Article(id=1148011746515743323, tenantId=1146029695717560320, journalId=1146119989267898375, issueId=1149298831252079541, articleNumber=null, orderNo=null, doi=10.7654/j.issn.2097-1974.20240207, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1648137600000, receivedDateStr=2022-03-25, revisedDate=1656691200000, revisedDateStr=2022-07-02, acceptedDate=null, acceptedDateStr=null, onlineDate=1751636929396, onlineDateStr=2025-07-04, pubDate=1713974400000, pubDateStr=2024-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1751636929396, onlineIssueDateStr=2025-07-04, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1751636929396, creator=13701087609, updateTime=1751636929396, updator=13701087609, issue=Issue{id=1149298831252079541, tenantId=1146029695717560320, journalId=1146119989267898375, year='2024', volume='47', issue='2', pageStart='1', pageEnd='106', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1751943794309, creator=13701087609, updateTime=1754895895552, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1161680841353552315, tenantId=1146029695717560320, journalId=1146119989267898375, issueId=1149298831252079541, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1161680841353552316, tenantId=1146029695717560320, journalId=1146119989267898375, issueId=1149298831252079541, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=51, endPage=58, ext={EN=ArticleExt(id=1148011746796761704, articleId=1148011746515743323, tenantId=1146029695717560320, journalId=1146119989267898375, language=EN, title=Sliding-mode-control based Cooperative Guidance Law in Active Aircraft Defense for Measurement Observability Enhancement, columnId=1154057567841014343, journalTitle=Missiles and Space Vehicles, columnName=Guidance, Navigation and Control, runingTitle=null, highlight=null, articleAbstract=

The active aircraft defense problem with unknown attacking missile's guidance law is considered, and the one-way and two-way cooperation modes for a target aircraft and a defending missile are introduced. Cooperative guidance laws for the target and defender are proposed by using sliding mode control, which can enhance the measurement observability and meanwhile guarantee the successful defensive interception. A sliding surface is firstly constructed, considering both the requirements of estimation enhancement and successful interception. And then the one-way and two-way cooperative guidance laws are derived, by adopting the double-power reaching law and the state-feedback based exponential reaching law respectively. Compared with one-way cooperative guidance law, the two-way cooperative guidance law is optimized by introducing the cost function of control effort for the target and defender. Meanwhile, in two-way cooperation mode, the target aircraft can take the cooperative maneuver to help defender impact the attacking missile with less control effort. Simulation results show that the proposed cooperative guidance law can guarantee both the good measurement observability and the well defensive guidance accuracy.

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针对敌方来袭拦截弹制导策略未知的主动防御协同突防场景,考虑目标弹-防御弹单向和双向协同配合模式,采用滑模控制方法提出了兼顾拦截弹探测信息可观测性和防御弹反拦截精度的协同突防制导律。构建了融合空间探测构型需求和拦截成功必要条件的滑模面,分别应用双幂次趋近律和带状态反馈的指数型趋近律,推导了目标弹-防御弹的单/双向协同制导律。相较于单向协同,双向协同通过引入加速度代价函数,应用最优化方法优化了协同突防制导律,目标弹通过协作机动帮助防御弹降低打击来袭拦截弹的过载需求。仿真结果表明,协同滑模突防制导律可确保目标弹和防御弹达到期望的空间探测构型,并能够精准地打击来袭拦截弹。

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王昌平(1998—),男,硕士研究生,主要研究方向为多智能体协同制导与控制。

方峰(1991—),男,博士,主要研究方向为飞行器协同制导与控制、智能决策。

王振亚(1990—),男,高级工程师,主要研究方向为多智能体决策与控制。

彭冬亮(1977—),男,教授,主要研究方向为模式识别与智能系统、导航制导控制等。

谢俊伟(1998—),男,硕士研究生,主要研究方向为智能决策与控制。

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王昌平(1998—),男,硕士研究生,主要研究方向为多智能体协同制导与控制。

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方峰(1991—),男,博士,主要研究方向为飞行器协同制导与控制、智能决策。

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方峰(1991—),男,博士,主要研究方向为飞行器协同制导与控制、智能决策。

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王振亚(1990—),男,高级工程师,主要研究方向为多智能体决策与控制。

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谢俊伟(1998—),男,硕士研究生,主要研究方向为智能决策与控制。

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谢俊伟(1998—),男,硕士研究生,主要研究方向为智能决策与控制。

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Journal of Gun Launch & Control, 2022,43(3): 68-73., articleTitle=Adaptive sliding mode control of a loading manipulator based on a new approach law, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1197274441521607555, tenantId=1146029695717560320, journalId=1146119989267898375, articleId=1148011746515743323, xref=1, ext=[AuthorCompanyExt(id=1197274441529996164, tenantId=1146029695717560320, journalId=1146119989267898375, articleId=1148011746515743323, companyId=1197274441521607555, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1School of Automation,Hangzhou Dianzi University,Hangzhou,310018), AuthorCompanyExt(id=1197274441538384773, tenantId=1146029695717560320, journalId=1146119989267898375, articleId=1148011746515743323, companyId=1197274441521607555, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1杭州电子科技大学自动化学院,杭州,310018)]), AuthorCompany(id=1197274443169969031, tenantId=1146029695717560320, journalId=1146119989267898375, articleId=1148011746515743323, xref=2, ext=[AuthorCompanyExt(id=1197274443178357640, tenantId=1146029695717560320, journalId=1146119989267898375, articleId=1148011746515743323, companyId=1197274443169969031, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2China Academy of Launch Vehicle Technology,Beijing,100076), AuthorCompanyExt(id=1197274443186746249, tenantId=1146029695717560320, journalId=1146119989267898375, articleId=1148011746515743323, companyId=1197274443169969031, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2中国运载火箭技术研究院,北京,100076)])], figs=[ArticleFig(id=1197274462971278256, tenantId=1146029695717560320, journalId=1146119989267898375, articleId=1148011746515743323, language=EN, label=Fig. 1, caption=Active aircraft defense engagement geometry, figureFileSmall=xfZ9FryNrBUF4b4KcCh8CA==, figureFileBig=+Ut9R42UwxH1JzbqxaNshw==, tableContent=null), ArticleFig(id=1197274463646561202, tenantId=1146029695717560320, journalId=1146119989267898375, articleId=1148011746515743323, language=CN, label=图1, caption=主动防御的攻防对抗示意

