The utilization of traffic information received from intelligent vehicle highway systems(IVHS) to plan velocity and split output power for multi-source vehicles is currently a research hotspot. However, it is an open ...The utilization of traffic information received from intelligent vehicle highway systems(IVHS) to plan velocity and split output power for multi-source vehicles is currently a research hotspot. However, it is an open issue to plan vehicle velocity and distribute output power between different supply units simultaneously due to the strongly coupling characteristic of the velocity planning and the power distribution. To address this issue, a flexible predictive power-split control strategy based on IVHS is proposed for electric vehicles(EVs) equipped with battery-supercapacitor system(BSS). Unlike hierarchical strategies to plan vehicle velocity and distribute output power separately, a monolayer model predictive control(MPC) method is employed to optimize them online at the same time. Firstly, a flexible velocity planning strategy is designed based on the signal phase and time(SPAT) information received from IVHS and then the Pontryagin’s minimum principle(PMP) is adopted to formulate the optimal control problem of the BSS. Then, the flexible velocity planning strategy and the optimal control problem of BSS are embedded into an MPC framework, which is online solved using the shooting method in a fashion of receding horizon. Simulation results verify that the proposed strategy achieves a superior performance compared with the hierarchical strategy in terms of transportation efficiency, battery capacity loss, energy consumption and computation time.展开更多
Heterogeneous wireless sensor networks(HWSNs)are vulnerable to malware propagation,because of their low configuration and weak defense mechanism.Therefore,an optimality system for HWSNs is developed to suppress malwar...Heterogeneous wireless sensor networks(HWSNs)are vulnerable to malware propagation,because of their low configuration and weak defense mechanism.Therefore,an optimality system for HWSNs is developed to suppress malware propagation in this paper.Firstly,a heterogeneous-susceptible-exposed-infectious-recovered-susceptible(HSEIRS)model is proposed to describe the state dynamics of heterogeneous sensor nodes(HSNs)in HWSNs.Secondly,the existence of an optimal control problem with installing antivirus on HSNs to minimize the sum of the cumulative infection probabilities of HWSNs at a low cost based on the HSEIRS model is proved,and then an optimal control strategy for the problem is derived by the optimal control theory.Thirdly,the optimal control strategy based on the HSEIRS model is transformed into corresponding Hamiltonian by the Pontryagin’s minimum principle,and the corresponding optimality system is derived.Finally,the effectiveness of the optimality system is validated by the experimental simulations,and the results show that the infectious HSNs will fall to an extremely low level at a low cost.展开更多
研究一种在空间3-D中求解弹道修正的最优控制问题的方法。根据Pontryagin极小值原理,将弹道修问题被转换成两点边值问题(Two-Point Boundary Value Problem,TPBVP),利用给定的边界条件,可将TPBVP可转换成针对主导向量初始值的参数优化问...研究一种在空间3-D中求解弹道修正的最优控制问题的方法。根据Pontryagin极小值原理,将弹道修问题被转换成两点边值问题(Two-Point Boundary Value Problem,TPBVP),利用给定的边界条件,可将TPBVP可转换成针对主导向量初始值的参数优化问题,并采用共轭算法求解主导向量初值。采用该控制方法进行了仿真实验以证明其可行性及准确性,仿真实验数据表明:所提出的算法鲁棒性强、精度高,可以满足战术需要。展开更多
The capture control of test mass by means of the electrostatic suspensions is crucial for drag-free spacecraft.The test mass must be released to the cage center of the inertial sensor accurately and quickly.This paper...The capture control of test mass by means of the electrostatic suspensions is crucial for drag-free spacecraft.The test mass must be released to the cage center of the inertial sensor accurately and quickly.This paper proposes a minimum-time capture control method for the test mass release phase of drag-free spacecraft.An analytical solution of optimal control is derived based on Pontryagin’s minimum principle and the linearized dynamics model of the test mass during the release phase.The parameters of the analytical solution are initially guessed with an approximate linear solution of the test mass dynamics model and are slightly modified by using differential correction.Compared with the exact numerical solution by the hp-adaptive pseudospectral method,the analytical solution is proved to be minimum-time.Numerical simulation shows that the proposed control method quickly captures the test mass to the cage center of the inertial sensor.The capture time to stabilization is only half that of the traditional controller.展开更多
Purpose–The purpose of this paper is to investigate time-optimal control problems for multiple unmanned aerial vehicle(UAV)systems to achieve predefined flying shape.Design/methodology/approach–Two time-optimal prot...Purpose–The purpose of this paper is to investigate time-optimal control problems for multiple unmanned aerial vehicle(UAV)systems to achieve predefined flying shape.Design/methodology/approach–Two time-optimal protocols are proposed for the situations with or without human control input,respectively.Then,Pontryagin’s minimum principle approach is applied to deal with the time-optimal control problems for UAV systems,where the cost function,the initial and terminal conditions are given in advance.Moreover,necessary conditions are derived to ensure that the given performance index is optimal.Findings–The effectiveness of the obtained time-optimal control protocols is verified by two contrastive numerical simulation examples.Consequently,the proposed protocolscan successfully achieve the prescribed flying shape.Originality/value–This paper proposes a solution to solve the time-optimal control problems for multiple UAV systems to achieve predefined flying shape.展开更多
基金supported by the National Natural Science Foundation of China (62173303)the Fundamental Research for the Zhejiang P rovincial Universities (RF-C2020003)。
文摘The utilization of traffic information received from intelligent vehicle highway systems(IVHS) to plan velocity and split output power for multi-source vehicles is currently a research hotspot. However, it is an open issue to plan vehicle velocity and distribute output power between different supply units simultaneously due to the strongly coupling characteristic of the velocity planning and the power distribution. To address this issue, a flexible predictive power-split control strategy based on IVHS is proposed for electric vehicles(EVs) equipped with battery-supercapacitor system(BSS). Unlike hierarchical strategies to plan vehicle velocity and distribute output power separately, a monolayer model predictive control(MPC) method is employed to optimize them online at the same time. Firstly, a flexible velocity planning strategy is designed based on the signal phase and time(SPAT) information received from IVHS and then the Pontryagin’s minimum principle(PMP) is adopted to formulate the optimal control problem of the BSS. Then, the flexible velocity planning strategy and the optimal control problem of BSS are embedded into an MPC framework, which is online solved using the shooting method in a fashion of receding horizon. Simulation results verify that the proposed strategy achieves a superior performance compared with the hierarchical strategy in terms of transportation efficiency, battery capacity loss, energy consumption and computation time.
