Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a gro...Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.展开更多
In this paper,a distributed Event-Triggered(ET)collision avoidance coordinated control for Quadrotor Unmanned Aerial Vehicles(QUAVs)is proposed based on Virtual Tubes(VTs)with flexible boundaries in the presence of un...In this paper,a distributed Event-Triggered(ET)collision avoidance coordinated control for Quadrotor Unmanned Aerial Vehicles(QUAVs)is proposed based on Virtual Tubes(VTs)with flexible boundaries in the presence of unknown external disturbances.Firstly,VTs are constructed for each QUAV,and the QUAV is restricted into the corresponding VT by the artificial potential field,which is distributed around the boundary of the VT.Thus,the collisions between QUAVs are avoided.Besides,the boundaries of the VTs are flexible by the modification signals,which are generated by the self-regulating auxiliary systems,to make the repulsive force smaller and give more buffer space for QUAVs without collision.Then,a novel ET mechanism is designed by introducing the concept of prediction to the traditional fixed threshold ET mechanism.Furthermore,a disturbance observer is proposed to deal with the adverse effects of the unknown external disturbance.On this basis,a distributed ET collision avoidance coordinated controller is proposed.Then,the proposed controller is quantized by the hysteresis uniform quantizer and then sent to the actuator only at the ET instants.The boundedness of the closed-loop signals is verified by the Lyapunov method.Finally,simulation and experimental results are performed to demonstrate the superiority of the proposed control method.展开更多
In this paper, distributed event-triggered performance constraint control is proposed for Heterogeneous Multiagent Systems (HMASs) including quadrotor unmanned aerial vehicles and unmanned ground vehicles in the prese...In this paper, distributed event-triggered performance constraint control is proposed for Heterogeneous Multiagent Systems (HMASs) including quadrotor unmanned aerial vehicles and unmanned ground vehicles in the presence of unknown external disturbances. To tackle the problem of different dynamic characteristics and facilitate the controller design, the virtual variable is introduced in the z axis of the nonlinear model of unmanned ground vehicles. By using this approach, a universal model is established for the HMAS. Moreover, a distributed disturbance observer is established to cope with the adverse influence of the external disturbances. Then, an Appointed-Time Prescribed Performance Function (ATPPF) is designed to restrict the tracking error in the predefined regions. On this basis, the distributed performance constraint controller is proposed for the HMAS based on the ATPPF and the distributed disturbance observer. Furthermore, the improved event-triggered mechanism is proposed with a dynamic threshold, which depends on the distance between the tracking error and the boundary of the ATPPF. Finally, the effectiveness of the proposed control method is verified by the comparative experiments on an HMAS.展开更多
This paper studies a robust adaptive compensation Fault Tolerant Control(FTC)for the medium-scale Unmanned Autonomous Helicopter(UAH)in the presence of external disturbances,actuator faults and input saturation.To imp...This paper studies a robust adaptive compensation Fault Tolerant Control(FTC)for the medium-scale Unmanned Autonomous Helicopter(UAH)in the presence of external disturbances,actuator faults and input saturation.To improve the disturbance rejection capacity of the UAH system in actuator healthy case,an adaptive control method is adopted to cope with the external disturbances and a nominal controller is proposed to stabilize the system.Meanwhile,compensation control inputs are designed to reduce the negative effects derived from actuator faults and input saturation.Based on the backstepping control and inner-outer loop control technologies,a robust adaptive FTC scheme is developed to guarantee the tracking errors convergence.Under the presented FTC controller,the uniform ultimate boundedness of all closed-loop signals is ensured via Lyapunov stability analysis.Simulation results demonstrate the effectiveness of the proposed control algorithm.展开更多
Game theory can be applied to the air combat decision-making problem of multiple unmanned combat air vehicles(UCAVs).However,it is difficult to have satisfactory decision-making results completely relying on air comba...Game theory can be applied to the air combat decision-making problem of multiple unmanned combat air vehicles(UCAVs).However,it is difficult to have satisfactory decision-making results completely relying on air combat situation information,because there is a lot of time-sensitive information in a complex air combat environment.In this paper,a constraint strategy game approach is developed to generate intelligent decision-making for multiple UCAVs in complex air combat environment with air combat situation information and time-sensitive information.Initially,a constraint strategy game is employed to model attack-defense decision-making problem in complex air combat environment.Then,an algorithm is proposed for solving the constraint strategy game based on linear programming and linear inequality(CSG-LL).Finally,an example is given to illustrate the effectiveness of the proposed approach.展开更多