${V}_{i},{\gamma }_{i},{a}_{i}\left({i =\mathrm{T},\mathrm{D},\mathrm{M}}\right)$—各导弹的速度、航向角、加速度;${\lambda }_{\mathrm{{TM}}},{r}_{\mathrm{{TM}}}$—目标弹- 拦截弹之间的视线角和相对距离;${\lambda }_{\mathrm{{DM}}},{r}_{\mathrm{{DM}}}$—防御弹-拦截弹之间的视线角和相对距离。

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增强探测信息可观测性的主动防御滑模协同突防制导律
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王昌平 1 , 方峰 1 , 王振亚 2 , 彭冬亮 1 , 谢俊伟 1
导弹与航天运载技术 | 导航、制导与控制 2024,47(2): 51-58
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导弹与航天运载技术 | 导航、制导与控制 2024, 47(2): 51-58
增强探测信息可观测性的主动防御滑模协同突防制导律
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王昌平1, 方峰1, 王振亚2, 彭冬亮1, 谢俊伟1
作者信息
  • 1杭州电子科技大学自动化学院,杭州,310018
  • 2中国运载火箭技术研究院,北京,100076
  • 王昌平(1998—),男,硕士研究生,主要研究方向为多智能体协同制导与控制。

    方峰(1991—),男,博士,主要研究方向为飞行器协同制导与控制、智能决策。

    王振亚(1990—),男,高级工程师,主要研究方向为多智能体决策与控制。

    彭冬亮(1977—),男,教授,主要研究方向为模式识别与智能系统、导航制导控制等。

    谢俊伟(1998—),男,硕士研究生,主要研究方向为智能决策与控制。

Sliding-mode-control based Cooperative Guidance Law in Active Aircraft Defense for Measurement Observability Enhancement
Changping WANG1, Feng FANG1, Zhenya WANG2, Dongliang PENG1, Junwei XIE1
Affiliations
  • 1School of Automation,Hangzhou Dianzi University,Hangzhou,310018
  • 2China Academy of Launch Vehicle Technology,Beijing,100076
出版时间: 2024-04-25 doi: 10.7654/j.issn.2097-1974.20240207
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针对敌方来袭拦截弹制导策略未知的主动防御协同突防场景,考虑目标弹-防御弹单向和双向协同配合模式,采用滑模控制方法提出了兼顾拦截弹探测信息可观测性和防御弹反拦截精度的协同突防制导律。构建了融合空间探测构型需求和拦截成功必要条件的滑模面,分别应用双幂次趋近律和带状态反馈的指数型趋近律,推导了目标弹-防御弹的单/双向协同制导律。相较于单向协同,双向协同通过引入加速度代价函数,应用最优化方法优化了协同突防制导律,目标弹通过协作机动帮助防御弹降低打击来袭拦截弹的过载需求。仿真结果表明,协同滑模突防制导律可确保目标弹和防御弹达到期望的空间探测构型,并能够精准地打击来袭拦截弹。

主动防御  /  协同制导  /  滑模控制  /  可观测性

The active aircraft defense problem with unknown attacking missile's guidance law is considered, and the one-way and two-way cooperation modes for a target aircraft and a defending missile are introduced. Cooperative guidance laws for the target and defender are proposed by using sliding mode control, which can enhance the measurement observability and meanwhile guarantee the successful defensive interception. A sliding surface is firstly constructed, considering both the requirements of estimation enhancement and successful interception. And then the one-way and two-way cooperative guidance laws are derived, by adopting the double-power reaching law and the state-feedback based exponential reaching law respectively. Compared with one-way cooperative guidance law, the two-way cooperative guidance law is optimized by introducing the cost function of control effort for the target and defender. Meanwhile, in two-way cooperation mode, the target aircraft can take the cooperative maneuver to help defender impact the attacking missile with less control effort. Simulation results show that the proposed cooperative guidance law can guarantee both the good measurement observability and the well defensive guidance accuracy.

