Non-contact debris removal methods are fuel-efficient in a single operation compared to contact-based strategies as spacecraft don’t need to match debris velocity.To comprehensively analyze this scheme,maneuvering sc...Non-contact debris removal methods are fuel-efficient in a single operation compared to contact-based strategies as spacecraft don’t need to match debris velocity.To comprehensively analyze this scheme,maneuvering schemes for maximum debris removal with minimum fuel consumption,including task assignment,sequence planning,and trajectory planning,must be formulated.The coupling between variables’dimensions and optimization results in task assignment poses challenges,as debris removal is repetitive and uncertain,leading to a vast search space.This paper proposes a novel Greedy Randomized Adaptive Search Procedure with Large Neighborhood and Crossover Mechanisms(GRASP-LNCM)to address this problem.The hybrid dynamic iteration mechanism improves computational efficiency and enhances the optimality of results.The model innovatively considers unsuccessful single removal by using a quantitative method to assess removal percentage.In addition,to improve the efficiency of sequence and trajectory planning,a Suboptimal Search Algorithm(SSA)based on the Lambert property and accelerated Multi-Revolution Lambert Problem(MRLP)solving strategy is established.Finally,a real Iridium-33 debris removal mission is studied.The simulation demonstrates that the proposed algorithm achieves state-of-the-art performance in several typical scenarios.Compared to the contact-based scheme,the new one is simpler,saving more fuel under certain conditions.展开更多
Rapid and reliable onboard optimization of bank angle profiles is crucial for mitigating uncertainties during Mars atmospheric entry.This paper presents a neural-network-accelerated methodology for optimizing parametr...Rapid and reliable onboard optimization of bank angle profiles is crucial for mitigating uncertainties during Mars atmospheric entry.This paper presents a neural-network-accelerated methodology for optimizing parametric bank angle profiles in Mars atmospheric entry missions.The methodology includes a universal approach to handling path constraints and a reliable solution method based on the Particle Swarm Optimization(PSO)algorithm.For illustrative purposes,a mission with the objective of maximizing terminal altitude is considered.The original entry optimization problem is converted into optimizing three coefficients for the bank angle profiles with terminal constraints by formulating a parametric Mars entry bank angle profile and constraint handling methods.The parameter optimization problem is addressed using the PSO algorithm,with reliability enhanced by increasing the PSO swarm size.To improve computational efficiency,an enhanced Deep Operator Network(Deep ONet)is used as a dynamics solver to predict terminal states under various bank angle profiles rapidly.Numerical simulations demonstrate that the proposed methodology ensures reliable convergence with a sufficiently large PSO swarm while maintaining high computational efficiency facilitated by the neural-network-based dynamics solver.Compared to the existing methodologies,this methodology offers a streamlined process,the reduced sensitivity to initial guesses,and the improved computational efficiency.展开更多
Focusing on the non-concave trajectory constraint,a sliding-mode-based nonsingular feedback fast fixed-time three-dimensional terminal guidance of rotor unmanned aerial vehicle landing,planetary landing and spacecraft...Focusing on the non-concave trajectory constraint,a sliding-mode-based nonsingular feedback fast fixed-time three-dimensional terminal guidance of rotor unmanned aerial vehicle landing,planetary landing and spacecraft rendezvous and docking terminal phase with external disturbance is investigated in this paper.Firstly,a fixed-time observer based on real-time differentiator is developed to compensate for the external disturbance,whose estimation error can converge to zero after a time independent of the initial state.Then,a sliding surface ensuring fixed-time convergence is presented.This sliding surface can guarantee that the vehicle achieves a non-concave trajectory,which is better for avoiding collision and maintaining the visibility of the landing site or docking port.Next,the nonsingular guidance ensuring the fixed-time convergence of the sliding surface is proposed,which is continuous and chatter free.At last,three numerical simulations of Mars landing are performed to validate the effectiveness and correctness of the designed scheme.展开更多