In this paper,a robust tracking control scheme based on nonlinear disturbance observer is developed for the self-balancing mobile robot with external unknown disturbances.A desired velocity control law is firstly desi...In this paper,a robust tracking control scheme based on nonlinear disturbance observer is developed for the self-balancing mobile robot with external unknown disturbances.A desired velocity control law is firstly designed using the Lyapunov analysis method and the arctan function.To improve the tracking control performance,a nonlinear disturbance observer is developed to estimate the unknown disturbance of the self-balancing mobile robot.Using the output of the designed disturbance observer,the robust tracking control scheme is presented employing the sliding mode method for the selfbalancing mobile robot.Numerical simulation results further demonstrate the effectiveness of the proposed robust tracking control scheme for the self-balancing mobile robot subject to external unknown disturbances.展开更多
In this paper, a neural network based adaptive prescribed performance control scheme is proposed for the altitude and attitude tracking system of the unmanned helicopter in the presence of state and output constraints...In this paper, a neural network based adaptive prescribed performance control scheme is proposed for the altitude and attitude tracking system of the unmanned helicopter in the presence of state and output constraints. For handling the state constraints, the barrier Lyapunov function and the saturation function are employed. And, the prescribed performance method is used to deal with the flapping angle constraints for the unmanned helicopter. It is proved that the proposed control approach can ensure that all the signals of the resulting closed-loop system are bounded, and the tracking errors are within the prescribed performance bounds for all time. The numerical simulation is given to illustrate the performance of the proposed scheme.展开更多
In order to improve detection system robustness and reliability, multi-sensors fusion is used in modern air combat. In this paper, a data fusion method based on reinforcement learning is developed for multi-sensors. I...In order to improve detection system robustness and reliability, multi-sensors fusion is used in modern air combat. In this paper, a data fusion method based on reinforcement learning is developed for multi-sensors. Initially, the cubic B-spline interpolation is used to solve time alignment problems of multisource data. Then, the reinforcement learning based data fusion(RLBDF) method is proposed to obtain the fusion results. With the case that the priori knowledge of target is obtained, the fusion accuracy reinforcement is realized by the error between fused value and actual value. Furthermore, the Fisher information is instead used as the reward if the priori knowledge is unable to be obtained. Simulations results verify that the developed method is feasible and effective for the multi-sensors data fusion in air combat.展开更多
In this paper,a sliding mode observer scheme of sensor fault diagnosis is proposed for a class of time delay nonlinear systems with input uncertainty based on neural network.The sensor fault and the system input uncer...In this paper,a sliding mode observer scheme of sensor fault diagnosis is proposed for a class of time delay nonlinear systems with input uncertainty based on neural network.The sensor fault and the system input uncertainty are assumed to be unknown but bounded.The radial basis function (RBF) neural network is used to approximate the sensor fault.Based on the output of the RBF neural network,the sliding mode observer is presented.Using the Lyapunov method,a criterion for stability is given in terms of matrix inequality.Finally,an example is given for illustrating the availability of the fault diagnosis based on the proposed sliding mode observer.展开更多
The control problem is discussed for a chaotic system without equilibrium in this paper.On the basis of the linear mathematical model of the two-wheeled self-balancing robot,a novel chaotic system which has no equilib...The control problem is discussed for a chaotic system without equilibrium in this paper.On the basis of the linear mathematical model of the two-wheeled self-balancing robot,a novel chaotic system which has no equilibrium is proposed.The basic dynamical properties of this new system are studied via Lyapunov exponents and Poincar′e map.To further demonstrate the physical realizability of the presented novel chaotic system,a chaotic circuit is designed.By using fractional-order operators,a controller is designed based on the state-feedback method.According to the Gronwall inequality,Laplace transform and Mittag-Leffler function,a new control scheme is explored for the whole closed-loop system.Under the developed control scheme,the state variables of the closed-loop system are controlled to stabilize them to zero.Finally,the numerical simulation results of the chaotic system with equilibrium and without equilibrium illustrate the effectiveness of the proposed control scheme.展开更多
