This paper investigates a switching control strategy for the altitude motion of a morphing aircraft with variable sweep wings based on Q-learning.The morphing process is regarded as a function of the system states and...This paper investigates a switching control strategy for the altitude motion of a morphing aircraft with variable sweep wings based on Q-learning.The morphing process is regarded as a function of the system states and a related altitude motion model is established.Then,the designed controller is divided into the outer part and inner part,where the outer part is devised by a combination of the back-stepping method and command filter technique so that the’explosion of complexity’problem is eliminated.Moreover,the integrator structure of the altitude motion model is exploited to simplify the back-stepping design,and disturbance observers inspired from the idea of extended state observer are devised to obtain estimations of the system disturbances.The control input switches from the outer part to the inner part when the altitude tracking error converges to a small value and linear approximation of the altitude motion model is applied.The inner part is generated by the Q-learning algorithm which learns the optimal command in the presence of unknown system matrices and disturbances.It is proved rigorously that all signals of the closed-loop system stay bounded by the developed control method and controller switching occurs only once.Finally,comparative simulations are conducted to validate improved control performance of the proposed scheme.展开更多
To synchronize the attitude of a spacecraft formation flying system, three novel autonomous control schemes are proposed to deal with the issue in this paper. The first one is an ideal autonomous attitude coordinated ...To synchronize the attitude of a spacecraft formation flying system, three novel autonomous control schemes are proposed to deal with the issue in this paper. The first one is an ideal autonomous attitude coordinated controller, which is applied to address the case with certain models and no disturbance. The second one is a robust adaptive attitude coordinated controller, which aims to tackle the case with external disturbances and model uncertainties. The last one is a filtered robust adaptive attitude coordinated controller, which is used to overcome the case with input con- straint, model uncertainties, and external disturbances. The above three controllers do not need any external tracking signal and only require angular velocity and relative orientation between a spacecraft and its neighbors. Besides, the relative information is represented in the body frame of each spacecraft. The controllers are proved to be able to result in asymptotical stability almost everywhere. Numerical simulation results show that the proposed three approaches are effective for attitude coordination in a spacecraft formation flying system.展开更多
The command and control（C2） is a decision-making process based on human cognition,which contains operational,physical,and human characteristics,so it takes on uncertainty and complexity.As a decision support approac...The command and control（C2） is a decision-making process based on human cognition,which contains operational,physical,and human characteristics,so it takes on uncertainty and complexity.As a decision support approach,Bayesian networks（BNs） provide a framework in which a decision is made by combining the experts＇ knowledge and the specific data.In addition,an expert system represented by human cognitive framework is adopted to express the real-time decision-making process of the decision maker.The combination of the Bayesian decision support and human cognitive framework in the C2 of a specific application field is modeled and executed by colored Petri nets（CPNs）,and the consequences of execution manifest such combination can perfectly present the decision-making process in C2.展开更多
基金supported by the National Natural Science Foundation of China(Nos.61873295,61833016)the Aeronautical Science Foundation of China(No.2016ZA51011).
文摘This paper investigates a switching control strategy for the altitude motion of a morphing aircraft with variable sweep wings based on Q-learning.The morphing process is regarded as a function of the system states and a related altitude motion model is established.Then,the designed controller is divided into the outer part and inner part,where the outer part is devised by a combination of the back-stepping method and command filter technique so that the’explosion of complexity’problem is eliminated.Moreover,the integrator structure of the altitude motion model is exploited to simplify the back-stepping design,and disturbance observers inspired from the idea of extended state observer are devised to obtain estimations of the system disturbances.The control input switches from the outer part to the inner part when the altitude tracking error converges to a small value and linear approximation of the altitude motion model is applied.The inner part is generated by the Q-learning algorithm which learns the optimal command in the presence of unknown system matrices and disturbances.It is proved rigorously that all signals of the closed-loop system stay bounded by the developed control method and controller switching occurs only once.Finally,comparative simulations are conducted to validate improved control performance of the proposed scheme.
基金co-supported by the National Natural Science Foundation of China (No. 61174037)the Innovation Found of Chinese Academy of Space Technology (No. CAST20120602)+1 种基金the Foundation for Creative Research Groups of the National Natural Science Foundation (No. 61021002)the National High-tech Research and Development Program of China (No. 2012AA120602)
文摘To synchronize the attitude of a spacecraft formation flying system, three novel autonomous control schemes are proposed to deal with the issue in this paper. The first one is an ideal autonomous attitude coordinated controller, which is applied to address the case with certain models and no disturbance. The second one is a robust adaptive attitude coordinated controller, which aims to tackle the case with external disturbances and model uncertainties. The last one is a filtered robust adaptive attitude coordinated controller, which is used to overcome the case with input con- straint, model uncertainties, and external disturbances. The above three controllers do not need any external tracking signal and only require angular velocity and relative orientation between a spacecraft and its neighbors. Besides, the relative information is represented in the body frame of each spacecraft. The controllers are proved to be able to result in asymptotical stability almost everywhere. Numerical simulation results show that the proposed three approaches are effective for attitude coordination in a spacecraft formation flying system.
基金supported by the National Natural Science Foundation of China (60874068)
文摘The command and control（C2） is a decision-making process based on human cognition,which contains operational,physical,and human characteristics,so it takes on uncertainty and complexity.As a decision support approach,Bayesian networks（BNs） provide a framework in which a decision is made by combining the experts＇ knowledge and the specific data.In addition,an expert system represented by human cognitive framework is adopted to express the real-time decision-making process of the decision maker.The combination of the Bayesian decision support and human cognitive framework in the C2 of a specific application field is modeled and executed by colored Petri nets（CPNs）,and the consequences of execution manifest such combination can perfectly present the decision-making process in C2.
