This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater ve...This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater vehicle(AUV).The number of controllers is increased to realize AUV motion decoupling.At the same time, in order to avoid the oversize of the algorithm, combined with the controlled content, a simplified Q-learning algorithm is constructed to realize the parameter adaptation of the LADRC controller.Finally, through the simulation experiment of the controller with fixed parameters and the controller based on the Q-learning algorithm, the rationality of the simplified algorithm, the effectiveness of parameter adaptation, and the unique advantages of the LADRC controller are verified.展开更多
A new general robust fuzzy approach was presented to control the position and the attitude of unmanned flying vehicles(UFVs). Control of these vehicles was challenging due to their nonlinear underactuated behaviors. T...A new general robust fuzzy approach was presented to control the position and the attitude of unmanned flying vehicles(UFVs). Control of these vehicles was challenging due to their nonlinear underactuated behaviors. The proposed control system combined great advantages of generalized indirect adaptive sliding mode control(IASMC) and fuzzy control for the UFVs. An on-line adaptive tuning algorithm based on Lyapunov function and Barbalat lemma was designed, thus the stability of the system can be guaranteed. The chattering phenomenon in the sliding mode control was reduced and the steady error was also alleviated. The numerical results, for an underactuated quadcopter and a high speed underwater vehicle as case studies, indicate that the presented adaptive design of fuzzy sliding mode controller performs robustly in the presence of sensor noise and external disturbances. In addition, online unknown parameter estimation of the UFVs, such as ground effect and planing force especially in the cases with the Gaussian sensor noise with zero mean and standard deviation of 0.5 m and 0.1 rad and external disturbances with amplitude of 0.1 m/s2 and frequency of 0.2 Hz, is one of the advantages of this method. These estimated parameters are then used in the controller to improve the trajectory tracking performance.展开更多
For the multicopter with more than four rotors,the rotor fault information is unobservable,which limits the applica-tion of active fault-tolerant on multicopters.This paper applies an existing fault-tolerant control m...For the multicopter with more than four rotors,the rotor fault information is unobservable,which limits the applica-tion of active fault-tolerant on multicopters.This paper applies an existing fault-tolerant control method for quadcopter to multi-copter with more than four rotors.Without relying on rotor fault information,this method is able to stabilize the multicopter with multiple rotor failures,which is validated on the hexacopter and octocopter using the hardware-in-the-loop simulations.Addi-tionally,the hardware-in-the-loop simulations demonstrate that a more significant tilt angle in flight will inhibit the maximum tolera-ble number of rotor failures of a multicopter.The more signifi-cant aerodynamic drag moment will make it difficult for the mul-ticopter to regain altitude control after rotor failure.展开更多
This paper introduces a fault-tolerant control(FTC)design for a faulty fixed-wing unmanned aerial vehicle(UAV).To constrain tracking errors against actuator faults,error constraint inequalities are first transformed t...This paper introduces a fault-tolerant control(FTC)design for a faulty fixed-wing unmanned aerial vehicle(UAV).To constrain tracking errors against actuator faults,error constraint inequalities are first transformed to a new set of variables based on prescribed performance functions.Then,the commonly used and powerful proportional-integral-derivative(PID)control concept is employed to filter the transformed error variables.To handle the fault-induced nonlinear terms,a composite learning algorithm consisting of neural network and disturbance observer is incorporated for increasing flight safety.It is shown by Lyapunov stability analysis that the tracking errors are strictly constrained within the specified error bounds.Experimental results are presented to verify the feasibility of the developed FTC scheme.展开更多
针对水下无人航行器(underwater unmanned vehicle,UUV)主动声呐系统对信号处理实时性、能效比及集成度的需求,采用模块化设计以及软硬件协同设计思想,提出一种基于异构多处理器片上系统(multi-processor system on chip,MPSoC)的主动...针对水下无人航行器(underwater unmanned vehicle,UUV)主动声呐系统对信号处理实时性、能效比及集成度的需求,采用模块化设计以及软硬件协同设计思想,提出一种基于异构多处理器片上系统(multi-processor system on chip,MPSoC)的主动声呐实时信号处理算法的加速方案。首先研究适合边缘端部署的声呐信号处理算法;然后设计基于MPSoC的加速计算结构,将数字下变频、逆/快速傅里叶变换、波束形成等具有高计算复杂性的处理步骤移植到可编程逻辑端,实现显著加速;最后将目标检测等复杂度较低的步骤部署在处理器系统端,实现更高的灵活性。仿真及湖上试验结果表明,提出的方案可在数据更新周期的41%时间内完成1帧回波数据的实时处理,并可在复杂水下环境下实时有效探测运动目标。该方案在水下UUV主动声呐探测领域具有广阔的应用前景。展开更多
基金supported by the National Natural Science Foundation of China (6197317561973172)Tianjin Natural Science Foundation (19JCZDJC32800)。
文摘This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater vehicle(AUV).The number of controllers is increased to realize AUV motion decoupling.At the same time, in order to avoid the oversize of the algorithm, combined with the controlled content, a simplified Q-learning algorithm is constructed to realize the parameter adaptation of the LADRC controller.Finally, through the simulation experiment of the controller with fixed parameters and the controller based on the Q-learning algorithm, the rationality of the simplified algorithm, the effectiveness of parameter adaptation, and the unique advantages of the LADRC controller are verified.
