A Novel Guidance Law for Intercepting a Highly Maneuvering Target
Given the resolution of the guidance for intercepting highly maneuvering targets, a novel finite-time convergent guidance law is proposed, which takes the following conditions into consideration, including the impact angle constraint, the guidance command input saturation constraint, and the autopil...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/2326323 |
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| _version_ | 1832557124396253184 |
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| author | Gang Wu Ke Zhang |
| author_facet | Gang Wu Ke Zhang |
| author_sort | Gang Wu |
| collection | DOAJ |
| description | Given the resolution of the guidance for intercepting highly maneuvering targets, a novel finite-time convergent guidance law is proposed, which takes the following conditions into consideration, including the impact angle constraint, the guidance command input saturation constraint, and the autopilot second-order dynamic characteristics. Firstly, based on the nonsingular terminal sliding mode control theory, a finite-time convergent nonsingular terminal sliding mode surface is designed. On the back of the backstepping control method, the virtual control law appears. A nonlinear first-order filter is constructed so as to address the “differential expansion” problem in traditional backstepping control. By designing an adaptive auxiliary system, the guidance command input saturation problem is dealt with. The RBF neural network disturbance observer is used for estimating the unknown boundary external disturbances of the guidance system caused by the target acceleration. The parameters of the RBF neural network are adjusted online in real time, for the purpose of improving the estimation accuracy of the RBF neural network disturbance observer and accelerating its convergence characteristics. At the same time, an adaptive law is designed to compensate the estimation error of the RBF neural network disturbance observer. Then, the Lyapunov stability theory is used to prove the finite-time stability of the guidance law. Finally, numerical simulations verify the effectiveness and superiority of the proposed guidance law. |
| format | Article |
| id | doaj-art-b8fee03ce544422395e5451763a285ff |
| institution | Kabale University |
| issn | 1687-5974 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-b8fee03ce544422395e5451763a285ff2025-02-03T05:43:35ZengWileyInternational Journal of Aerospace Engineering1687-59742021-01-01202110.1155/2021/2326323A Novel Guidance Law for Intercepting a Highly Maneuvering TargetGang Wu0Ke Zhang1School of AstronauticsSchool of AstronauticsGiven the resolution of the guidance for intercepting highly maneuvering targets, a novel finite-time convergent guidance law is proposed, which takes the following conditions into consideration, including the impact angle constraint, the guidance command input saturation constraint, and the autopilot second-order dynamic characteristics. Firstly, based on the nonsingular terminal sliding mode control theory, a finite-time convergent nonsingular terminal sliding mode surface is designed. On the back of the backstepping control method, the virtual control law appears. A nonlinear first-order filter is constructed so as to address the “differential expansion” problem in traditional backstepping control. By designing an adaptive auxiliary system, the guidance command input saturation problem is dealt with. The RBF neural network disturbance observer is used for estimating the unknown boundary external disturbances of the guidance system caused by the target acceleration. The parameters of the RBF neural network are adjusted online in real time, for the purpose of improving the estimation accuracy of the RBF neural network disturbance observer and accelerating its convergence characteristics. At the same time, an adaptive law is designed to compensate the estimation error of the RBF neural network disturbance observer. Then, the Lyapunov stability theory is used to prove the finite-time stability of the guidance law. Finally, numerical simulations verify the effectiveness and superiority of the proposed guidance law.http://dx.doi.org/10.1155/2021/2326323 |
| spellingShingle | Gang Wu Ke Zhang A Novel Guidance Law for Intercepting a Highly Maneuvering Target International Journal of Aerospace Engineering |
| title | A Novel Guidance Law for Intercepting a Highly Maneuvering Target |
| title_full | A Novel Guidance Law for Intercepting a Highly Maneuvering Target |
| title_fullStr | A Novel Guidance Law for Intercepting a Highly Maneuvering Target |
| title_full_unstemmed | A Novel Guidance Law for Intercepting a Highly Maneuvering Target |
| title_short | A Novel Guidance Law for Intercepting a Highly Maneuvering Target |
| title_sort | novel guidance law for intercepting a highly maneuvering target |
| url | http://dx.doi.org/10.1155/2021/2326323 |
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