The problem of passive detection discussed in this paper involves searching and locating an aerial emitter by dualaircraft using passive radars. In order to improve the detection probability and accuracy, a fuzzy Q le...The problem of passive detection discussed in this paper involves searching and locating an aerial emitter by dualaircraft using passive radars. In order to improve the detection probability and accuracy, a fuzzy Q learning algorithrn for dual-aircraft flight path planning is proposed. The passive detection task model of the dual-aircraft is set up based on the partition of the target active radar＇s radiation area. The problem is formulated as a Markov decision process （MDP） by using the fuzzy theory to make a generalization of the state space and defining the transition functions, action space and reward function properly. Details of the path planning algorithm are presented. Simulation results indicate that the algorithm can provide adaptive strategies for dual-aircraft to control their flight paths to detect a non-maneuvering or maneu- vering target.展开更多
针对矢量推力双旋翼无人机姿态控制过程中存在强耦合、模型不精确的问题,提出了一种改进型的线性自抗扰姿态控制(linear active disturbance rejection controller,LADRC)方法。该方法利用改进线性扩张状态观测器(linear extended state...针对矢量推力双旋翼无人机姿态控制过程中存在强耦合、模型不精确的问题,提出了一种改进型的线性自抗扰姿态控制(linear active disturbance rejection controller,LADRC)方法。该方法利用改进线性扩张状态观测器(linear extended state observer,LESO)提高对总扰动的实时观测精度,根据姿态角的误差及其变化率引入模糊控制思想对线性状态误差反馈控制律进行在线参数整定,最后以矢量推力双旋翼飞行器为研究对象,对比PID和常规LADRC对外界扰动的抗扰效果,仿真试验验证了该方法能够较好估计补偿系统的总扰动,具有更好的抗扰性能和收敛速度。展开更多
基金supported by the National Natural Science Foundation of China(60874040)
文摘The problem of passive detection discussed in this paper involves searching and locating an aerial emitter by dualaircraft using passive radars. In order to improve the detection probability and accuracy, a fuzzy Q learning algorithrn for dual-aircraft flight path planning is proposed. The passive detection task model of the dual-aircraft is set up based on the partition of the target active radar＇s radiation area. The problem is formulated as a Markov decision process （MDP） by using the fuzzy theory to make a generalization of the state space and defining the transition functions, action space and reward function properly. Details of the path planning algorithm are presented. Simulation results indicate that the algorithm can provide adaptive strategies for dual-aircraft to control their flight paths to detect a non-maneuvering or maneu- vering target.
文摘针对矢量推力双旋翼无人机姿态控制过程中存在强耦合、模型不精确的问题,提出了一种改进型的线性自抗扰姿态控制(linear active disturbance rejection controller,LADRC)方法。该方法利用改进线性扩张状态观测器(linear extended state observer,LESO)提高对总扰动的实时观测精度,根据姿态角的误差及其变化率引入模糊控制思想对线性状态误差反馈控制律进行在线参数整定,最后以矢量推力双旋翼飞行器为研究对象,对比PID和常规LADRC对外界扰动的抗扰效果,仿真试验验证了该方法能够较好估计补偿系统的总扰动,具有更好的抗扰性能和收敛速度。