active aircraft defense  /  cooperative guidance law  /  sliding mode control  /  measurement observability
王昌平, 方峰, 王振亚, 彭冬亮, 谢俊伟. 增强探测信息可观测性的主动防御滑模协同突防制导律. 导弹与航天运载技术, 2024 , 47 (2) : 51 -58 . DOI: 10.7654/j.issn.2097-1974.20240207
Changping WANG, Feng FANG, Zhenya WANG, Dongliang PENG, Junwei XIE. Sliding-mode-control based Cooperative Guidance Law in Active Aircraft Defense for Measurement Observability Enhancement[J]. Missiles and Space Vehicles, 2024 , 47 (2) : 51 -58 . DOI: 10.7654/j.issn.2097-1974.20240207
随着导弹防御系统的不断完善和拦截制导技术的快速发展, 空中高价值飞行器突防面临严峻挑战。目前, 飞行器突防策略主要分为反侦察类和反拦截类[1],其中反侦察类策略包括电子干扰、红外诱饵、 隐身策略等, 是一种被动突防策略, 但在敌方强大的目标探测识别与跟踪能力情况下,突防成功率将大大降低。主动防御通过释放防御弹, 对来袭拦截弹进行反拦截从而保护目标弹, 是一种高效的反拦截类突防策略。其中, 目标弹为高价值飞行器, 如具有重要战略意义的弹道导弹或空战预警机,防御弹指的是较低成本的护卫弹, 拦截弹则由导弹防御系统释放, 如THAAD、PAC-3等。主动防御是一个典型的双边三方对抗问题, 目标弹-防御弹作为协作一方, 目标弹通过协助机动, 期望帮助防御弹以较低的控制代价打击来袭拦截弹, 而来袭拦截弹则期望在规避防御弹的同时, 准确命中目标弹。目前, 已有大量文献研究了主动防御突防制导策略[2-14]
文献[2]~[4]将主动防御协同突防问题构建为最优控制问题, 根据不同制导需求设计合理的代价函数和终端约束条件, 推导了最优协同突防制导律。 但最优协同制导律性能易受目标加速度和剩余飞行时间等状态估计精度的影响。文献[5]~[7]使用三点导引法原理设计协同制导律, 其基本思想是在制导过程中确保防御弹始终处于拦截弹-目标弹的视线上。 但是三点导引法在面对高速机动目标时, 存在容易陷入过载饱和而导致制导精度低的问题。文献[8]$\sim$[11]将主动防御问题构建为以突防方和拦截方组成的微分对策问题, 但是推导得到的微分对策制导律在模型不匹配和不确定因素影响下,制导效果难以达到预期。上述大部分文献研究是在线性运动学模型基础上开展的, 但是当主动防御攻防对抗过程不满足小角度线性化假设时, 上述协同制导律性能将急剧下降。 由此,文献[12]~[14]在非线性运动学模型基础上, 根据不同的制导需求设计合理的滑模面, 应用滑模控制理论推导得到了相应的协同突防制导律。
目标的状态估计信息是制导过程中重要的输入信息来源, 目标状态估计精度直接影响了制导性能。因此, 需要在制导律设计过程中兼顾目标状态估计性能。文献[15]和[16]通过理论分析和仿真测试发现, 增大目标弹-拦截弹与防御弹-拦截弹的视线夹角能够提升突防方关于拦截弹探测信息的可观测度, 从而提升协同突防制导精度。因此, 本文将对拦截弹目标信息的可观测性反映到目标弹和防御弹的探测空间构型中, 并将其以一个期望的弹目视线角差值引入到滑模制导律设计中。在非线性主动防御运动学模型基础上, 针对单向和双向协同配合模式, 推导了具有两种不同趋近特性的协同滑模制导律。通过大量仿真对比,验证了本文提出的协同滑模制导方法可以较好地兼顾对目标探测的可观测性及协同突防制导精度。
图1为主动防御攻防对抗示意,其中T、D、M分别表示目标弹、防御弹和来袭拦截弹, 目标弹为空中高价值目标飞行器, 在敌方拦截系统探测到目标弹后, 经过拦截预判和发射诸元等计算, 在特定时刻发射拦截弹对目标弹实施拦截。目标弹在发现拦截弹威胁后,在合适的距离释放携带的防御弹进行主动防御。本文考虑的是主动防御的末制导阶段, 在该阶段拦截弹已通过目标识别与跟踪系统, 准确锁定目标弹, 对其进行末制导拦截。同时, 目标弹和防御弹也实时对拦截弹进行探测跟踪, 获取拦截弹状态估计信息,应用于协同制导律的计算。由图1可知, 主动防御攻防对抗问题可以表示为防御弹-拦截弹和拦截弹- 目标弹的两组追逃问题。
根据图1可建立主动防御的非线性运动学模型为
$\left\{\begin{matrix}{\dot{\lambda }}_{\mathrm{M}}= {V}_{\mathrm{M}}\sin \left({{\gamma }_{\mathrm{M}}- {\lambda }_{i\mathrm{M}}}\right)/{r}_{i\mathrm{M}}- {V}_{i}\sin \left({{\gamma }_{i}- {\lambda }_{i\mathrm{M}}}\right)/{r}_{i\mathrm{M}}\\{\ddot{\lambda }}_{\mathrm{M}}= {a}_{\mathrm{M}}\cos \left({{\gamma }_{\mathrm{M}}- {\lambda }_{i\mathrm{M}}}\right)/{r}_{i\mathrm{M}}- {a}_{i}\cos \left({{\gamma }_{i}- {\lambda }_{i\mathrm{M}}}\right)/{r}_{i\mathrm{M}}- \\ 2{\dot{r}}_{i\mathrm{M}}{\dot{\lambda }}_{\mathrm{M}}/{r}_{i\mathrm{M}}\\{\dot{r}}_{i\mathrm{M}}= {V}_{\mathrm{M}}\cos \left({{\gamma }_{\mathrm{M}}- {\lambda }_{i\mathrm{M}}}\right)- {V}_{i}\cos \left({{\gamma }_{i}- {\lambda }_{i\mathrm{M}}}\right)\\{\dot{\gamma }}_{i}= {a}_{i}/{V}_{i}\end{matrix}\right.$
式中$i =\{\mathrm{T},\mathrm{D}\}, j =\{\mathrm{T},\mathrm{D},\mathrm{M}\}$
图1${\theta }_{\mathrm{{DT}}}$为目标弹-拦截弹和防御弹-拦截弹视线角偏差值,满足${\theta }_{\mathrm{{DT}}}= {\lambda }_{\mathrm{{TM}}}- {\lambda }_{\mathrm{{DM}}}$。由文献[16]可知, 增加${\theta }_{\mathrm{{DT}}}$可以增强目标角度探测信息的可观测度。因此,在制导律设计中引入${\theta }_{\mathrm{{DT}}}= {\theta }_{\mathrm{f}}$的视线角偏差目标约束,其中,${\theta }_{\mathrm{f}}$为在反拦截时刻${t}_{\mathrm{f}}$时期望的视线角偏差。 满足上述约束条件, 则能够确保目标弹和防御弹对拦截弹保持期望的空间探测几何构型, 由此确保收获较好的目标协同状态估计精度。
${\Psi }_{\mathrm{{DT}}}$为实际和期望视线角偏差值的偏离量,满足${\Psi }_{\mathrm{{DT}}}= {\theta }_{\mathrm{{DT}}}- {\theta }_{\mathrm{f}}$。对状态变量${\Psi }_{\mathrm{{DT}}}$求二阶导数,可得:
${\ddot{\Psi }}_{\mathrm{{DT}}}= {\ddot{\lambda }}_{\mathrm{{TM}}}- {\ddot{\lambda }}_{\mathrm{{DM}}}\\= {a}_{\mathrm{D}}\cos \left({{\gamma }_{\mathrm{D}}- {\lambda }_{\mathrm{{DM}}}}\right)/{r}_{\mathrm{{DM}}}- {a}_{\mathrm{T}}\cos \left({{\gamma }_{\mathrm{T}}- {\lambda }_{\mathrm{{TM}}}}\right)/{r}_{\mathrm{{TM}}}\\+ {a}_{\mathrm{M}}\cos \left({{\gamma }_{\mathrm{M}}- {\lambda }_{\mathrm{{TM}}}}\right)/{r}_{\mathrm{{TM}}}- {a}_{\mathrm{M}}\cos \left({{\gamma }_{\mathrm{M}}- {\lambda }_{\mathrm{{DM}}}}\right)/{r}_{\mathrm{{DM}}}\\-2{\dot{r}}_{\mathrm{{TM}}}{\dot{\lambda }}_{\mathrm{{TM}}}/{r}_{\mathrm{{TM}}}+ 2{\dot{r}}_{\mathrm{{DM}}}{\dot{\lambda }}_{\mathrm{{DM}}}/{r}_{\mathrm{{DM}}}$
由于敌方来袭拦截弹的加速度信息${a}_{\mathrm{M}}$未知,因此可以将式(2)中含${a}_{\mathrm{M}}$的项视作制导控制系统的干扰$d$,满足:
$ d ={a}_{\mathrm{M}}\cos \left({{\gamma }_{\mathrm{M}}- {\lambda }_{\mathrm{{TM}}}}\right)/{r}_{\mathrm{{TM}}}- {a}_{\mathrm{M}}\cos \left({{\gamma }_{\mathrm{M}}- {\lambda }_{\mathrm{{DM}}}}\right)/{r}_{\mathrm{{DM}}}$
其中,$d$的上界${d}_{\max }$满足:
$\begin{aligned} |d|= & \left|a_{\mathrm{M}}\right|\left|\frac{\cos \left(\gamma_{\mathrm{M}}-\lambda_{\mathrm{TM}}\right)}{r_{\mathrm{TM}}}-\frac{\cos \left(\gamma_{\mathrm{M}}-\lambda_{\mathrm{DM}}\right)}{r_{\mathrm{DM}}}\right| \leqslant \\ & \left(1 / r_{\mathrm{TM}}^{t_{f}}+1 / r_{\mathrm{DM}}^{t_{f}}\right) a_{\mathrm{M}}^{\max }=d_{\max } \end{aligned}$
式中${a}_{\mathrm{M}}^{\max }$为来袭拦截弹的横向加速度上界;${r}_{\mathrm{{TM}}}^{{t}_{i}},{r}_{\mathrm{{DM}}}^{{t}_{i}}$分别为防御弹反拦截时刻${t}_{\mathrm{f}}$时目标弹-拦截弹和防御弹-拦截弹之间的距离。
将式(3)所示的干扰项代入合并式(2), 可得:
$\begin{aligned} \ddot{\Psi}_{\mathrm{DT}}= & a_{\mathrm{D}} \cos \left(\gamma_{\mathrm{D}}-\lambda_{\mathrm{DM}}\right) / r_{\mathrm{DM}}-a_{\mathrm{T}} \cos \left(\gamma_{\mathrm{T}}-\lambda_{\mathrm{TM}}\right) / r_{\mathrm{TM}}- \\ & 2 \dot{r}_{\mathrm{TM}} \dot{\lambda}_{\mathrm{TM}} / r_{\mathrm{TM}}+2 \dot{r}_{\mathrm{DM}} \dot{\lambda}_{\mathrm{DM}} / r_{\mathrm{DM}}+d \end{aligned}$
由式(5)可知,${\Psi }_{\mathrm{{DT}}}$的变化受目标弹和防御弹制导加速度的直接影响, 通过滑模控制设计合理的目标弹和防御弹的制导加速度, 可以抵消目标未知机动扰动$d$的影响,使得${\Psi }_{\mathrm{{DT}}}$按照一定的变化规律达到期望的零偏差值, 确保目标弹-防御弹达到期望的空间探测构型。由此, 在式(5)的基础上, 分别考虑目标弹- 防御弹单向和双向协同配合模式, 按照各自的协同制导目标, 应用滑模控制理论和最优化理论推导相应的协同制导律。
考虑目标弹-防御弹单向协同配合模式, 在此情况下目标弹采取独立机动, 将自身信息单向传递给防御弹, 而防御弹则结合目标弹和来袭拦截弹信息进行反拦截制导。同时考虑目标可探测性和突防制导精度的需求, 设计了如下滑模面:
$ s ={\dot{\Psi }}_{\mathrm{{DT}}}+ \mu {\Psi }_{\mathrm{{DT}}},\mu > 0 $
分析式(6)可知,当系统状态到达滑模切换面$s = 0$时,满足${\Psi }_{\mathrm{{DT}}}= {\Psi }_{\mathrm{{DT}}}\left({t}_{0}\right){\mathrm{e}}^{-{\mu t}}$,其中${t}_{0}$表示系统状态到达切换面的初始时刻, 随后系统状态将沿着切换面趋于零点。状态量${\Psi }_{\mathrm{{DT}}}$趋于零可以确保视线角偏差达到期望值, 从而保证达到期望的空间探测构型。同时,${\dot{\Psi }}_{\mathrm{{DT}}}$也趋于零则确保了${\dot{\lambda }}_{\mathrm{{TM}}}- {\dot{\lambda }}_{\mathrm{{DM}}}= 0$,由于拦截弹的捕获制导律会使得${\lambda }_{\mathrm{{TM}}}$趋向于零,因此${\lambda }_{\mathrm{{DM}}}$也会逐渐趋于零。${\lambda }_{\mathrm{{DM}}}= 0$为防御弹能够成功打击拦截弹的充分条件, 从而可以确保反拦截的成功。综上分析, 式(6)所示的滑模面能够同时实现增强拦截弹目标状态可观测性和防御弹成功打击拦截弹的双重需求。为了满足不同场景下的制导需求, 本节分别应用双幂次趋近律和带状态反馈的指数型趋近律设计了两种防御弹单向协同滑模制导律。
首先, 为了确保滑模控制系统在有限时间收敛, 采用双幂次趋近律设计防御弹的滑模制导律, 其趋近律表达式为
$\dot{s}= -{\mu }_{1}{\left| s\right|}^{{a}_{1}}\operatorname{sign}\left( s\right)- {\mu }_{2}{\left| s\right|}^{{a}_{2}}\operatorname{sign}\left( s\right)$
其中,${\mu }_{1}> 0,{\mu }_{2}> 0,0 <{a}_{1}< 1,{a}_{2}> 1$
