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Three-dimensional finite-time guidance law based on sliding mode adaptive RBF neural network against a highly manoeuvering target

Published online by Cambridge University Press:  10 January 2022

G. Wu Open the ORCID record for G. Wu [Opens in a new window] ,
K. Zhang  and
Z. Han
G. Wu*
Affiliation:
School of Astronautics, Northwestern Polytechnical University, Xi’an, China
K. Zhang
Affiliation:
School of Astronautics, Northwestern Polytechnical University, Xi’an, China
Z. Han
Affiliation:
School of Astronautics, Northwestern Polytechnical University, Xi’an, China
*
E-mail: [email protected]
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Abstract

In order to intercept a highly manoeuvering target with an ideal impact angle in the three-dimensional space, this paper promises to probe into the problem of three-dimensional terminal guidance. With the goal of the highly target acceleration and short terminal guidance time, a guidance law, based on the advanced fast non-singular terminal sliding mode theory, is designed to quickly converge the line-of-sight (LOS) angle and the LOS angular rate within a finite time. In the design process, the target acceleration is regarded as an unknown boundary external disturbance of the guidance system, and the RBF neural network is used to estimate it. In order to improve the estimation accuracy of RBF neural network and accelerate its convergence, the parameters of RBF neural network are adjusted online in real time. At the same time, an adaptive law is designed to compensate the estimation error of the RBF neural network, which improves the convergence speed of the guidance system. Theoretical analysis demonstrates that the state and the sliding manifold of the guidance system converge in finite time. According to Lyapunov theory, the stability of the system can be guaranteed by online adjusting the parameters of RBF neural network and adaptive parameters. The numerical simulation results verify the effectiveness and superiority of the proposed guidance law.

Keywords

Highly manoeuvering targetsFinite-time convergenceRBF neural networkTerminal sliding modeAdaptive law
Type
Research Article
Information
The Aeronautical Journal , Volume 126 , Issue 1301 , July 2022 , pp. 1124 - 1143
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Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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References

