Adaptive neuro-fuzzy sliding mode control guidance law with impact angle constraint

Qingchun Li; Wensheng Zhang; Gang Han; Yehui Yang

Adaptive neuro-fuzzy sliding mode control guidance law with impact angle constraint

View Fulltext

Author(s): Qingchun Li ¹ ; Wensheng Zhang ¹ ; Gang Han ¹ ; Yehui Yang ¹
- Affiliations: 1: Chinese Academy of Sciences, Institute of Automation, Beijing 100190, People's Republic of China
Source: Volume 9, Issue 14, 17 September 2015, p. 2115 – 2123
DOI: 10.1049/iet-cta.2014.1206 , Print ISSN 1751-8644, Online ISSN 1751-8652

Received 21/11/2014, Accepted 25/05/2015, Revised 21/03/2015, Published 23/06/2015

This study presents a guidance law to intercept non-manoeuvring targets at a desired impact angle. The desired impact angle, defined in terms of a desired line-of-sight angle, is achieved by selecting the missile's lateral acceleration to enforce the sliding mode on a sliding surface. Then, the authors use the Lyapunov stability theory to prove the stability of the proposed non-linear sliding surface. Furthermore, they introduce the adaptive neuro-fuzzy inference system (ANFIS) to adaptively update the additional control command and reduce the high-frequency chattering of sliding mode control (SMC). The proposed guidance law, denoted ANFSMC guidance law with impact angle constraint, combines the SMC methodology with ANFIS to enhance the robustness and reduce the chattering of the system. The effectiveness of the ANFSMC guidance law is also verified by the numerical simulations.