由文献[17]可知, 双幂次趋近律具有全局固定时间收敛特性, 收敛时间存在一个与滑模初值无关的上界,满足${T}_{\max }= 1/{\mu }_{1}\left({1 -{a}_{1}}\right)+ 1/{\mu }_{2}\left({{a}_{2}-1}\right)$,且当滑模存在有界扰动时, 双幂次趋近律也可以使滑模状态量在有限时间收敛到稳态误差界内。
对式(6)所示的滑模面求导,并将式(5)带入, 可得:
$\dot{s}= -{a}_{\mathrm{T}}\cos \left({{\gamma }_{\mathrm{T}}- {\lambda }_{\mathrm{{TM}}}}\right)/{r}_{\mathrm{{TM}}}+ N +{a}_{\mathrm{D}}\cos \left({{\gamma }_{\mathrm{D}}- {\lambda }_{\mathrm{{DM}}}}\right)/{r}_{\mathrm{{DM}}}+ d$
式中$N = 2{\dot{r}}_{\mathrm{{DM}}}{\dot{\lambda }}_{\mathrm{{DM}}}/{r}_{\mathrm{{DM}}}-2{\dot{r}}_{\mathrm{{TM}}}{\dot{\lambda }}_{\mathrm{{TM}}}/{r}_{\mathrm{{TM}}}+ \mu {\dot{\Psi }}_{\mathrm{{DT}}}$
考虑干扰为零的情况, 同时令滑模面以式(7)所示的双幂次趋近律形式趋向于切换面, 可推导得到的防御弹制导律为
${a}_{\mathrm{D}}= \frac{{r}_{\mathrm{{DM}}}}{\cos \left({{\gamma }_{\mathrm{D}}- {\lambda }_{\mathrm{{DM}}}}\right)} \\{\left(\frac{\cos \left({{\gamma }_{\mathrm{T}}- {\lambda }_{\mathrm{{TM}}}}\right)}{{r}_{\mathrm{{TM}}}}{a}_{\mathrm{T}}- N -{\mu }_{1}{\left| s\right|}^{{a}_{1}}\operatorname{sign}\left( s\right)- {\mu }_{2}{\left| s\right|}^{{a}_{2}}\operatorname{sign}\left( s\right)\right)}^{2}$
定理1: 由式(9)所示的单向协同滑模制导律可以确保系统状态轨迹在有限时间收敛到以下区域:
$\left\{\begin{array}{ll}\left| s\right|\leq \min \left\{{{\Delta }_{1},{\Delta }_{2}}\right\}, &\left|\dot{s}\right|\leq \min \left\{{{\Delta }_{3},{\Delta }_{4}}\right\}+ 2{d}_{\max }\\{\Delta }_{1}= {\left({d}_{\max }/{\mu }_{2}\right)}^{1/{a}_{2}},& {\Delta }_{2}= {\left({d}_{\max }/{\mu }_{1}\right)}^{1/{a}_{1}},\\{\Delta }_{3}= {\mu }_{1}{\left({d}_{\max }/{\mu }_{2}\right)}^{{a}_{1}/{a}_{2}},& {\Delta }_{4}= {\mu }_{2}{\left({d}_{\max }/{\mu }_{1}\right)}^{{a}_{2}/{a}_{1}}\end{array}\right.$
证明: 定义Lyapunov函数为
$ V ={0.5}{s}^{2}$
对式(11)求导, 并将式(8)和式(9)代入可得:
$\begin{aligned} \dot{V}= & s\left(-\mu_{1}|s|^{a_{1}} \operatorname{sign}(s)-\mu_{2}|s|^{a_{2}} \operatorname{sign}(s)+d\right) \leqslant \\ & -\mu_{1}|s|^{a_{1}+1}-\mu_{2}|s|^{a_{2}+1}+d_{\max }|s| \end{aligned}$
式(12)可以表述为如下两种形式:
$\dot{V}\leq -{\mu }_{1}{\left| s\right|}^{{a}_{1}+ 1}- \left| s\right|\left({{\mu }_{2}{\left| s\right|}^{{a}_{2}}- {d}_{\max }}\right)$
$\dot{V}\leq -\left| s\right|\left({{\mu }_{1}{\left| s\right|}^{{a}_{1}}- {d}_{\max }}\right)- {\mu }_{2}{\left| s\right|}^{{a}_{2}+ 1}$
$s$满足不等式$\left({{\mu }_{2}{\left| s\right|}^{{a}_{2}}- {d}_{\max }}\right)> 0$,即当$V \geq {V}_{1}=$${0.5}{\left({d}_{\max }/{\mu }_{2}\right)}^{2/{a}_{2}}$时,由式(13)可知:
$\dot{V}\leq -{\mu }_{1}{2}^{\left({{a}_{1}+ 1}\right)/2}{V}^{\left({{a}_{1}+ 1}\right)/2}$
$V$${V}_{0}= {0.5}{s}_{0}^{2}$收敛到${V}_{1}$所需要的时间${T}_{1}$满足${T}_{1}\leq {T}_{1\max }$,其中:
$\begin{aligned} T_{1 \max }= & \int_{V_{1}}^{V_{0}} \frac{1}{\mu_{1} 2^{\left(a_{1}+1\right) / 2} V^{\left(a_{1}+1\right) / 2}} \mathrm{~d} V= \\ & \left(\left(d_{\max } / \mu_{1}\right)^{\left(1-a_{1}\right) / a_{2}}-\left|s_{0}\right|^{1-a_{1}}\right) /\left(\mu_{1}\left(a_{1}-1\right)\right) \end{aligned}$
故对于式(13), 系统可在有限时间内收敛到:
$\left| s\right|\leq {\Delta }_{1}= {\left({d}_{\max }/{\mu }_{2}\right)}^{1/{a}_{2}}$
对于式(14), 可以利用和式(13)类似的分析,$V$${V}_{0}$收敛到${V}_{2}$所需要的时间${T}_{2}$满足${T}_{2}\leq {T}_{2\max }$,其中:
$\begin{aligned} T_{2 \max }= & \int_{V_{2}}^{V_{0}} \frac{1}{\mu_{2} 2^{\left(a_{2}+1\right) / 2} V^{\left(a_{2}+1\right) / 2}} \mathrm{~d} V= \\ & \left(\left(d_{\max } / \mu_{2}\right)^{\left(1-a_{2}\right) / a_{1}}-\left|s_{0}\right|^{1-a_{2}}\right) /\left(\mu_{2}\left(a_{2}-1\right)\right) \end{aligned}$
故对于式(14),系统可在有限时间内收敛到区域:
$\left| s\right|\leq {\Delta }_{2}= {\left({d}_{\max }/{\mu }_{1}\right)}^{1/{a}_{1}}$