Traditional landers typically encounter difficulties achieving stable landings because of the weak gravity and complex terrain of small celestial bodies.A multi-node lander with flexible connections can improve the st...Traditional landers typically encounter difficulties achieving stable landings because of the weak gravity and complex terrain of small celestial bodies.A multi-node lander with flexible connections can improve the stability of a small celestial body landing.However,this also poses new challenges,particularly for landing guidance in hazardous terrain.To address this problem,an equivalent simplified dynamic model of a multi-node flexible lander is first constructed,and its flat output is determined.Subsequently,a trajectoryplanning method combining the flow and vector fields is designed to avoid collision,and the parameters of the vector field are optimized online according to the dynamic and obstacle constraints during the descent process to obtain a more suitable trajectory.Finally,the effectiveness of the proposed trajectory-planning method is verified through comparative simulations of landing and obstacle avoidance from the hover point to the landing area.This study offers new prospects for upcoming small celestial body landing missions in complex terrains.展开更多
In recent years,with the rapid development of unmanned systems technology,unmanned aerial vehicle(UAV)swarm formation flying has gained considerable attention[1,2].Among formation control methods,distributed architect...In recent years,with the rapid development of unmanned systems technology,unmanned aerial vehicle(UAV)swarm formation flying has gained considerable attention[1,2].Among formation control methods,distributed architectures enable the swarm to maintain the shape despite individual UAV failures or communication disruptions,thus demonstrating greater robustness.Moreover,distributed control eliminates reliance on centralized information,yielding a more balanced communication structure across the network[3].展开更多
Small bodies have the characteristics of noncooperative,irregular gravity,and complex terrain on the surface,which cause difficulties in successful landing for conventional landers.In this paper,a multinode flexible l...Small bodies have the characteristics of noncooperative,irregular gravity,and complex terrain on the surface,which cause difficulties in successful landing for conventional landers.In this paper,a multinode flexible lander is put forward to address the problem.The dynamics of this new lander are constructed based on the port-Hamilton framework.The trajectory-tracking formation controller for the lander is designed in a passive way.The proposed dynamics and controller are further validated through numerical simulations.This research presents a fresh concept that holds inspiration for future design involving small-body landers.展开更多
基金co-supported by the National Natural Science Foundation of China(Nos.U23B6001,62273118,12150008)the Fundamental Research Funds for the Central Universities,China(No.2023FRFK02043)+1 种基金the Natural Science Foundation of Heilongjiang Province,China(No.LH2022F023)China Aerospace Science and Technology Corporation Youth Talent Support Program.
文摘Non-contact debris removal methods are fuel-efficient in a single operation compared to contact-based strategies as spacecraft don’t need to match debris velocity.To comprehensively analyze this scheme,maneuvering schemes for maximum debris removal with minimum fuel consumption,including task assignment,sequence planning,and trajectory planning,must be formulated.The coupling between variables’dimensions and optimization results in task assignment poses challenges,as debris removal is repetitive and uncertain,leading to a vast search space.This paper proposes a novel Greedy Randomized Adaptive Search Procedure with Large Neighborhood and Crossover Mechanisms(GRASP-LNCM)to address this problem.The hybrid dynamic iteration mechanism improves computational efficiency and enhances the optimality of results.The model innovatively considers unsuccessful single removal by using a quantitative method to assess removal percentage.In addition,to improve the efficiency of sequence and trajectory planning,a Suboptimal Search Algorithm(SSA)based on the Lambert property and accelerated Multi-Revolution Lambert Problem(MRLP)solving strategy is established.Finally,a real Iridium-33 debris removal mission is studied.The simulation demonstrates that the proposed algorithm achieves state-of-the-art performance in several typical scenarios.Compared to the contact-based scheme,the new one is simpler,saving more fuel under certain conditions.
