Three‐dimensional impact angle‐constrained adaptive guidance law considering autopilot lag and input saturation

Lin, Defu; Ji, Yi; Wang, Wei; Wang, Yuchen; Wang, Hui; Zhang, Fubiao

doi:10.1002/rnc.4955

Cited by 29 publications

(19 citation statements)

References 39 publications

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“…To tackle challenging environment and unknown highly variable dynamics, an adaptive guidance law and integrated navigation is proposed in [3] with deep meta-RL. Meta-learning can provide adaption to unforeseen environment changes through online learning while most traditional adaptive guidance is limited to specific faults [1] [14]. In Ref.…”

Section: A Deep Rl In Guidance Law Designmentioning

confidence: 99%

“…Rising interest has been witnessed on the application of deep RL in guidance design, with great potential shown by deep reinforcement learning. Compared with guidance designed using traditional control theory [1], deep RL is a data driven method. Many recent works has utilized deep RL in guidance law design for performance enhancement [2], or for requirement traditional control theory hard to satisfy [3] [4].…”

Section: Introductionmentioning

confidence: 99%

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Range-Aware Impact Angle Guidance Law With Deep Reinforcement Meta-Learning

et al. 2020

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In this paper, a new guidance law is proposed for impact angle constrained missile with timevarying velocity against a maneuvering target. The proposed guidance law is based on model-based deep reinforcement learning (RL) technique where a deep neural network is trained to be a predictive model used in model predictive path integral (MPPI) control. Tube-MPPI, a robust approach utilizing ancillary controller for disturbance rejection, is introduced in guidance law design in this work to deal with the MPPI degradation of robustness when the deep predictive model differs with actual environment. To further improve the performance, meta-learning is utilized to enable the deep neural dynamics adapt to environment changes online. With this approach the model mismatch of the nominal controller is reduced to improve tube-MPPI performance. Furthermore, a range-aware hyperbolic function is proposed as an adaptive function in the MPPI performance index design. Thus, reduced initial acceleration command and increased terminal velocity benefit guidance performance. Numerical simulations under various conditions demonstrate the effectiveness of proposed guidance law. INDEX TERMS Missile guidance, tube model predictive control, meta-learning, deep reinforcement learning, impact angle constraint

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Section: A Deep Rl In Guidance Law Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Range-Aware Impact Angle Guidance Law With Deep Reinforcement Meta-Learning

et al. 2020

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“…This approach is also sometimes denoted as offline cooperation because there is no communication between the missiles. Several guidance laws including types of bias or gain-varying proportional navigation guidance law [7][8][9], optimal guidance law(OGL) [10,11], and sliding mode guidance law(SMGL) [6,12,13], are proposed to impose the pre-specified angle in the scenarios of stationary or maneuvering target interception. As the interception is usually operated within short time, the convergence rate is an important performance index for evaluating the guidance law.…”

Section: Introductionmentioning

confidence: 99%

“…As the interception is usually operated within short time, the convergence rate is an important performance index for evaluating the guidance law. Compared with the cooperative guidance laws in [7][8][9][10][11], the finite-time convergent cooperative guidance law [6,12,13] based on sliding mode control has faster convergence rate and higher guidance precision, but its convergence time is seriously affected by the initial states of the missiles [14]. If the initial states are unavailable, the settling time cannot be estimated prior.…”

Section: Introductionmentioning

confidence: 99%

Target Tracking Enhancement by Three-Dimensional Cooperative Guidance Law Imposing Relative Interception Geometry

Liu

Han²,

Guo

et al. 2020

Aerospace

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The problem that two cooperative missiles intercept a maneuvering target while imposing a desired relative geometry is investigated in the paper. Firstly, a three-dimensional (3D) estimation model for cooperative target tracking is proposed and the observability of the missile-target range measurement is analyzed. In order to enhance the estimation performance, a two-level cooperative interception guidance architecture is proposed which combines a coordination algorithm with a novel 3D fixed-time convergent guidance law considering line of sight (LOS) angle constraints, such that the desired relative geometry can be imposed quickly and steadily by a dynamic strategy. The effectiveness and superiority of the proposed guidance law is evidenced through the numerical simulations comparing with other guidance laws.

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“…So it is necessary to design a guidance law with antiacceleration saturation. Although the references [38,39] consider the acceleration saturation constraint when designing the guidance law, they do not consider the missile autopilot dynamics characteristics or only consider the autopilot first-order dynamic characteristics, rather than the autopilot second-order dynamic characteristics that are closer to the actual situation. In [24], the acceleration saturation constraint and the missile autopilot secondorder dynamic characteristics are noticed, but this guidance law cannot converge in a finite time.…”

mentioning

confidence: 99%

A Novel Guidance Law for Intercepting a Highly Maneuvering Target

Zhang

2021

International Journal of Aerospace Engineering

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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.

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Three‐dimensional impact angle‐constrained adaptive guidance law considering autopilot lag and input saturation

Cited by 29 publications

References 39 publications

Range-Aware Impact Angle Guidance Law With Deep Reinforcement Meta-Learning

Range-Aware Impact Angle Guidance Law With Deep Reinforcement Meta-Learning

Target Tracking Enhancement by Three-Dimensional Cooperative Guidance Law Imposing Relative Interception Geometry

A Novel Guidance Law for Intercepting a Highly Maneuvering Target

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