基金National Natural Science Foundation of China(No.61772018)Zhejiang Provincial Natural Science Foundation of China(No.LZ22F020002)。
文摘Heterogeneous wireless sensor networks(HWSNs)are vulnerable to malware propagation,because of their low configuration and weak defense mechanism.Therefore,an optimality system for HWSNs is developed to suppress malware propagation in this paper.Firstly,a heterogeneous-susceptible-exposed-infectious-recovered-susceptible(HSEIRS)model is proposed to describe the state dynamics of heterogeneous sensor nodes(HSNs)in HWSNs.Secondly,the existence of an optimal control problem with installing antivirus on HSNs to minimize the sum of the cumulative infection probabilities of HWSNs at a low cost based on the HSEIRS model is proved,and then an optimal control strategy for the problem is derived by the optimal control theory.Thirdly,the optimal control strategy based on the HSEIRS model is transformed into corresponding Hamiltonian by the Pontryagin’s minimum principle,and the corresponding optimality system is derived.Finally,the effectiveness of the optimality system is validated by the experimental simulations,and the results show that the infectious HSNs will fall to an extremely low level at a low cost.
文摘研究一种在空间3-D中求解弹道修正的最优控制问题的方法。根据Pontryagin极小值原理,将弹道修问题被转换成两点边值问题(Two-Point Boundary Value Problem,TPBVP),利用给定的边界条件,可将TPBVP可转换成针对主导向量初始值的参数优化问题,并采用共轭算法求解主导向量初值。采用该控制方法进行了仿真实验以证明其可行性及准确性,仿真实验数据表明:所提出的算法鲁棒性强、精度高,可以满足战术需要。
基金supported by Guangdong Major Project of Basic and Applied Basic Research(grant no.2019B030302001)National Key Research and Development Program(2022YFC2204200)+1 种基金Beijing Nova Program(Z211100002121137)Beijing Natural Science Foundation(1222018).
文摘The capture control of test mass by means of the electrostatic suspensions is crucial for drag-free spacecraft.The test mass must be released to the cage center of the inertial sensor accurately and quickly.This paper proposes a minimum-time capture control method for the test mass release phase of drag-free spacecraft.An analytical solution of optimal control is derived based on Pontryagin’s minimum principle and the linearized dynamics model of the test mass during the release phase.The parameters of the analytical solution are initially guessed with an approximate linear solution of the test mass dynamics model and are slightly modified by using differential correction.Compared with the exact numerical solution by the hp-adaptive pseudospectral method,the analytical solution is proved to be minimum-time.Numerical simulation shows that the proposed control method quickly captures the test mass to the cage center of the inertial sensor.The capture time to stabilization is only half that of the traditional controller.
基金supported by the National Natural Science Foundation of China under Grant Nos 61602163 and 61471163the Science Fund for Distinguished Young Scholars of Hubei Province under Grant No.2017CFA034the Natural Science Foundation of Hubei Province under 2016CFC735.The Hubei Education Department Science and Technology Research Program for young talents under Grant No.Q20182503.
文摘Purpose–The purpose of this paper is to investigate time-optimal control problems for multiple unmanned aerial vehicle(UAV)systems to achieve predefined flying shape.Design/methodology/approach–Two time-optimal protocols are proposed for the situations with or without human control input,respectively.Then,Pontryagin’s minimum principle approach is applied to deal with the time-optimal control problems for UAV systems,where the cost function,the initial and terminal conditions are given in advance.Moreover,necessary conditions are derived to ensure that the given performance index is optimal.Findings–The effectiveness of the obtained time-optimal control protocols is verified by two contrastive numerical simulation examples.Consequently,the proposed protocolscan successfully achieve the prescribed flying shape.Originality/value–This paper proposes a solution to solve the time-optimal control problems for multiple UAV systems to achieve predefined flying shape.
