Dynamic feedback control based on ANN compensation controller for AUV motions
Dynamic feedback control based on ANN compensation controller for AUV motions
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发表时间：
2011
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通讯作者：
Feng Xi-sheng
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作者：
Feng Xi-sheng
针对自主水下航行器(AUV)的运动问题，设计了一种神经网络补偿器与动态状态反馈控制相结合的控制算法。将AUV的数学模型分解为一个扩展的线性子系统和一个未知的非线性子系统。前一部分由动态反馈控制算法控制，动态反馈控制算法对反馈参数进行改进，反馈参数由时间、姿态和运动参数的函数描述。利用李亚普诺夫理论对跟踪误差收敛到零的理论进行了证明和发展，并在MatLab平台上进行了仿真，结果表明所提出的控制算法具有较强的抗干扰性，同时这些半物理环境的实验结果表明，所提出的控制算法比传统的PID控制算法具有更好的动态性能。
One algorithm of artificial neural network(ANN) compensator coupled with dynamical state feedback control was designed for motions of autonomous underwater vehicle(AUV).The math model of AUV was decomposed to one extended linear subsystem and an unknown nonlinear subsystem.The fore part was controlled by dynamic state feedback control algorithm which was improved on feedback parameters described by some functions of time,poses,and surge speed as well as the last one being controlled by ANN whose parameters are online adjustment.Theories are proved and developed by Lyapunov theory which denoted that the tracking error can be converged to zero.Some simulation results with Matlab platform show that the advised control algorithm holds the capability of anti-disturbance.Meanwhile,these semi-physical environment experiences make it clear that the advised control algorithm can have better dynamic performance than PID control algorithm.