. V5-43-V5-46, doi: 10.1109/ICACTE.2010.5579215.

M. S. Ab-Rahman and M. R. Hassan, “Lock-on range of infrared heat seeker missile,” in 2009 International Conference on Electrical Engineering and Informatics, Aug. 2009, vol. 02, pp. 472–477, doi: 10.1109/ICEEI.2009.5254691.

I. F. Gibbons and J. J. Botha, “Tactical radar missile challenges,” in 2015 IEEE Radar Conference, Oct. 2015, pp. 46–50, doi: 10.1109/RadarConf.2015.7411852.

K. Günaydin, T. Çimen, and O. Tekinalp, “Response surface based performance analysis of an Air-Defense Missile System,” in 2014 IEEE Aerospace Conference, Mar. 2014, pp. 1–10, doi: 10.1109/AERO.2014.6836276.

B. Li, G. He, and J. Wu, “A Research of Automatic Measuring and Test System of Some Surface-to-Air Missile Autopilot,” in 2009 IEEE Circuits and Systems International Conference on Testing and Diagnosis, Apr. 2009, pp. 1–3, doi: 10.1109/CAS-ICTD.2009.4960769.

T. Ender et al., “Systems-of-Systems Analysis of Ballistic Missile Defense Architecture Effectiveness Through Surrogate Modeling and Simulation,” IEEE Syst. J., vol. 4, no. 2, pp. 156–166, Jun. 2010, doi: 10.1109/JSYST.2010.2045541.

Guo-Min Zheng and Hui Gu, “Research on availability simulation of Surface-to-Air missile weapon systems,” in 2010 International Conference On Computer Design and Applications, Jun. 2010, vol. 5, pp. V5-99-V5-103, doi: 10.1109/ICCDA.2010.5540867.

X. Fu and M. Chen, “Missile Location Based on Missile-Borne Bistatic SAR,” in 2014 Seventh International Symposium on Computational Intelligence and Design, Dec. 2014, vol. 2, pp. 232–235, doi: 10.1109/ISCID.2014.106.

K. Faqih et al., “Smart grid photovoltaic system pilot scale using sunlight intensity and state of charge (SoC) battery based on Mamdani fuzzy logic control,” J. Mechatron. Electr. Power Veh. Technol., vol. 10, no. 1, Art. no. 1, Dec. 2019, doi: 10.14203/j.mev.2019.v10.36-47.

H. Modares, F. L. Lewis, and Z.-P. Jiang, “Optimal Output-Feedback Control of Unknown Continuous-Time Linear Systems Using Off-policy Reinforcement Learning,” IEEE Trans. Cybern., vol. 46, no. 11, pp. 2401–2410, Nov. 2016, doi: 10.1109/TCYB.2015.2477810.

X. Lidan, Z. Ke’nan, C. Wanchun, and Y. Xingliang, “Optimal Control and Output Feedback Considerations for Missile with Blended Aero-fin and Lateral Impulsive Thrust,” Chin. J. Aeronaut., vol. 23, no. 4, pp. 401–408, Aug. 2010, doi: 10.1016/S1000-9361(09)60234-X.

J. Sun, C. Liu, and J. Dai, “Robust optimal control for missile-target guidance systems via adaptive dynamic programming,” in 2018 Chinese Automation Congress (CAC), Nov. 2018, pp. 836–841, doi: 10.1109/CAC.2018.8623174.

F. L. Lewis, Optimal Estimation: With an Introduction to Stochastic Control Theory, 1 edition. New York: Wiley-Interscience, 1986.

T. Herlambang, E. B. Djatmiko, and H. Nurhadi, “Navigation and guidance control system of AUV with trajectory estimation of linear modelling,” in 2015 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA), Oct. 2015, pp. 184–187, doi: 10.1109/ICAMIMIA.2015.7508028.

T. Herlambang, E. B. Djatmiko, and H. Nurhadi, “Ensemble Kalman Filter with a Square Root Scheme (EnKF-SR) for Trajectory Estimation of AUV SEGOROGENI ITS,” Int. Rev. Mech. Eng. IREME, vol. 9, no. 6, pp. 553-560–560, Nov. 2015, doi: 10.15866/ireme.v9i6.6341.

D. Luo, J. Zhang, and Y. Liu, “Autopilot design for bank to turn missile,” in 2016 12th IEEE International Conference on Control and Automation (ICCA), Jun. 2016, pp. 401–406, doi: 10.1109/ICCA.2016.7505310.

S. S. Mehta, W. MacKunis, and J. W. Curtis, “Adaptive Vision-based Missile Guidance in the Presence of Evasive Target Maneuvers,” IFAC Proc. Vol., vol. 44, no. 1, pp. 5471–5476, Jan. 2011, doi: 10.3182/20110828-6-IT-1002.03258.

J. Farlik, “Simulation of surface-to-air missile units: Cluster design,” in International Conference on Military Technologies (ICMT) 2015, May 2015, pp. 1–6, doi: 10.1109/MILTECHS.2015.7153687.

S. Lee, N. Cho, and Y. Kim, “Missile Guidance Based on Tracking of Predicted Target Trajectory,” in 2018 26th Mediterranean Conference on Control and Automation (MED), Jun. 2018, pp. 229–234, doi: 10.1109/MED.2018.8442895.

D. E. Rumelhart, “Hinton and Williams, RJ (1986):‘Learning internal representations by error propagation,’” Parallel Distrib. Process., vol. 1, 1986.

Z. Deyun and Z. Feng, “Data fusion control and guidance of surface-to-air missile under the complex circumstance based on neural-net technology,” J. Syst. Eng. Electron., vol. 19, no. 5, pp. 996–1002, Oct. 2008, doi: 10.1016/S1004-4132(08)60187-5.

Y.-J. Liu, J. Li, S. Tong, and C. L. P. Chen, “Neural Network Control-Based Adaptive Learning Design for Nonlinear Systems With Full-State Constraints,” IEEE Trans. Neural Netw. Learn. Syst., vol. 27, no. 7, pp. 1562–1571, Jul. 2016, doi: 10.1109/TNNLS.2015.2508926.

V. Amrizal and Q. Aini, Kecerdasan Buatan. Halaman Moeka Publishing, 2013.

D. Huang, S. Huang, Y. Tang, W. Zhao, and W. Cao, “Matching algorithm of missile tail flame based on back-propagation neural network,” in Fourth Seminar on Novel Optoelectronic Detection Technology and Application, Feb. 2018, vol. 10697, p. 1069702, doi: 10.1117/12.2305884.

Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM


Copyright (c) 2020 Journal of Mechatronics, Electrical Power, and Vehicular Technology

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.