The trajectory tracking control problem is addressed for autonomous underwater vehicle(AUV) in marine environ?ment, with presence of the influence of the uncertain factors including ocean current disturbance, dynamic ...The trajectory tracking control problem is addressed for autonomous underwater vehicle(AUV) in marine environ?ment, with presence of the influence of the uncertain factors including ocean current disturbance, dynamic modeling uncertainty, and thrust model errors. To improve the trajectory tracking accuracy of AUV, an adaptive backstepping terminal sliding mode control based on recurrent neural networks(RNN) is proposed. Firstly, considering the inaccu?rate of thrust model of thruster, a Taylor’s polynomial is used to obtain the thrust model errors. And then, the dynamic modeling uncertainty and thrust model errors are combined into the system model uncertainty(SMU) of AUV; through the RNN, the SMU and ocean current disturbance are classified, approximated online. Finally, the weights of RNN and other control parameters are adjusted online based on the backstepping terminal sliding mode controller. In addition, a chattering?reduction method is proposed based on sigmoid function. In chattering?reduction method, the sigmoid function is used to realize the continuity of the sliding mode switching function, and the sliding mode switching gain is adjusted online based on the exponential form of the sliding mode function. Based on the Lyapu?nov theory and Barbalat’s lemma, it is theoretically proved that the AUV trajectory tracking error can quickly converge to zero in the finite time. This research proposes a trajectory tracking control method of AUV, which can e ectively achieve high?precision trajectory tracking control of AUV under the influence of the uncertain factors. The feasibility and e ectiveness of the proposed method is demonstrated with trajectory tracking simulations and pool?experi?ments of AUV.展开更多
We realize the function projective synchronization (FPS) between two discrete-time hyperchaotic systems, that is, the drive state vectors and the response state vectors can evolve in a proportional scaling function ma...We realize the function projective synchronization (FPS) between two discrete-time hyperchaotic systems, that is, the drive state vectors and the response state vectors can evolve in a proportional scaling function matrix. In this paper, a systematic scheme is explored to investigate the function projective synchronization of two identical discrete-time hyperchaotic systems using the backstepping method. Additionally, FPS of two different hyperchaotic systems is also realized. Numeric simulations are given to verify the effectiveness of our scheme.展开更多
In this paper,a new optimal adaptive backstepping control approach for nonlinear systems under deception attacks via reinforcement learning is presented in this paper.The existence of nonlinear terms in the studied sy...In this paper,a new optimal adaptive backstepping control approach for nonlinear systems under deception attacks via reinforcement learning is presented in this paper.The existence of nonlinear terms in the studied system makes it very difficult to design the optimal controller using traditional methods.To achieve optimal control,RL algorithm based on critic–actor architecture is considered for the nonlinear system.Due to the significant security risks of network transmission,the system is vulnerable to deception attacks,which can make all the system state unavailable.By using the attacked states to design coordinate transformation,the harm brought by unknown deception attacks has been overcome.The presented control strategy can ensure that all signals in the closed-loop system are semi-globally ultimately bounded.Finally,the simulation experiment is shown to prove the effectiveness of the strategy.展开更多
在某些特殊条件下,电力系统会受影响产生混沌振荡现象,影响电网的安全稳定运行。比如,电力系统在运行过程中产生过多的无功功率将会导致电压相角偏移,从而进一步引发电力系统混沌振荡现象。通过对电力系统相对电角度和相对角速度的调控...在某些特殊条件下,电力系统会受影响产生混沌振荡现象,影响电网的安全稳定运行。比如,电力系统在运行过程中产生过多的无功功率将会导致电压相角偏移,从而进一步引发电力系统混沌振荡现象。通过对电力系统相对电角度和相对角速度的调控和观测,可以实现电力系统稳定性的控制。文中首先对二阶电力系统模型(model of second order power system, MSOPS)进行混沌振荡的动力学分析,综合利用反步法和固定时间控制器等方法,设计了一种改进有限时间(finite-time, FT)的控制器,既实现了对电力系统混沌振荡的抑制又减轻了计算负担、提升系统收敛速度。最后采用MATLAB软件进行数值仿真表明:文中提出的控制策略能够快速抑制电力系统的混沌状态,验证了控制方法的鲁棒性和快速性。展开更多