References

1. 1)
  - 30. Bagheri, A., Peyhani, H.M., Akbari, M.: ‘Financial forecasting using ANFIS networks with quantum-behaved particle swarm optimization’, Expert Syst. Appl., 2014, 41, (14), pp. 6235–6250 (doi: 10.1016/j.eswa.2014.04.003).
2. 2)
  - 22. Wei, Y., Hou, M., Duan, G.R.: ‘Adaptive multiple sliding surface control for integrated missile guidance and autopilot with terminal angular constraint’. Proc. Chinese Control Conf., Beijing, China, 2010, pp. 2162–2166.
3. 3)
  - 6. Bryson, A., Ho, Y.: ‘Applied optimal control, optimization, estimation and control’ (Halsted Press, Hemisphere, USA, 1975).
4. 4)
  - 25. Rao, S., Ghose, D.: ‘Sliding mode control based terminal impact angle constrained guidance laws using dual sliding surface’. Proc. IEEE Workshop on Variable Structure Syst., Mumbai, India, 2012, pp. 325–330.
5. 5)
  - 26. Harl, N., Balakrishnan, S.N.: ‘Impact time and angle guidance with sliding mode control’, IEEE Trans. Control Syst. Tech., 2012, 20, (6), pp. 1436–1449 (doi: 10.1109/TCST.2011.2169795).
6. 6)
  - 14. Lee, J.I., Jeon, I.S., Tahk, M.J.: ‘Guidance law to control impact time and angle’, IEEE Trans. Aerosp. Electron. Syst., 2007, 43, (1), pp. 301–310 (doi: 10.1109/TAES.2007.357135).
7. 7)
  - 13. Jeon, I.S., Lee, J.I., Tahk, M.J.: ‘Guidance law to control impact time and angle’, Int. Conf. on Control and Automation, Budapest, Hungary, 2005, pp. 852–857.
8. 8)
  - 23. Hu, Z., Tang, X., Wang, Y.: ‘A 3-dimensional robust guidance law with impact angle constraint’. Proc. Chinese Control and Decision Conf., Mianyang, China, 2011, pp. 999–1006.
9. 9)
  - 11. Lee, Y.I., Ryoo, C.K., Kim, E.: ‘Optimal guidance with constraints on impact angle and terminal acceleration’. Presented at the AIAA Guidance, Navigation, Control Conf., Austin, TX, 2003.
10. 10)
  - 17. Akhil, G., Ghose, D.: ‘Biased PN based impact angle constrained guidance using a nonlinear engagement model’. Proc. of American Control Conf., Montreal, Canada, 2012, pp. 950–955.
11. 11)
  - 32. Takagi, T., Sugeno, M.: ‘Fuzzy identification of systems and its applications to modelling and control’, IEEE Trans. Syst. Man Cybern., 1995, 15, pp. 116–132.
12. 12)
  - 16. Jeong, S.K., Cho, S.J., Kim, E.G.: ‘Angle constraint biased PNG’. Proc. of Asian Control Conf., Melbourne, Autralia, 2004, pp. 1849–1854.
13. 13)
  - 34. Perez-Cruz, J.H., Chairez, I., de Jesus Rubio, J., Pacheco, J.: ‘Identification and control of class of non-linear systems with non-symmetric deadzone using recurrent neural networks’, IET Control Theory Appl., 2014, 8, (3), pp. 183–192 (doi: 10.1049/iet-cta.2013.0248).
14. 14)
  - 10. Ohlmeyer, E.J.: ‘Control of terminal engagement geometry using generalized vector explicit guidance’. Proc. on America Control Conf., Denver, CO, 2003.
15. 15)
  - 19. Kim, B.S., Lee, J.G., Han, H.S., et al: ‘Homing guidance with terminal angular constraint against nonmaneuvering and maneuvering targrts’. AIAA, 1997, pp. 97–3474.
16. 16)
  - 5. Kim, M., Grider, K.V.: ‘Terminal guidance law for impact attitude angle constrained flight trajectories’, IEEE Trans. Aerosp. Electron. Syst., 1973, 9, (6), pp. 852–859 (doi: 10.1109/TAES.1973.309659).
17. 17)
  - 21. Shima, T.: ‘Deviated velocity pursuit’. AIAA Guidance, Navigation, and Control Conf. and Exhibit, 2007, pp. 4364–4379.
18. 18)
  - 20. Zhou, D., Mu, C., Xu, W.: ‘Adaptive sliding-mode guidance of a homing missile’, J. Guid. Control Dyn., 1999, 22, (4), pp. 589–594 (doi: 10.2514/2.4421).
19. 19)
  - 3. Song, Q., Meng, X.: ‘Design and simulation of guidance law with angular constraint based on non-singular terminal sliding mode’, Phys. Procedia, 2012, 25, pp. 1197–1204 (doi: 10.1016/j.phpro.2012.03.111).
20. 20)
  - 9. Ryoo, C.K., Cho, H., Tahk, M.J.: ‘Closed-form solutions of optimal guidance with terminal impact angle constraint’. IEEE Conf. on Control Appl., Istanbul, Turkey, 2003.
21. 21)
  - 7. York, R.J., Pastrick, H.L.: ‘Optimal terminal guidance with constraints at a final time’, J. Spacecr. Rockets, 1977, 14, pp. 381–382 (doi: 10.2514/3.57212).
22. 22)
  - 8. Song, T.L., Shin, S.J.: ‘Time-optimal impact angle control for vertical plane engagements’, IEEE Trans. Aerosp. Electron. Syst., 1999, 39, (2), pp. 738–742 (doi: 10.1109/7.766954).
23. 23)
  - 4. Kim, B.S., Lee, J.G., Han, H.S.: ‘Biased PNG law for impact with angular constraint’, IEEE Trans. Aerosp. Electron. Syst., 1998, 34, (1), pp. 277–288 (doi: 10.1109/7.640285).
24. 24)
  - 1. Zhang, Q.Z., Wang, Z.B., Tao, F., et al: ‘On-line optimization design of sliding mode guidance law with multiple constraints’, Appl. Math. Model., 2013, 37, (14–15), pp. 7568–7587 (doi: 10.1016/j.apm.2013.02.030).
25. 25)
  - 2. Yoon, M.: ‘Relative circular navigation guidance for the impact angle control problem’, IEEE Trans. Aerosp. Electron. Syst., 2008, 44, (4), pp. 1449–1463 (doi: 10.1109/TAES.2008.4667721).
26. 26)
  - 15. Kim, K.S., Kim, Y.: ‘Design of generalized conceptual guidance law using aim angle’, Control Eng. Prac., 2004, 12, (3), pp. 291–298 (doi: 10.1016/S0967-0661(03)00097-2).
27. 27)
  - 31. Wai, R.J., Huang, Y.C., Yang, Z.W., Shih, C.Y.: ‘Adaptive fuzzy-neural-network velocity sensorless control for robot manipulator position tracking’, IET Control Theory Appl., 2010, 4, (6), pp. 1079–1093 (doi: 10.1049/iet-cta.2009.0166).
28. 28)
  - 28. Zhao, H., Liu, W., Yang, J., et al: ‘Design of stochastic sliding mode variable structure guidance law based on adaptive EKF’, Procedia Eng., 2011, 23, pp. 276–283 (doi: 10.1016/j.proeng.2011.11.2477).
29. 29)
  - 24. Shi, Y., Zhou, C., Huang, X., et al: ‘Intelligent fault-tolerant control for swing-arm system in the space-borne spectrograph’, Acta Astronaut., 2012, 73, pp. 67–75 (doi: 10.1016/j.actaastro.2011.12.007).
30. 30)
  - 18. Utkin, V.: ‘Sliding modes in control and optimization’ (Springer-Verlag, Berlin, 1992).
31. 31)
  - 12. Ryoo, C.K., Cho, H., Tahk, M.J.: ‘Time-to-go weighted optimal guidance with impact angle constraints’, IEEE Trans. Control Syst. Technol., 2006, 14, (3), pp. 483–492 (doi: 10.1109/TCST.2006.872525).
32. 32)
  - 27. Wen, X., Li, G., Zhang, X., et al: ‘Research on sliding-mode variable structure guidance law based on fuzzy neural network’, J. Ballistics, 2014, 26, (4), pp. 13–18.
33. 33)
  - 29. Jang, J.S.: ‘ANFIS: Adaptive-network-based fuzzy inference systems’, IEEE Trans. Syst. Man Cybern., 1993, 23, (3), pp. 665–685 (doi: 10.1109/21.256541).

Login

Not registered yet?

Share

Tools

Login to add to favourites

Key

Adaptive neuro-fuzzy sliding mode control guidance law with impact angle constraint

References

Related content