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AIAA SciTech Forum

作者： Takanol, Hiroyuki Shiraishi, Youhei Yamasaki, Takeshi Yamaguchi, Isao Natl Def Acad Dept Aerosp Engn Yokosuka Kanagawa 2398686 Japan Natl Def Acad Yokosuka Kanagawa 2398686 Japan

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

It is well known that the Proportional Navigation guidance (PN) is used as a terminal guidance law for missiles. It is also famous that PN is an optimal guidance under some conditions, but in the real world, PN is not always the 'optimal' guidance especially when the missile accelerates. For the accelerating missiles, Modified Proportional Navigation guidance (MPN) was proposed, although the axial acceleration of the missile was considered as constant. In fact, the missile will be accelerated nonlinearly, thus the Modified Proportional Navigation guidance (MPN) is revisited and we proposed a new method. Our method is based on the optimal trajectories and the objective function was traditional minimum squared lift coefficient integration in order to maintain the missile lift coefficient should be as small as possible. However, there are many kinds of objective functions and so are the trajectories. Thus, we considered several optimal trajectories and the corresponding guidance in this paper. Under new formulation, numerical analyses are performed. As a result, we succeeded to improve the MPN missile guidance.

关键词： Proportional Navigation terminal guidance Lift Coefficient Aerodynamic Coefficients guidance Laws Flight Path Angle Pursuit guidance Velocity Profiles Dynamic Pressure Newton's Method

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Image-Based Meta-Reinforcement Learning for Autonomous guidance of an Asteroid Impactor

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JOURNAL OF guidance CONTROL AND DYNAMICS 2022年第11期45卷 2013-2028页

作者： Federici, Lorenzo Scorsoglio, Andrea Ghilardi, Luca D'Ambrosio, Andrea Benedikter, Boris Zavoli, Alessandro Furfaro, Roberto Sapienza Univ Rome Dept Mech & Aerosp Engn Via Eudossiana 18 I-00184 Rome Italy Univ Arizona Dept Syst & Ind Engn 1127E James E Rogers Way Tucson AZ 85721 USA Sapienza Univ Rome Sch Aerosp Engn Via Salaria 851 I-00138 Rome Italy Univ Arizona Dept Aerosp & Mech Engn 1130 N Mt Ave Tucson AZ 85721 USA

This paper focuses on the use of meta-reinforcement learning for the autonomous guidance of a spacecraft during the terminal phase of an impact mission toward a binary asteroid system. The control policy is replaced by a convolutional-recurrent neural network, which is used to map optical observations collected by the onboard camera to the control thrust and thrusting times. The network is trained by a proximal policy optimization algorithm, a family of reinforcement learning methods. The final phase of NASA's Double Asteroid Redirection Test (DART) mission is used as a test case. The objective is to maneuver the spacecraft to impact the smaller object, Dimorphos, in the Didymos binary system. The spacecraft dynamics are described using the bi-elliptic restricted four-body problem with solar radiation pressure. The initial conditions are randomly scattered according to the actual specifications of the DART mission. A random error on the orbital position of Dimorphos is also considered to reflect uncertainty on the binary system's characteristics and dynamics. The control system aims at minimizing the error on the final spacecraft position. Numerical results show that the guidance system can correctly drive the spacecraft toward the final impact point in more than 98% of the 500 test scenarios.

关键词： Reinforcement Learning Potentially Hazardous Object Deep Convolutional Neural Network Markov Decision Process guidance System Optimization Algorithm Spacecraft Dynamics Solar Radiation Interplanetary Trajectories terminal guidance

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Augmented Plane Pursuit for Impact-Angle Control in Three Dimensions

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JOURNAL OF guidance CONTROL AND DYNAMICS 2022年第9期45卷 1769-1775页

作者： Tekin, Raziye Roketsan Missiles Inc Tact Missile Syst TR-06780 Ankara Turkey

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A fixed-time convergence adaptive fast sliding mode guidance law with angle constraint 11

A fixed-time convergence adaptive fast sliding mode guidance...