基金Basic Research Program of Ministry of Industry and Information Technology of China(Grant No.B2420133003)National Natural Science Foundation of China(Grant Nos.51779060,51679054)
文摘The trajectory tracking control problem is addressed for autonomous underwater vehicle(AUV) in marine environ?ment, with presence of the influence of the uncertain factors including ocean current disturbance, dynamic modeling uncertainty, and thrust model errors. To improve the trajectory tracking accuracy of AUV, an adaptive backstepping terminal sliding mode control based on recurrent neural networks(RNN) is proposed. Firstly, considering the inaccu?rate of thrust model of thruster, a Taylor’s polynomial is used to obtain the thrust model errors. And then, the dynamic modeling uncertainty and thrust model errors are combined into the system model uncertainty(SMU) of AUV; through the RNN, the SMU and ocean current disturbance are classified, approximated online. Finally, the weights of RNN and other control parameters are adjusted online based on the backstepping terminal sliding mode controller. In addition, a chattering?reduction method is proposed based on sigmoid function. In chattering?reduction method, the sigmoid function is used to realize the continuity of the sliding mode switching function, and the sliding mode switching gain is adjusted online based on the exponential form of the sliding mode function. Based on the Lyapu?nov theory and Barbalat’s lemma, it is theoretically proved that the AUV trajectory tracking error can quickly converge to zero in the finite time. This research proposes a trajectory tracking control method of AUV, which can e ectively achieve high?precision trajectory tracking control of AUV under the influence of the uncertain factors. The feasibility and e ectiveness of the proposed method is demonstrated with trajectory tracking simulations and pool?experi?ments of AUV.
文摘We realize the function projective synchronization (FPS) between two discrete-time hyperchaotic systems, that is, the drive state vectors and the response state vectors can evolve in a proportional scaling function matrix. In this paper, a systematic scheme is explored to investigate the function projective synchronization of two identical discrete-time hyperchaotic systems using the backstepping method. Additionally, FPS of two different hyperchaotic systems is also realized. Numeric simulations are given to verify the effectiveness of our scheme.
基金supported in part by the National Key R&D Program of China under Grants 2021YFE0206100in part by the National Natural Science Foundation of China under Grant 62073321+2 种基金in part by National Defense Basic Scientific Research Program JCKY2019203C029in part by the Science and Technology Development Fund,Macao SAR under Grants FDCT-22-009-MISE,0060/2021/A2 and 0015/2020/AMJin part by the financial support from the National Defense Basic Scientific Research Project(JCKY2020130C025).
文摘In this paper,a new optimal adaptive backstepping control approach for nonlinear systems under deception attacks via reinforcement learning is presented in this paper.The existence of nonlinear terms in the studied system makes it very difficult to design the optimal controller using traditional methods.To achieve optimal control,RL algorithm based on critic–actor architecture is considered for the nonlinear system.Due to the significant security risks of network transmission,the system is vulnerable to deception attacks,which can make all the system state unavailable.By using the attacked states to design coordinate transformation,the harm brought by unknown deception attacks has been overcome.The presented control strategy can ensure that all signals in the closed-loop system are semi-globally ultimately bounded.Finally,the simulation experiment is shown to prove the effectiveness of the strategy.
文摘在某些特殊条件下,电力系统会受影响产生混沌振荡现象,影响电网的安全稳定运行。比如,电力系统在运行过程中产生过多的无功功率将会导致电压相角偏移,从而进一步引发电力系统混沌振荡现象。通过对电力系统相对电角度和相对角速度的调控和观测,可以实现电力系统稳定性的控制。文中首先对二阶电力系统模型(model of second order power system, MSOPS)进行混沌振荡的动力学分析,综合利用反步法和固定时间控制器等方法,设计了一种改进有限时间(finite-time, FT)的控制器,既实现了对电力系统混沌振荡的抑制又减轻了计算负担、提升系统收敛速度。最后采用MATLAB软件进行数值仿真表明:文中提出的控制策略能够快速抑制电力系统的混沌状态,验证了控制方法的鲁棒性和快速性。