This paper investigates the path planning method of unmanned aerial vehicle(UAV)in threedimensional map.Firstly,in order to keep a safe distance between UAV and obstacles,the obstacle grid in the map is expanded.By us...This paper investigates the path planning method of unmanned aerial vehicle(UAV)in threedimensional map.Firstly,in order to keep a safe distance between UAV and obstacles,the obstacle grid in the map is expanded.By using the data structure of octree,the octree map is constructed,and the search nodes is significantly reduced.Then,the lazy theta*algorithm,including neighbor node search,line-of-sight algorithm and heuristics weight adjustment is improved.In the process of node search,UAV constraint conditions are considered to ensure the planned path is actually flyable.The redundant nodes are reduced by the line-of-sight algorithm through judging whether visible between two nodes.Heuristic weight adjustment strategy is employed to control the precision and speed of search.Finally,the simulation results show that the improved lazy theta*algorithm is suitable for path planning of UAV in complex environment with multi-constraints.The effectiveness and flight ability of the algorithm are verified by comparing experiments and real flight.展开更多
The robust bounded flight control scheme is developed for the uncertain longitudinal flight dynamics of the fighter with control input saturation invoking the backstepping technique. To enhance the disturbance rejecti...The robust bounded flight control scheme is developed for the uncertain longitudinal flight dynamics of the fighter with control input saturation invoking the backstepping technique. To enhance the disturbance rejection ability of the robust flight control for fighters, the sliding mode disturbance observer is designed to estimate the compounded disturbance including the unknown external disturbance and the effect of the control input saturation. Based on the backstepping technique and the compounded disturbance estimated output, the robust bounded flight control scheme is proposed for the fighter with the unknown external disturbance and the control input saturation. The closed-loop system stability under the developed robust bounded flight control scheme is rigorously proved using the Lyapunov method and the uniformly asymptotical convergences of all closed-loop signals are guaranteed. Finally, simulation results are presented to show the effectiveness of the proposed robust bounded flight control scheme for the uncertain longitudinal flight dynamics of the fighter.展开更多
In this paper, a disturbance observer-based safe tracking control scheme is proposed for a medium-scale unmanned helicopter with rotor flapping dynamics in the presence of partial state constraints and unknown externa...In this paper, a disturbance observer-based safe tracking control scheme is proposed for a medium-scale unmanned helicopter with rotor flapping dynamics in the presence of partial state constraints and unknown external disturbances. A safety protection algorithm is proposed to keep the constrained states within the given safe-set. A second-order disturbance observer technique is utilized to estimate the external disturbances. It is shown that the desired tracking performance of the controlled unmanned helicopter can be achieved with the application of the backstepping approach, dynamic surface control technique, and Lyapunov method. Finally, the availability of the proposed control scheme has been shown by simulation results.展开更多
This paper proposes a backstepping technique and Multi-dimensional Taylor Polynomial Networks(MTPN)based adaptive attitude tracking control strategy for Near Space Vehicles(NSVs)subjected to input constraints and stoc...This paper proposes a backstepping technique and Multi-dimensional Taylor Polynomial Networks(MTPN)based adaptive attitude tracking control strategy for Near Space Vehicles(NSVs)subjected to input constraints and stochastic input noises.Firstly,considering the control input has stochastic noises,and the attitude motion dynamical model of the NSVs is actually modeled as the Multi-Input Multi-Output(MIMO)stochastic nonlinear system form.Furthermore,the MTPN is used to estimate the unknown system uncertainties,and an auxiliary system is designed to compensate the influence of the saturation control input.Then,by using backstepping method and the output of the auxiliary system,a MTPN-based robust adaptive attitude control approach is proposed for the NSVs with saturation input nonlinearity,stochastic input noises,and system uncertainties.Stochastic Lyapunov stability theory is utilized to analysis the stability in the sense of probability of the entire closed-loop system.Additionally,by selecting appropriate parameters,the tracking errors will converge to a small neighborhood with a tunable radius.Finally,the numerical simulation results of the NSVs attitude motion show the satisfactory flight control performance under the proposed tracking control strategy.展开更多
文摘Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.
基金supported in part by the National Key R&D Program of China(No.2023YFB4704400)in part by the National Natural Science Foundation of China(Nos.U23B2036,U2013201).