文摘A new general robust fuzzy approach was presented to control the position and the attitude of unmanned flying vehicles(UFVs). Control of these vehicles was challenging due to their nonlinear underactuated behaviors. The proposed control system combined great advantages of generalized indirect adaptive sliding mode control(IASMC) and fuzzy control for the UFVs. An on-line adaptive tuning algorithm based on Lyapunov function and Barbalat lemma was designed, thus the stability of the system can be guaranteed. The chattering phenomenon in the sliding mode control was reduced and the steady error was also alleviated. The numerical results, for an underactuated quadcopter and a high speed underwater vehicle as case studies, indicate that the presented adaptive design of fuzzy sliding mode controller performs robustly in the presence of sensor noise and external disturbances. In addition, online unknown parameter estimation of the UFVs, such as ground effect and planing force especially in the cases with the Gaussian sensor noise with zero mean and standard deviation of 0.5 m and 0.1 rad and external disturbances with amplitude of 0.1 m/s2 and frequency of 0.2 Hz, is one of the advantages of this method. These estimated parameters are then used in the controller to improve the trajectory tracking performance.
基金supported by the National Natural Science Foundation of China(61973015).
文摘For the multicopter with more than four rotors,the rotor fault information is unobservable,which limits the applica-tion of active fault-tolerant on multicopters.This paper applies an existing fault-tolerant control method for quadcopter to multi-copter with more than four rotors.Without relying on rotor fault information,this method is able to stabilize the multicopter with multiple rotor failures,which is validated on the hexacopter and octocopter using the hardware-in-the-loop simulations.Addi-tionally,the hardware-in-the-loop simulations demonstrate that a more significant tilt angle in flight will inhibit the maximum tolera-ble number of rotor failures of a multicopter.The more signifi-cant aerodynamic drag moment will make it difficult for the mul-ticopter to regain altitude control after rotor failure.
基金This work was supported by the National Natural Science Foundation of China(62003162,61833013,62020106003)the Natural Science Foundation of Jiangsu Province of China(BK20200416)+3 种基金the China Postdoctoral Science Foundation(2020TQ0151,2020M681590)the State Key Laboratory of Synthetical Automation for Process Industries,Northeastern University(2019-KF-23-05)the 111 Project(B20007)the Natural Sciences and Engineering Research Council of Canada.
文摘This paper introduces a fault-tolerant control(FTC)design for a faulty fixed-wing unmanned aerial vehicle(UAV).To constrain tracking errors against actuator faults,error constraint inequalities are first transformed to a new set of variables based on prescribed performance functions.Then,the commonly used and powerful proportional-integral-derivative(PID)control concept is employed to filter the transformed error variables.To handle the fault-induced nonlinear terms,a composite learning algorithm consisting of neural network and disturbance observer is incorporated for increasing flight safety.It is shown by Lyapunov stability analysis that the tracking errors are strictly constrained within the specified error bounds.Experimental results are presented to verify the feasibility of the developed FTC scheme.
文摘针对水下无人航行器(underwater unmanned vehicle,UUV)主动声呐系统对信号处理实时性、能效比及集成度的需求,采用模块化设计以及软硬件协同设计思想,提出一种基于异构多处理器片上系统(multi-processor system on chip,MPSoC)的主动声呐实时信号处理算法的加速方案。首先研究适合边缘端部署的声呐信号处理算法;然后设计基于MPSoC的加速计算结构,将数字下变频、逆/快速傅里叶变换、波束形成等具有高计算复杂性的处理步骤移植到可编程逻辑端,实现显著加速;最后将目标检测等复杂度较低的步骤部署在处理器系统端,实现更高的灵活性。仿真及湖上试验结果表明,提出的方案可在数据更新周期的41%时间内完成1帧回波数据的实时处理,并可在复杂水下环境下实时有效探测运动目标。该方案在水下UUV主动声呐探测领域具有广阔的应用前景。
