Hyperbolic tangent function weighted optimal intercept angle guidance law

Xiong, Shunbin; Ming-ying, Wei; Zhao, Mi; Xiong, Hui; Wang, Weihong; Zhou, Benchun

doi:10.1016/j.ast.2018.05.018

Cited by 35 publications

(20 citation statements)

References 33 publications

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“…[11] employ hyperbolic tangent function as weighting in guidance design. However, the value of this variant of hyperbolic function in [11] grows exponentially with time. A range-aware hyperbolic tangent function is designed in this work to tackle this problem.…”

Section: B Optimal Error Shaping Guidance Lawsmentioning

confidence: 99%

“…The large acceleration command consumes excessive missile momentum energy, and will result control saturation. In [11], a hyperbolic tangent function weighted guidance law is proposed trying to tackle this problem. However, the value of proposed function grows exponentially with time, thus penalizing mostly impact angle and miss distance error while neglecting acceleration loss.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, utilizing the elegant saturation property of hyperbolic tangent function, a variant of hyperbolic function is proposed in this paper that has an adjustable value during final phase of guidance. Different from [11] which use time as decision variable, range-to-go is used in this paper since it provides more accurate information about current stage of guidance. Thus, in this work, a novel range-aware hyperbolic tangent function is proposed to reduce input saturation at the initial phase of guidance.…”

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: B Optimal Error Shaping Guidance Lawsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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“…Homing guidance systems that can implement fire-andforget attacks have been rapidly developed and widely applied [1,2]. In recent years, studies on homing guidance have dealt with constraints in the angle of impact [3], mostly through the employment of optimal control theory [4][5][6][7][8][9][10][11][12][13]. Moreover, constraints on the maximum acceleration command are also commonly considered [14,15].…”

Section: Introductionmentioning

confidence: 99%

Cooperative Guidance of Seeker-Less Missiles for Precise Hit

Zhao

Xiong

2019

International Journal of Aerospace Engineering

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A novel cooperative guidance scenario is proposed that implements fire-and-forget attacks for seeker-less missiles with a cheap finder for stationary targets and without requiring real-time communication among missiles or precise position information. Within the proposed cooperative scenario, the classic leader-follower framework is utilized, and a two-stage cooperative guidance law is derived for the seeker-less missile. Linear-quadratic optimal control and biased proportional navigation guidance (PNG) are employed to develop this two-stage cooperative guidance law to minimize the control cost in the first stage and to reduce the maximum acceleration command in the second stage when the acceleration command is continuous. Simulations and comparisons are conducted that demonstrate the effectiveness and advantages of the proposed guidance law.

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“…Furthermore, if the weighting functions can be chosen arbitrarily, then the flexibility of the pathfollowing guidance design could be largely enhanced. Various weighting functions, such as constant function [16], Gaussian function [17], time-to-go function [18], exponential function [19], hyperbolic tangent function [20], and sinusoidal function [21], have been used to devise terminal guidance laws for different guidance objectives. These weighting functions have their corresponding advantages, for example, reducing sensitivity with respect to initial heading error, extending the operational margin to cope with the external disturbances in the terminal phase, or alleviating the acceleration command at the initial phase.…”

Section: Introductionmentioning

confidence: 99%

Optimal Path-Following Guidance with Generalized Weighting Functions Based on Indirect Gauss Pseudospectral Method

Chen

Wang

Yang³

2018

Mathematical Problems in Engineering

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An indirect Gauss pseudospectral method based path-following guidance law is presented in this paper. A virtual target moving along the desired path with explicitly specified speed is introduced to formulate the guidance problem. By establishing a virtual target-fixed coordinate system, the path-following guidance is transformed into a terminal guidance with impact angle constraints, which is then solved by using indirect Gauss pseudospectral method. Meanwhile, the acceleration dynamics are modeled as the first-order lag to the command. Using the receding horizon technique a closed-loop guidance law, which considers generalized weighting functions (even discontinuous) of both the states and the control cost, is derived. The accuracy and effectiveness of the proposed guidance law are validated by numerical comparisons. A STM32 Nucleo board based on the ARM Cortex-M7 processor is used to evaluate the real-time computational performance of the proposed indirect Gauss pseudospectral method. Simulations for various types of desired paths are presented to show that the proposed guidance law has better performance when compared with the existing results for pure pursuit, a nonlinear guidance law, and trajectory shaping path-following guidance and provides more degrees of freedom in path-following guidance design applications.

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Hyperbolic tangent function weighted optimal intercept angle guidance law

Cited by 35 publications

References 33 publications

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

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

Cooperative Guidance of Seeker-Less Missiles for Precise Hit

Optimal Path-Following Guidance with Generalized Weighting Functions Based on Indirect Gauss Pseudospectral Method

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