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11th International Conference on Control, Mechatronics and Automation (ICCMA)

作者： Liu, Yuan Yang, Zhen Huo, Weiyu He, Yupeng Zhou, Deyun Northwestern Polytech Univ Sch Elect & Informat Xian 710072 Peoples R China

ISBN: (纸本)9798350315684

In this paper, a fixed-time convergence adaptive fast sliding mode guidance law with line-of-sight (LOS) angle constraint is designed for the terminal guidance problem of large maneuvering targets in the air. Firstly, the three-dimensional (3D) spatial missile-target relative equations of motion are constructed, and the terminal guidance model with LOS angle constraints is established. Secondly, a novel fixed-time nonsingular terminal sliding mode surface is designed, and by designing a fast convergence law, while avoiding system singularity and reducing end jitter, the LOS angle and angular rate of the missile are guaranteed to converge quickly to the desired value in a fixed time, and have the advantage that the upper bound of the convergence time can be artificially set. In addition, the interference observer is constructed using the good approximation property of RBF neural network for continuous functions, which provides an effective estimation of the unknown acceleration of the intercepted target, and increases the self-adaptive capability of the system. Finally, the effectiveness and superiority of the designed guidance law is verified by simulation.

关键词： fixed time convergence adaptive sliding mode angular constraint terminal guidance neural network observer

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Maneuver-Compensated guidance Law for End-Guided Targets Under Side-Window Constraints

Maneuver-Compensated Guidance Law for End-Guided Targets Und...

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2024 International Conference on guidance, Navigation and Control

作者： Li, Liya Zhang, Xulong Qi, Guoyuan Wang, Shishen Yan, Hualong Tiangong Univ Sch Control Sci & Engn Tianjin 300387 Peoples R China South China Technol Sch Automat Sci & Engn Guangzhou 510006 Peoples R China China Fire & Rescue Inst Beijing 102202 Peoples R China

ISBN: (纸本)9789819622429;9789819622405;9789819622399

In order to realize the terminal guidance interception of high maneuvering target, a target maneuvering compensation guidance law (TMCC) based on compensation function observer (CFO) is proposed. Firstly, the relative model of missile and target is established. Then, the CFO is used to estimate the target acceleration and feed it back to the controller. Considering the side window constraint, the interceptor line of sight angle is controlled. Finally, in order to prove the high interception accuracy and low energy consumption, a comparative simulation experiment between the studied guidance law and the traditional Proportional Navigation (PN) is designed.

关键词： terminal guidance compensation function observer target maneuver compensation control interceptor

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Nonlinear Optimal Impact-Angle-Constrained guidance with Large Initial Heading Error

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JOURNAL OF guidance CONTROL AND DYNAMICS 2021年第9期44卷 1663-1676页

作者： Li, Hongyan Wang, Jiang He, Shaoming Lee, Chang-Hun Beijing Inst Technol Sch Aerosp Engn 5th Zhongguancun South Street Beijing 100081 Peoples R China Korea Adv Inst Sci & Technol Dept Aerosp Engn 291 Daehak Ro Daejeon 34141 South Korea

This paper investigates the problem of impact-angle-constrained guidance law design against maneuvering target with large initial heading error. The guidance problem is first formulated in the range domain by leveraging a relative reference frame. Based on optimal control theory and optimal error dynamics, the proposed guidance law is derived analytically without using any linearization assumptions. The approximate closed-form solution and exact numerical solution are presented to analyze the characteristics and physical meaning of the proposed guidance law. The key feature of the proposed guidance law lies in its simple implementation and exact nonlinear nature. Hence, the tolerable initial heading error of the proposed approach is larger than that of conventional linear optimal guidance laws. Numerical simulations are conducted to support the analytical findings.

关键词： Control guidance Optimal Control Numerical Simulation Flight Path Angle terminal Sliding Mode Engagement Kinematics Proportional Navigation Surface to Air Missile terminal guidance Yawing Stability

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guidance Law Design with Fixed-Time Convergent Error Dynamics

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JOURNAL OF guidance CONTROL AND DYNAMICS 2021年第7期44卷 1389-1398页

作者： Wang, Chunyan Dong, Wei Wang, Jianan Shan, Jiayuan Xin, Ming Beijing Inst Technol Sch Aerosp Engn Beijing 100081 Peoples R China Univ Missouri Dept Mech & Aerosp Engn Columbia MO 65211 USA

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Arresting-Cable System for Robust terminal Landing of Reusable Rockets

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JOURNAL OF SPACECRAFT AND ROCKETS 2021年第2期58卷 425-443页

作者： Zhang, Huan Zhao, Zhihua Ren, Gexue Hu, Pengxiang Yang, Yunfei Pan, Zhongwen Sanfedino, Francesco Tsinghua Univ Sch Aerosp Engn Beijing 100084 Peoples R China China Acad Launch Vehicle Technol Beijing Inst Space Syst Engn Beijing 100076 Peoples R China Univ Toulouse Natl Higher French Inst Aeronaut & Space F-31055 Toulouse France