文摘In this paper,a distributed Event-Triggered(ET)collision avoidance coordinated control for Quadrotor Unmanned Aerial Vehicles(QUAVs)is proposed based on Virtual Tubes(VTs)with flexible boundaries in the presence of unknown external disturbances.Firstly,VTs are constructed for each QUAV,and the QUAV is restricted into the corresponding VT by the artificial potential field,which is distributed around the boundary of the VT.Thus,the collisions between QUAVs are avoided.Besides,the boundaries of the VTs are flexible by the modification signals,which are generated by the self-regulating auxiliary systems,to make the repulsive force smaller and give more buffer space for QUAVs without collision.Then,a novel ET mechanism is designed by introducing the concept of prediction to the traditional fixed threshold ET mechanism.Furthermore,a disturbance observer is proposed to deal with the adverse effects of the unknown external disturbance.On this basis,a distributed ET collision avoidance coordinated controller is proposed.Then,the proposed controller is quantized by the hysteresis uniform quantizer and then sent to the actuator only at the ET instants.The boundedness of the closed-loop signals is verified by the Lyapunov method.Finally,simulation and experimental results are performed to demonstrate the superiority of the proposed control method.
基金supported in part by the National Natural Science Foundation of China(Nos.U23B2036,U2013201).
文摘In this paper, distributed event-triggered performance constraint control is proposed for Heterogeneous Multiagent Systems (HMASs) including quadrotor unmanned aerial vehicles and unmanned ground vehicles in the presence of unknown external disturbances. To tackle the problem of different dynamic characteristics and facilitate the controller design, the virtual variable is introduced in the z axis of the nonlinear model of unmanned ground vehicles. By using this approach, a universal model is established for the HMAS. Moreover, a distributed disturbance observer is established to cope with the adverse influence of the external disturbances. Then, an Appointed-Time Prescribed Performance Function (ATPPF) is designed to restrict the tracking error in the predefined regions. On this basis, the distributed performance constraint controller is proposed for the HMAS based on the ATPPF and the distributed disturbance observer. Furthermore, the improved event-triggered mechanism is proposed with a dynamic threshold, which depends on the distance between the tracking error and the boundary of the ATPPF. Finally, the effectiveness of the proposed control method is verified by the comparative experiments on an HMAS.
基金supported in part by the National Natural Science Foundation of China(Nos.61825302,61573184)in part by the Jiangsu Natural Science Foundation of China(No.BK20171417)in part by the Aeronautical Science Foundation of China(No.20165752049)
文摘This paper studies a robust adaptive compensation Fault Tolerant Control(FTC)for the medium-scale Unmanned Autonomous Helicopter(UAH)in the presence of external disturbances,actuator faults and input saturation.To improve the disturbance rejection capacity of the UAH system in actuator healthy case,an adaptive control method is adopted to cope with the external disturbances and a nominal controller is proposed to stabilize the system.Meanwhile,compensation control inputs are designed to reduce the negative effects derived from actuator faults and input saturation.Based on the backstepping control and inner-outer loop control technologies,a robust adaptive FTC scheme is developed to guarantee the tracking errors convergence.Under the presented FTC controller,the uniform ultimate boundedness of all closed-loop signals is ensured via Lyapunov stability analysis.Simulation results demonstrate the effectiveness of the proposed control algorithm.
基金supported by Major Projects for Science and Technology Innovation 2030(Grant No.2018AA0100800)Equipment Pre-research Foundation of Laboratory(Grant No.61425040104)in part by Jiangsu Province“333”project under Grant BRA2019051.
文摘Game theory can be applied to the air combat decision-making problem of multiple unmanned combat air vehicles(UCAVs).However,it is difficult to have satisfactory decision-making results completely relying on air combat situation information,because there is a lot of time-sensitive information in a complex air combat environment.In this paper,a constraint strategy game approach is developed to generate intelligent decision-making for multiple UCAVs in complex air combat environment with air combat situation information and time-sensitive information.Initially,a constraint strategy game is employed to model attack-defense decision-making problem in complex air combat environment.Then,an algorithm is proposed for solving the constraint strategy game based on linear programming and linear inequality(CSG-LL).Finally,an example is given to illustrate the effectiveness of the proposed approach.
基金supported by the National Natural Science Foundation of China(61573184)the Specialized Research Fund for the Doctoral Program of Higher Education(20133218110013)+1 种基金the Six Talents Peak Project of Jainism Province(2012-XRAY-010)the Fundamental Research Funds for theCentral Universities(NE2016101)
文摘In this paper,a robust tracking control scheme based on nonlinear disturbance observer is developed for the self-balancing mobile robot with external unknown disturbances.A desired velocity control law is firstly designed using the Lyapunov analysis method and the arctan function.To improve the tracking control performance,a nonlinear disturbance observer is developed to estimate the unknown disturbance of the self-balancing mobile robot.Using the output of the designed disturbance observer,the robust tracking control scheme is presented employing the sliding mode method for the selfbalancing mobile robot.Numerical simulation results further demonstrate the effectiveness of the proposed robust tracking control scheme for the self-balancing mobile robot subject to external unknown disturbances.