综上,$\left| s\right|$将在有限时间内收敛到区域:
$\left| s\right|\leq \min \left\{{{\left({d}_{\max }/{\mu }_{2}\right)}^{1/{a}_{2}},{\left({d}_{\max }/{\mu }_{1}\right)}^{1/{a}_{1}}}\right\}$
将式(9)和式(20)带入式(8)可得:
$\left|\dot{s}\right|\leq \min \left\{{{\mu }_{1}{\left({d}_{\max }/{\mu }_{2}\right)}^{{a}_{1}/{a}_{2}},{\mu }_{2}{\left({d}_{\max }/{\mu }_{2}\right)}^{{a}_{2}/{a}_{1}}}\right\}+ 2{d}_{\max }$
由此定理1得证。
分析式(9)可知,双幂次趋近滑模制导律在$\left| s\right|$接近零时,$-{\mu }_{1}{\left| s\right|}^{{a}_{1}}\operatorname{sign}\left( s\right)$项会在滑模切换面产生较大的抖振。因此, 为了削弱滑模抖振现象, 引入了一种带状态反馈的指数型趋近律[18],该趋近律表达式为
$\dot{s}= -\frac{{k}_{1}\operatorname{sat}\left( s\right)}{\beta +\left({1 +{\left| x\right|}^{-2}- \beta }\right){e}^{-\alpha \left| s\right|}}- {k}_{2}{\left| x\right|}^{\delta }s $
其中,${k}_{1}> 0,{k}_{2}> 0,\alpha > 0,0 <\beta < 1,0 <\delta < 1, x$为可选择的系统状态变量,如$x ={\Psi }_{\mathrm{{DT}}}$$x ={\dot{\Psi }}_{\mathrm{{DT}}}$,切换控制的饱和函数为
$\operatorname{sat}\left( s\right)= \left\{\begin{array}{ll}\operatorname{sign}\left( s\right), &\left| s\right|\geq \Delta \\ s/\Delta ,& \left| s\right|< \Delta \end{array}\right.$
式中$\Delta$为饱和函数的边界层厚度。
分析式(22)可知,该等式右边第2项为指数项,能够保证当$\left| s\right|$较大时,系统状态以较大的速度趋于滑模面;第1项为等速项,当$\left| s\right|$接近于零时,等速项系数衰减为$-{k}_{1}{\left| x\right|}^{2}/\left({1 +{\left| x\right|}^{2}}\right)$,此时趋近速度较小, 且$\left| x\right|$在控制律的作用下也逐渐减小到零,有效地削弱抖振现象。此外, 饱和函数在边界层采用切换控制, 也能够有效地削弱抖振。
其次, 基于带状态反馈的指数型趋近律设计防御弹的单向协同滑模制导律, 该制导律可以表示为
${a}_{\mathrm{D}}= \frac{{r}_{\mathrm{{DM}}}}{\cos \left({{\gamma }_{\mathrm{D}}- {\lambda }_{\mathrm{{DM}}}}\right)}\left\lbrack {\frac{\cos \left({{\gamma }_{\mathrm{T}}- {\lambda }_{\mathrm{{TM}}}}\right)}{{r}_{\mathrm{{TM}}}}{a}_{\mathrm{T}}- N -}\right.\\\left.{\frac{{k}_{1}\operatorname{sat}\left( s\right)}{\beta +\left({1 +{\left| x\right|}^{-2}- \beta }\right){\mathrm{e}}^{-a\left| s\right|}}- {k}_{2}{\left| x\right|}^{\delta }s -{d}_{\max }\operatorname{sign}\left( s\right)}\right\rbrack $
定理2:由式(24)所示的防御弹滑模制导律能够确保系统收敛到切换面同时使得${\Psi }_{\mathrm{{DT}}}= 0$
证明: 取式(11)所示的Lyapunov函数对式(11)求导,并将式(8)、式(24)带入可得:
$\dot{V}= s\left({-\frac{{k}_{1}\operatorname{sat}\left( s\right)}{\beta +\left({1 +{\left| x\right|}^{2}- \beta }\right){\mathrm{e}}^{-\alpha \left| s\right|}}- {k}_{2}{\left| x\right|}^{\delta }s -}\right.\\\left.{{k}_{2}{\left| x\right|}^{\delta }s -{d}_{\max }\operatorname{sign}\left( s\right)+ d}\right)\leq \\- \frac{{k}_{1}s\operatorname{sat}\left( s\right)}{\beta +\left({1 +{\left| x\right|}^{-2}- \beta }\right){\mathrm{e}}^{-\alpha \left| s\right|}}- {k}_{2}{\left| x\right|}^{\delta }{\left| s\right|}^{2}\leq 0 $
由式(25)可知,滑模能够收敛到切换面$s = 0$; 同时结合式(6)所示的滑模面分析可知, 系统状态${\Psi }_{\mathrm{{DT}}}$也能够逐渐趋于0。因此,定理2得证。
式(9)所示的双幂次趋近律下的滑模制导律具有全局固定时间收敛特性, 因此适用于实际视线角偏差距离期望值较大且需要快速收敛的场景,但在$\left| s\right|$趋于零时, 会存在一定的抖振问题。式(24)所示带状态反馈的指数型趋近律下的滑模制导律引入了带系统状态的等速项,减少了滑模抖振,可适用于缓慢趋近且系统抖振不宜频繁切换的场景。
考虑目标弹-防御弹双向协同配合模式, 在此情况下目标弹-防御弹之间通过双向通信实现信息共享, 互相协同以达到反拦截制导目标。相较于单向协同配合模式, 双向协同的优势在于目标弹可以做协助机动帮助反拦截。由此, 在单向协同的基础上, 引入目标弹-防御弹加速度加权和的目标函数, 通过优化该目标函数, 降低防御弹打击拦截弹所需要的过载, 防止防御弹加速度长时间处于饱和状态导致反拦截失败。
考虑目标弹-防御弹双向协同配合, 将式(8)重写为
$ u = A{a}_{\mathrm{T}}- D{a}_{\mathrm{D}}= N + d -\dot{s}$
其中,系数定义为$A =\cos \left({{\gamma }_{\mathrm{T}}- {\lambda }_{\mathrm{{TM}}}}\right)/{r}_{\mathrm{{TM}}}, D =\cos \left({{\gamma }_{\mathrm{D}}- }\right.$$\left.{\lambda }_{\mathrm{{DM}}}\right)/{r}_{\mathrm{{DM}}}$,将$u$视为目标弹和防御弹的复合控制律,当趋近律选择双幂次趋近律时,复合控制律$u$表达式为