Recent successful recovery techniques for rockets require that rockets maintain a vertical configuration with zero vertical and lateral velocities;otherwise, landings may fail. To relax this requirement, a new active-arresting system (inspired by the arresting gears used on aircraft carriers) is proposed herein to achieve a robust landing, even if the rocket deviates from the target position or has notable residual velocities and inclinations. The system consists of four deployable onboard hooks above the rocket's center of mass, an on-ground apparatus containing four arresting cables forming a square capture frame, and four buffer devices to actively catch and passively decelerate the landing rocket. To catch the rocket, the capture frame was controlled by servo motors via a simple proportional-derivative controller. After catching, the buffer devices generate decelerating forces to stop its motion. A flexible multibody model of the proposed system was built to evaluate its robust performance under various combinations of multiple uncertainties, such as noise measurement, time delay in the motor, initial conditions, and wind excitation. Using a quasi-Monte Carlo method, hundreds of deviated landing cases were generated and simulated. The results confirmed the robustness of the proposed system for achieving successful terminal landings.

关键词： Rocket Design Servo Motors Proportional Derivative Controller Quasi Monte Carlo Method Aircraft Carriers Arresting Gear Trusses Rocket Plane Lagrange Multipliers terminal guidance

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Robust Finite-Time Control for guidance Law with Uncertainties in Missile Dynamics

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JOURNAL OF AEROSPACE TECHNOLOGY AND MANAGEMENT 2024年 16卷

作者： Tao, Fazhan Shi, Jingtian Zhang, Jie Fu, Zhumu Gao, Song Henan Univ Sci & Technol Coll Informat Engn Luoyang Henan Peoples R China Longmen Lab Luoyang Henan Peoples R China Henan Univ Sci & Technol Henan Key Lab Robot & Intelligent Syst Luoyang Henan Peoples R China

In this paper, the robust finite-time control for impact angle guidance of missile dynamic system with uncertainties is investigated by combining linear extended state observer (LESO) and adaptive non-singular fast terminal sliding mode method. Specially for dealing with existing uncertainties including time-varying parametric perturbation and nonparametric disturbances in high order line-of-sight rates and target acceleration, a robust LESO strategy is proposed for designing sliding mode-based impact angle guidance, which can guarantee that estimation error converges to the neighborhood of the origin in finite-time. Based on the proposed LESO framework, an adaptive non-singular fast terminal sliding mode guidance law is considered for realizing interception of maneuvering targets, which can guarantee asymptotically stability of the system. Simulation results are shown for confirming effectiveness of the proposed guidance strategy of this paper. Compared with former methods, accuracy of estimation is increased by nearly two times, and miss distance is reduced by nearly two times.

关键词： terminal guidance Targets Angle of attack Missile control

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Proximal policy optimization guidance algorithm for intercepting near-space maneuvering targets

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AEROSPACE SCIENCE AND TECHNOLOGY 2023年 132卷

作者： Chen, Wenxue Gao, Changsheng Jing, Wuxing Harbin Inst Technol Sch Astronaut Harbin 150001 Peoples R China

This paper studies a novel guidance framework of the vehicle against a high-speed and maneuvering target based on deep reinforcement learning (DRL) considering the energy consumption, autopilot lag dynamics, and input saturation, which can effectively cope with the high flight-path angle error flight phase and various uncertainties. The guidance framework proposes an end-to-end mapping transformation between the guidance command and observation states consisting of line-of-sight (LOS) angle, relative distance, and their rate measured by the seeker. At the same time, the observability of the LOS angle and relative distance is included in constructing the reward function. Besides, the relative engagement kinematic model of the interceptor-target is established and combined with the PPO guidance algorithm, jointly described as a Markov decision process (MDP). Notably, the guidance framework is optimized using the improved proximal policy optimization (PPO) algorithm and demonstrated in a simulated terminal phase in the near-space. Specifically, the PPO guidance algorithm is structured by the policy (actor) neural network and the critic neural network, and both are standard fully-connected neural networks. Subsequently, observation states and rewards are fully collected and applied by introducing the experience replay method. Also, the exponential decay learning rate method, mini-batch stochastic gradient ascent (SGA) method, zero-score standardization, and Adam optimizer are proposed to train the reinforcement learning algorithm more efficiently. Moreover, the proposed guidance framework has an excellent generalization capability and guarantees the implementation of fixed and stochastic engagement scenarios, which means that the interceptor can realize the unlearned practical combat scenarios. The robust capacity is indicated and validated using Monte Carlo simulation under various uncertainties. Moreover, the DRL guidance framework can satisfy the onboard application

关键词： Deep reinforcement learning (DRL) Proximal policy optimization (PPO) Markov decision process (MDP) Near -space interception terminal guidance Maneuvering targets

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