基金supported by the National Natural Science Foundation of China (Nos. 61573184, 61751210)Aeronautical Science Foundation of China (No. 20165752049)the Fundamental Research Funds for the Central Universities of China (No. NE2016101)
文摘In this paper, a neural network based adaptive prescribed performance control scheme is proposed for the altitude and attitude tracking system of the unmanned helicopter in the presence of state and output constraints. For handling the state constraints, the barrier Lyapunov function and the saturation function are employed. And, the prescribed performance method is used to deal with the flapping angle constraints for the unmanned helicopter. It is proved that the proposed control approach can ensure that all the signals of the resulting closed-loop system are bounded, and the tracking errors are within the prescribed performance bounds for all time. The numerical simulation is given to illustrate the performance of the proposed scheme.
基金supported by National Natural Science Foundation of China(61174102)Jiangsu Natural Science Foundation of China(SBK20130033)+1 种基金Aeronautical Science Foundation of China 20145152029)Specialized Research Fund for the Doctoral Program of Higher Education(20133218110013)
基金supported in part by the Major Projects for Science and Technology Innovation 2030(2018AA0100800)the Equipment Pre-research Foundation of Laboratory(61425040104)+1 种基金the Joint Fund of China Electronics Technology for Equipment Preresearch(6141B08231110a)the Funding for Short Visit Program of Nanjing University of Aeronautics and Astronautics(NUAA)(190915DF03)。
文摘In order to improve detection system robustness and reliability, multi-sensors fusion is used in modern air combat. In this paper, a data fusion method based on reinforcement learning is developed for multi-sensors. Initially, the cubic B-spline interpolation is used to solve time alignment problems of multisource data. Then, the reinforcement learning based data fusion(RLBDF) method is proposed to obtain the fusion results. With the case that the priori knowledge of target is obtained, the fusion accuracy reinforcement is realized by the error between fused value and actual value. Furthermore, the Fisher information is instead used as the reward if the priori knowledge is unable to be obtained. Simulations results verify that the developed method is feasible and effective for the multi-sensors data fusion in air combat.
基金Natural Science Foundation of Jiangsu Province (No.SBK20082815)Aeronautical Science Foundation of China (No.20075152014)
文摘In this paper,a sliding mode observer scheme of sensor fault diagnosis is proposed for a class of time delay nonlinear systems with input uncertainty based on neural network.The sensor fault and the system input uncertainty are assumed to be unknown but bounded.The radial basis function (RBF) neural network is used to approximate the sensor fault.Based on the output of the RBF neural network,the sliding mode observer is presented.Using the Lyapunov method,a criterion for stability is given in terms of matrix inequality.Finally,an example is given for illustrating the availability of the fault diagnosis based on the proposed sliding mode observer.
基金supported by the National Natural Science Foundation of China(61573184)Jiangsu Natural Science Foundation of China(SBK20130033)+1 种基金Six Talents Peak Project of Jiangsu Province(2012-XXRJ-010)Fundamental Research Funds for the Central Universities(NE2016101)
文摘The control problem is discussed for a chaotic system without equilibrium in this paper.On the basis of the linear mathematical model of the two-wheeled self-balancing robot,a novel chaotic system which has no equilibrium is proposed.The basic dynamical properties of this new system are studied via Lyapunov exponents and Poincar′e map.To further demonstrate the physical realizability of the presented novel chaotic system,a chaotic circuit is designed.By using fractional-order operators,a controller is designed based on the state-feedback method.According to the Gronwall inequality,Laplace transform and Mittag-Leffler function,a new control scheme is explored for the whole closed-loop system.Under the developed control scheme,the state variables of the closed-loop system are controlled to stabilize them to zero.Finally,the numerical simulation results of the chaotic system with equilibrium and without equilibrium illustrate the effectiveness of the proposed control scheme.