$ u = N +{\mu }_{1}{\left| s\right|}^{{a}_{1}}\operatorname{sign}\left( s\right)+ {\mu }_{2}{\left| s\right|}^{{a}_{2}}\operatorname{sign}\left( s\right)$
式(27)所示的控制律能够确保$s$$\dot{s}$在有限时间内收敛到式(10)的区域, 其证明过程与定理1类似, 此处不再赘述。
当趋近律选择带状态反馈的指数型趋近律时, 设计控制律$u$的表达式为
$ u =\frac{{k}_{1}\operatorname{sat}\left( s\right)}{\beta +\left({1 +{\left| x\right|}^{-2}- \beta }\right){\mathrm{e}}^{-\alpha \left| s\right|}}+ {k}_{2}{\left| x\right|}^{\delta }s + N +{d}_{\max }\operatorname{sign}\left( s\right)$
式(28)所示的控制律能够使系统收敛, 其证明过程与式(24)定理2类似, 此处不再赘述。
由式(27)或(28)都无法唯一地确定一组目标弹-防御弹的协同制导加速度指令, 考虑在协同突防过程尽量避免目标弹和防御弹的加速度出现过载饱和问题, 引入加速度目标函数, 将该双向协同问题表述为在式(27)或(28)所示的协同滑模制导律的基础上最小化目标弹-防御弹的加速度的优化问题。
构造如下目标函数:
$ J ={\left\lbrack {\left|{\rho }_{1}{a}_{\mathrm{T}}\right|}^{p}+ {\left|{\rho }_{2}{a}_{\mathrm{D}}\right|}^{p}\right\rbrack }^{1/p}$
式中$p$为大于1的正整数;${\rho }_{1},{\rho }_{2}$为正权重系数,分别为
${\rho }_{1}= \frac{{a}_{\mathrm{D}}^{\max }}{{a}_{\mathrm{D}}^{\max }+ {a}_{\mathrm{T}}^{\max }},{\rho }_{2}= \frac{{a}_{\mathrm{T}}^{\max }}{{a}_{\mathrm{D}}^{\max }+ {a}_{\mathrm{T}}^{\max }}$
式中${a}_{\mathrm{D}}^{\max },{a}_{\mathrm{T}}^{\max }$分别为防御弹和目标弹的最大加速度。 分式(30)可知, 当防御弹的最大加速度大于目标弹时,有${\rho }_{1}> {\rho }_{2}$,此时目标函数侧重于最小化目标弹的制导加速度, 使机动能力较小的目标弹免受加速度饱和困扰; 反之, 目标函数侧重于最小化防御弹的制导加速度, 确保过载能力较小的防御弹不会长时间处于过载饱和。
将式(26)带入式(29)中,最优化问题描述为
$\mathop{\min }\limits_{{a}_{\mathrm{D}}}J\left({a}_{\mathrm{D}}\right)= {\left\lbrack {\left|\frac{{\rho }_{1}}{A}\left( u + D{a}_{\mathrm{D}}\right)\right|}^{p}+ {\left|{\rho }_{2}{a}_{\mathrm{D}}\right|}^{p}\right\rbrack }^{1/p}$
将式(31)对${a}_{\mathrm{D}}$求偏导,可得:
$\begin{aligned} \frac{\partial J}{\partial a_{\mathrm{D}}}= & {\left[\left|u+D a_{\mathrm{D}}\right|^{p-1} D\left|\rho_{1}\right|^{p} p|A|^{-p} \operatorname{sign}\left(u+D a_{\mathrm{D}}\right)+\right.} \\ & \left.\left|a_{\mathrm{D}}\right|^{p-1} p\left|\rho_{2}\right|^{p} \operatorname{sign}\left(a_{\mathrm{D}}\right)\right] \frac{J^{1-p}}{p} \end{aligned}$
令式(32)的偏导数为零, 可得:
${\left|\frac{u}{{a}_{\mathrm{D}}}+ D\right|}^{p - 1}\operatorname{sign}\left({\frac{u}{{a}_{\mathrm{D}}}+ D}\right)= -\frac{{\left| A{\rho }_{2}\right|}^{p}}{D{\left|{\rho }_{1}\right|}^{p}}$
由式(33)和式(27)可得双幂次趋近律下防御弹和目标弹的双向协同制导律为
$\left\{\begin{matrix}{a}_{\mathrm{D}}= \frac{-N -{\mu }_{1}{\left| s\right|}^{{a}_{1}}\operatorname{sign}\left( s\right)- {\mu }_{2}{\left| s\right|}^{{a}_{2}}\operatorname{sign}\left( s\right)}{D +{\left|\left({\left| A{\rho }_{2}\right|}^{p}\right)/\left({\left| D{\rho }_{1}\right|}^{p}\right)\right|}^{{\left( p - 1\right)}^{-1}}}\operatorname{sign}\left( D\right)\\{a}_{\mathrm{T}}= \frac{N +{\mu }_{1}{\left| s\right|}^{{a}_{1}}\operatorname{sign}\left( s\right)+ {\mu }_{2}{\left| s\right|}^{{a}_{2}}\operatorname{sign}\left( s\right)+ D{a}_{\mathrm{D}}}{A}\end{matrix}\right.$
将式(28)带入式(33)即可得带状态反馈的指数型趋近律下防御弹和目标弹的双向协同制导律为
$\left\{\begin{matrix}{a}_{\mathrm{D}}= \left\lbrack {-{k}_{1}\operatorname{sat}\left( s\right)/\left({\beta +\left({1 +{\left| x\right|}^{-2}- \beta }\right){\mathrm{e}}^{-\alpha \left| s\right|}}\right)}\right\rbrack -{k}_{2}{\left| x\right|}^{\delta }s - N -\\{d}_{\max }\operatorname{sign}\left( s\right)/\left\lbrack \left({D +{\left|\left( A{\rho }_{2}{\left.{}^{p}\right|}^{\prime }\right)/\left( D{\left|{\rho }_{1}\right|}^{p}\right)\right|}^{{\left( p - 1\right)}^{-1}}\operatorname{sign}\left( D\right)}\right)\right\rbrack \\{a}_{\mathrm{T}}= \left\lbrack {{k}_{1}\operatorname{sat}\left( s\right)/\left({\beta +\left({1 +{\left| x\right|}^{-2}- \beta }\right){\mathrm{e}}^{-\alpha \left| s\right|}}\right)+ {k}_{2}{\left| x\right|}^{\delta }s + N +}\right\rbrack \\{d}_{\max }\operatorname{sign}\left( s\right)+ D{a}_{\mathrm{D}}/A \end{matrix}\right.$