基金supported in part by the National Defense Basic Scientific Research Program of China(No.JCKY2021603B030)the Shenzhen Fundamental Research Program,China(No.JCYJ20220818102601004)the Science Center Program of National Natural Science Foundation of China(No.62188101)。
文摘Rapid and reliable onboard optimization of bank angle profiles is crucial for mitigating uncertainties during Mars atmospheric entry.This paper presents a neural-network-accelerated methodology for optimizing parametric bank angle profiles in Mars atmospheric entry missions.The methodology includes a universal approach to handling path constraints and a reliable solution method based on the Particle Swarm Optimization(PSO)algorithm.For illustrative purposes,a mission with the objective of maximizing terminal altitude is considered.The original entry optimization problem is converted into optimizing three coefficients for the bank angle profiles with terminal constraints by formulating a parametric Mars entry bank angle profile and constraint handling methods.The parameter optimization problem is addressed using the PSO algorithm,with reliability enhanced by increasing the PSO swarm size.To improve computational efficiency,an enhanced Deep Operator Network(Deep ONet)is used as a dynamics solver to predict terminal states under various bank angle profiles rapidly.Numerical simulations demonstrate that the proposed methodology ensures reliable convergence with a sufficiently large PSO swarm while maintaining high computational efficiency facilitated by the neural-network-based dynamics solver.Compared to the existing methodologies,this methodology offers a streamlined process,the reduced sensitivity to initial guesses,and the improved computational efficiency.
基金co-supported by the National Defense Basic Scientific Research Project,China(No.JCKY2020903B002)the National Natural Science Foundation of China(Nos.61973100,62273118 and 12150008)。
文摘Focusing on the non-concave trajectory constraint,a sliding-mode-based nonsingular feedback fast fixed-time three-dimensional terminal guidance of rotor unmanned aerial vehicle landing,planetary landing and spacecraft rendezvous and docking terminal phase with external disturbance is investigated in this paper.Firstly,a fixed-time observer based on real-time differentiator is developed to compensate for the external disturbance,whose estimation error can converge to zero after a time independent of the initial state.Then,a sliding surface ensuring fixed-time convergence is presented.This sliding surface can guarantee that the vehicle achieves a non-concave trajectory,which is better for avoiding collision and maintaining the visibility of the landing site or docking port.Next,the nonsingular guidance ensuring the fixed-time convergence of the sliding surface is proposed,which is continuous and chatter free.At last,three numerical simulations of Mars landing are performed to validate the effectiveness and correctness of the designed scheme.
基金the National Key R&D Program(grant number 2019YFA0706500)the National Defense Basic Research Projects(grant number JCKY2021603B030).
文摘Traditional landers typically encounter difficulties achieving stable landings because of the weak gravity and complex terrain of small celestial bodies.A multi-node lander with flexible connections can improve the stability of a small celestial body landing.However,this also poses new challenges,particularly for landing guidance in hazardous terrain.To address this problem,an equivalent simplified dynamic model of a multi-node flexible lander is first constructed,and its flat output is determined.Subsequently,a trajectoryplanning method combining the flow and vector fields is designed to avoid collision,and the parameters of the vector field are optimized online according to the dynamic and obstacle constraints during the descent process to obtain a more suitable trajectory.Finally,the effectiveness of the proposed trajectory-planning method is verified through comparative simulations of landing and obstacle avoidance from the hover point to the landing area.This study offers new prospects for upcoming small celestial body landing missions in complex terrains.
基金supported by Guangdong Basic and Applied Basic Research Foundation(Grant No.2023B1515120018)Shenzhen Fundamental Research Program(Grant Nos.JCYJ20241202124010014 and GXWD20231129140908002)。
文摘In recent years,with the rapid development of unmanned systems technology,unmanned aerial vehicle(UAV)swarm formation flying has gained considerable attention[1,2].Among formation control methods,distributed architectures enable the swarm to maintain the shape despite individual UAV failures or communication disruptions,thus demonstrating greater robustness.Moreover,distributed control eliminates reliance on centralized information,yielding a more balanced communication structure across the network[3].
基金supported by the National Key R&D Program(grant number 2019YFA0706500)the National Natural Science Foundation of China(grant number 62273118)National defense basic research projects(grant numbers JCKY2021603B030,JCKY2020903B002).
文摘Small bodies have the characteristics of noncooperative,irregular gravity,and complex terrain on the surface,which cause difficulties in successful landing for conventional landers.In this paper,a multinode flexible lander is put forward to address the problem.The dynamics of this new lander are constructed based on the port-Hamilton framework.The trajectory-tracking formation controller for the lander is designed in a passive way.The proposed dynamics and controller are further validated through numerical simulations.This research presents a fresh concept that holds inspiration for future design involving small-body landers.