基金supported in part by the National Natural Science Foundation of China under Grant U2013201in part by the Key R & D projects (Social Development) in Jiangsu Province of China under Grant BE2020704
文摘This paper investigates the path planning method of unmanned aerial vehicle(UAV)in threedimensional map.Firstly,in order to keep a safe distance between UAV and obstacles,the obstacle grid in the map is expanded.By using the data structure of octree,the octree map is constructed,and the search nodes is significantly reduced.Then,the lazy theta*algorithm,including neighbor node search,line-of-sight algorithm and heuristics weight adjustment is improved.In the process of node search,UAV constraint conditions are considered to ensure the planned path is actually flyable.The redundant nodes are reduced by the line-of-sight algorithm through judging whether visible between two nodes.Heuristic weight adjustment strategy is employed to control the precision and speed of search.Finally,the simulation results show that the improved lazy theta*algorithm is suitable for path planning of UAV in complex environment with multi-constraints.The effectiveness and flight ability of the algorithm are verified by comparing experiments and real flight.
基金supported by the National Natural Science Foundation of China(61174102)the Jiangsu Natural Science Foundation of China(SBK20130033)+1 种基金the NUAA Fundamental Research Funds(NS2013028)the Specialized Research Fund for the Doctoral Program of Higher Education(20133218110013)
文摘The robust bounded flight control scheme is developed for the uncertain longitudinal flight dynamics of the fighter with control input saturation invoking the backstepping technique. To enhance the disturbance rejection ability of the robust flight control for fighters, the sliding mode disturbance observer is designed to estimate the compounded disturbance including the unknown external disturbance and the effect of the control input saturation. Based on the backstepping technique and the compounded disturbance estimated output, the robust bounded flight control scheme is proposed for the fighter with the unknown external disturbance and the control input saturation. The closed-loop system stability under the developed robust bounded flight control scheme is rigorously proved using the Lyapunov method and the uniformly asymptotical convergences of all closed-loop signals are guaranteed. Finally, simulation results are presented to show the effectiveness of the proposed robust bounded flight control scheme for the uncertain longitudinal flight dynamics of the fighter.
基金supported in part by the National Natural ScienceFoundation of China (U2013201)the National Science Fund for Distinguished Young Scholars (61825302)the Postgraduate Research&Practice Innovation Program of Jiangsu Province (KYCX20_0208)。
文摘In this paper, a disturbance observer-based safe tracking control scheme is proposed for a medium-scale unmanned helicopter with rotor flapping dynamics in the presence of partial state constraints and unknown external disturbances. A safety protection algorithm is proposed to keep the constrained states within the given safe-set. A second-order disturbance observer technique is utilized to estimate the external disturbances. It is shown that the desired tracking performance of the controlled unmanned helicopter can be achieved with the application of the backstepping approach, dynamic surface control technique, and Lyapunov method. Finally, the availability of the proposed control scheme has been shown by simulation results.
文摘This paper proposes a backstepping technique and Multi-dimensional Taylor Polynomial Networks(MTPN)based adaptive attitude tracking control strategy for Near Space Vehicles(NSVs)subjected to input constraints and stochastic input noises.Firstly,considering the control input has stochastic noises,and the attitude motion dynamical model of the NSVs is actually modeled as the Multi-Input Multi-Output(MIMO)stochastic nonlinear system form.Furthermore,the MTPN is used to estimate the unknown system uncertainties,and an auxiliary system is designed to compensate the influence of the saturation control input.Then,by using backstepping method and the output of the auxiliary system,a MTPN-based robust adaptive attitude control approach is proposed for the NSVs with saturation input nonlinearity,stochastic input noises,and system uncertainties.Stochastic Lyapunov stability theory is utilized to analysis the stability in the sense of probability of the entire closed-loop system.Additionally,by selecting appropriate parameters,the tracking errors will converge to a small neighborhood with a tunable radius.Finally,the numerical simulation results of the NSVs attitude motion show the satisfactory flight control performance under the proposed tracking control strategy.
文摘实际空战的复杂性和不确定性及部分空战信息未知性,给无人机空战目标意图预测带来巨大挑战.针对非完备信息下无人机空战目标意图预测问题,本文提出了一种基于长短时记忆(long shortterm memory,LSTM)网络的非完备信息下空战目标意图预测模型.采用分层的方法建立空战目标意图预测特征集,并将空战信息编码成时序特征,将专家经验封装成标签,引入三次样条插值函数拟合以及平均值填充法来修补不完备数据,利用自适应矩估计(adaptive moment estimation,Adam)优化算法,加快目标意图预测模型训练速度,以便有效地防止局部最优的问题.最后通过仿真验证了所建立的无人机空战目标意图预测模型能有效预测无人机空战目标意图.