Ben-Asger, J.Z., Farber, N. and Levinson, S. New proportional navigation law for ground-to-air systems, J. Guidance Control Dyn., 2003, 26, (5), pp 822–825.CrossRefGoogle Scholar
Gao, C., Li, J., Feng, T. and Jing, W. Adaptive terminal guidance law with impact-angle constraint, Aeronaut. J., 2018, 122, (1249), pp 369–389.Google Scholar
Yang, C.D. and Yang, C.C. Analytical solution of three-dimensional realistic true proportional navigation, J. Guidance Control Dyn., 1996, 19, (3), pp 569–577.CrossRefGoogle Scholar
Chakravarthy, A. and Ghose, D. Capturability of realistic generalized true proportional navigation, IEEE Trans. Aerospace Electron. Syst., 1996, 32, (1), pp 407–418.Google Scholar
Li, K.B., Zhang, T.T. and Chen, L. Ideal proportional navigation for exoatmospheric interception, Chin. J. Aeronaut., 2013, 26, (4), pp 976–985.CrossRefGoogle Scholar
Cho, N. and Kim, Y. Modified pure proportional navigation guidance law for impact time control, J. Guidance Control Dyn., 2016, 39, (4), pp 852–872.Google Scholar
Cho, N., Kim, Y. and Park, S. Three-dimensional nonlinear differential geometric path-following guidance law, J. Guidance Control Dyn., 2015, 38, (12), pp 2366–2385.CrossRefGoogle Scholar
Fu, S.N., Liu, X.D., Zhang, W.J. and Xia, Q.L. Multiconstraint adaptive three-dimensional guidance law using convex optimisation, J. Syst. Eng. Electron., 2020, 31, (4), pp 791–803.Google Scholar
He, S.M., Wang, W. and Wang, J. Three-dimensional impact angle guidance laws based on model predictive control and sliding mode disturbance observer, J. Dyn. Syst. Meas. Controls, 2016, 138, (8), pp 1–8.Google Scholar
Li, G.L. and Ji, H.B. A three-dimensional robust nonlinear terminal guidance law with ISS finite-time convergence, Int. J. Control, 2016, 89, (5), pp 938–949.CrossRefGoogle Scholar
Man, C.Y., Liu, R.J. and Li, S.H. Three-dimensional suboptimal guidance law based on theta - D technique and nonlinear disturbance observer, J. Aerospace Eng., 2019, 233, (14), pp 5122–5133.Google Scholar
Weiss, G. and Rusnak, I. All-aspect three-dimensional guidance law based on feedback linearisation, J. Guidance Control Dyn., 2015, 38, (12), pp 2421–2428.Google Scholar
Yan, X.H., Zhu, J.H., Kuang, M.C. and Yuan, X.M. A computational-geometry-based 3-dimensional guidance law to control impact time and angle, Aerospace Sci. Technol., 2020, 98, pp 1–12.CrossRefGoogle Scholar
Ji, Y., Lin, D.F., Wang, W., Hu, S.Y. and Pei, P. Three-dimensional terminal angle constrained robust guidance law with autopilot lag consideration, Aerospace Sci. Technol., 2020, 86, pp 160–176.Google Scholar
Shafiei, M.H. and Vazirpour, N. The approach of partial stabilisation in design of discrete-time robust guidance laws against manoeuvering targets, Aeronaut. J., 2020, 124, (1277), pp 1114–1127.CrossRefGoogle Scholar
Guo, J., Li, Y. and Zhou, J. A new continuous adaptive finite time guidance law against highly manoeuvering targets, Aerospace Sci. Technol., 2019, 85, pp 40–47.CrossRefGoogle Scholar
Li, K.-B., Shin, H.-S. and Tsourdos, A. Capturability of a sliding-mode guidance law with finite-time convergence, IEEE Trans. Aerospace Electron. Syst., 2020, 56, (3), pp 2312–2325.Google Scholar
Zhang, W.J., Xia, Q.L. and Li, W. Novel second-order sliding mode guidance law with an impact angle constraint that considers autopilot lag for intercepting manoeuvering targets, Aeronaut. J., 2020, 124, (1279), pp 1350–1370.CrossRefGoogle Scholar
He, S.M., Lin, D.F. and Wang, J. Continuous second-order sliding mode based impact angle guidance law, Aerospace Sci. Technol., 2015, 41, pp 199–208.CrossRefGoogle Scholar
Sun, L., Wang, W., Yi, R. and Xiong, S. A novel guidance law using fast terminal sliding mode control with impact angle constraints, ISA Trans., 2016, 64, pp 12–23.Google ScholarPubMed
Song, J., Song, S. and Zhou, H. Adaptive nonsingular fast terminal sliding mode guidance law with impact angle constraints, Int. J. Control Autom. Syst., 2016, 14, (1), pp 99–114.CrossRefGoogle Scholar
He, S. and Lin, D. Sliding mode-based continuous guidance law with terminal angle constraint, Aeronaut. J., 2016, 120, (1229), pp 1175–1195.CrossRefGoogle Scholar
Wu, K., Cai, Z.H., Zhao, J. and Wang, Y.X. Target tracking based on a nonsingular fast terminal sliding mode guidance law by fixed-wing UAV, Appl. Sci., 2017, 7, (4), pp 1–18.Google Scholar
Zhao, Z.H., Li, C.T., Yang, J. and Li, S.H. Output feedback continuous terminal sliding mode guidance law for missile-target interception with autopilot dynamics, Aerospace Sci. Technol., 2019, 86, pp 256–267.CrossRefGoogle Scholar
Xu, S., Gao, M., Fang, D., Wang, Y. and Li, B.C. A novel adaptive second-order nonsingular terminal sliding mode guidance law design, J. Aerospace Eng., 2020, 234, (16), pp 2263–2273.Google Scholar
Zhang, W.J., Fu, S.N., Li, W. and Xia, Q.L. An impact angle constraint integral sliding mode guidance law for manoeuvering targets interception, J. Syst. Eng. Electron., 2020, 31, (1), pp 168–184.Google Scholar
Song, J.H. and Song, S.M. Three-dimensional guidance law based on adaptive integral sliding mode control, Chin. J. Aeronaut., 2016, 29, (1), pp 202–214.CrossRefGoogle Scholar
Meng, K.Z. and Zhou, D. Super-twisting integral-sliding-mode guidance law considering autopilot dynamics, J. Aerospace Eng., 2018, 232, (9), pp 1787–1799.Google Scholar
Kumar, S.R. and Ghose, D. Three-dimensional impact angle guidance with coupled engagement dynamics, J. Aerospace Eng., 2017, 231, (4), pp 621–641.Google Scholar
Zhang, N., Gai, W.D., Zhong, M.Y. and Zhang, J. A fast finite-time convergent guidance observer for unmanned aerial vehicles law with nonlinear disturbance collision avoidance, Aerospace Sci. Technol., 2019, 86, pp 204–214.Google Scholar
Zhao, F.J. and You, H. New three-dimensional second-order sliding mode guidance law with impact-angle constraints, Aeronaut. J., 2019, 124, (1273), pp 368–384.CrossRefGoogle Scholar
Yang, F. and Xia, G. A finite-time 3D guidance law based on fixed-time convergence disturbance observer, Chin. J. Aeronaut., 2020, 33, (4), pp 1299–1310.Google Scholar
Ma, K.M., Khalil, H.K. and Yao, Y. Guidance law implementation with performance recovery using an extended high-gain observer, Aerospace Sci. Technol., 2013, 24, (1), pp 177–186.Google Scholar
Chwa, D. Robust nonlinear disturbance observer based adaptive guidance law against uncertainties in missile dynamics and target maneuver, IEEE Trans. Aerospace Electron. Syst., 2018, 54, (4), pp 1739–1749.CrossRefGoogle Scholar
Lin, C.L., Hsieh, S.L. and Lin, Y.P. Trajectory estimation based on extended state observer with Fal-filter, Aeronaut. J., 2015, 119, (1218), pp 1017–1031.Google Scholar
Zhao, E.J., Chao, T., Wang, S.Y. and Yang, M. Multiple flight vehicles cooperative guidance law based on extended state observer and finite time consensus theory, J. Aerospace Eng., 2018, 232, (2), pp 270–279.Google Scholar
Duan, M.J., Zhou, D. and Cheng, D.L. Extended state observer-based finite-time guidance laws on account of thruster dynamics, J. Aerospace Eng., 2019, 233, (12), pp 4583–4597.Google Scholar
Liao, F., Luo, Q., Ji, H.B. and Gai, W. Guidance laws with input saturation and nonlinear robust H-infinity observers, ISA Trans., 2016, 63, pp 20–31.CrossRefGoogle Scholar
Si, Y. and Song, S. Adaptive reaching law based three-dimensional finite-time guidance law against manoeuvering targets with input saturation, Aerospace Sci. Technol., 2017, 70, pp 198–210.CrossRefGoogle Scholar
Si, Y. and Song, S. Three-dimensional adaptive finite-time guidance law for intercepting manoeuvering targets, Chin. J. Aeronaut., 2017, 30, (6), pp 1985–2003.CrossRefGoogle Scholar
Jiang, Y., Wang, Q. and Dong, C. A reaching law based neural network terminal sliding-mode guidance law design, TENCON 2013-2013 IEEE Region 10 Conference (31194), 2013.CrossRefGoogle Scholar