主动防御的仿真场景参数如下: 目标弹、防御弹和拦截弹的初始位置分别为$\left({0\mathrm{\;m},0\mathrm{\;m}}\right)\text{、}(0\mathrm{\;m}$,$0\mathrm{\;m})\text{、}\left({{6000}\mathrm{\;m},0\mathrm{\;m}}\right)$; 初始速度分别为${200}\mathrm{\;m}/\mathrm{s}$${300}\mathrm{\;m}/\mathrm{s}$${300}\mathrm{\;m}/\mathrm{s}$;初始航向角分别为${30}^{\circ }$${0}^{\circ }$${155}^{\circ }$; 可用过载分别为${20g}$${30g}$${30g}$。各导弹按照式(1)所示的非线性运动学方程进行仿真推进, 式(6)所示的滑模面参数取$\mu ={0.8}$,期望的视线角差值${\theta }_{\mathrm{f}}= {10}^{\circ }$,仿真步长为${0.001}\mathrm{\;s}$。来袭拦截弹采用比例导引, 比例导引系数为5 。首先, 考虑目标弹- 防御弹单向协同配合的场景, 该场景下假设目标弹按照预设路线飞行,令其加速度为${a}_{\mathrm{T}}= 0\mathrm{\;m}/{\mathrm{s}}^{2}$。 式(9)所示的双幂次滑模制导律的参数设置为${\mu }_{1}=$${0.05},{\mu }_{2}= {2.3},{a}_{1}= {0.3},{a}_{2}= 2$; 式(24)所示的带状态反馈的指数趋近制导律的参数设置为${k}_{1}= {10}$,${k}_{2}= {0.015},\beta ={0.01},\delta ={0.01},\alpha ={20},\Delta ={20}$,其中取系统状态变量$x ={\Psi }_{\mathrm{{DT}}}$。防御弹采用上述两种滑模制导律进行反拦截,得到的仿真结果如图2~图5所示。
图2为两种趋近律下的主动防御攻防对抗曲线, 由图2可知, 基于这两种趋近律的滑模制导律均能使防御弹成功拦截来袭拦截弹, 并且为了满足目标弹和防御弹的空间探测构型设置, 在主动防御初始阶段, 防御弹会主动拉开与目标弹之间的距离。图3显示的是不同趋近律下滑模面$s$的收敛曲线,由图3可知两种趋近律下的滑模面$s$均会趋于零,但双幂次趋近律的收敛速度更快。由图4两种趋近律下各导弹的加速度变化曲线可知, 防御弹在初始阶段需要很大的加速度来使得滑模面较快地趋于零, 因此防御弹在初始阶段陷入加速度过载饱和,当滑模面$s$趋近于零时,防御弹的加速度也逐渐趋于零。此外, 由图4的局部放大图可知, 双幂次趋近律下防御弹的加速度存在抖振问题。由图5可知, 在不同趋近律下实际视线角偏差均能够逐渐趋于期望值${\theta }_{\mathrm{f}}= {10}^{\circ }$,并且维持在期望值。
考虑目标弹-防御弹双向协同配合的场景, 当目标弹-防御弹的协同滑模制导趋近律选择为双幂次趋近律时,参数设置为${u}_{1}= {0.075},{u}_{2}= 8$; 当选择为带状态反馈的指数型趋近律时,其参数设置为${k}_{1}= {10}$,${k}_{2}= {1.7}$; 其余参数与单向协同配合下的仿真参数一致。对上述两种趋近律下的双向制导律进行仿真, 得到的仿真结果如图6~图9所示。
图6的主动防御攻防对抗曲线可知, 在不同趋近律的双向协同制导律作用下,目标弹和防御弹通过协同配合成功实现对来袭拦截弹的突防,且指数型趋近协同制导律下的目标弹和防御弹飞行轨迹更为平缓。由图7可知, 双幂次趋近律下滑模面的收敛速度要明显快于带状态反馈的指数型趋近律, 因为双幂次趋近律具有全局固定时间收敛特性, 在滑模系统初值较大时收敛速度较快。图8为不同趋近律下各弹的加速度曲线, 由图8可知双幂次趋近律下目标弹和防御弹的加速度存在抖振问题。图9为不同趋近律下视线角偏差的变化曲线, 其中双幂次趋近律下的视线角偏差可以更快地收敛到期望值。
此外, 将双幂次趋近律下的单向协同制导律和双向协同制导律进行性能对比分析, 得到的仿真结果如图10~图13所示。由图10的两种协同配合模式下的攻防对抗曲线分析可知, 在双向协同配合模式下, 为了更快地达到期望的空间探测构型, 目标弹和防御弹在主动防御初始阶段会主动拉开双方之间的距离。图11为在单/双向协同配合下滑模面的变化曲线, 对比可知在双向协同配合下滑模面的收敛速度更快, 收敛时间更短, 因为双向协同下目标弹可以做协助机动帮助防御弹进行快速反拦截。由图12的单/双向协同制导加速度曲线可知, 双向协同配合下防御弹遭受过载饱和的时间更短且控制能量更少, 但是目标弹付出了一定的控制代价。分析图13可知, 双向协同制导律使得视线角偏差值更快地达到期望值, 通过图11图13可以看出双向协同配合下防御弹能够更快地打击拦截弹。
本文针对由目标弹和防御弹组成的主动防御协同场景, 引入了突防过程中的目标探测信息可观测性的问题, 将目标可观测性问题转换为视线角偏差控制问题, 设计了相应的滑模面来确保可探测性和协同突防性能。在单向协同配合模式下, 应用两种典型的趋近律推导了防御弹的滑模制导律, 并证明了制导律的性能。在双向协同模式下, 在单向协同滑模制导的基础上, 应用最优化控制理论, 推导了双向协同滑模制导律, 兼顾了对于目标未知机动的鲁棒性和对于目标弹-防御弹的控制能量的优化。仿真结果验证了所提出的主动防御滑模单/双向协同制导律的性能, 双幂次趋近制导律收敛时间较快但存在一定抖振问题, 带状态反馈的指数型趋近制导律则可以减弱抖振现象但是趋近较缓,因此可根据不同的场景需求选择合适的滑模制导律。此外, 相较于单向协同, 双向协同制导律在目标弹付出一定的控制代价情况下,可以使防御弹以较小的控制代价打击来袭拦截弹, 避免过多地遭遇过载饱和。
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2024年第47卷第2期
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doi: 10.7654/j.issn.2097-1974.20240207
  • 接收时间:2022-03-25
  • 首发时间:2025-07-04
  • 出版时间:2024-04-25
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  • 收稿日期:2022-03-25
  • 修回日期:2022-07-02
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    1杭州电子科技大学自动化学院,杭州,310018
    2中国运载火箭技术研究院,北京,100076
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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