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基于自适应神经网络的低速AUV变质心控制 被引量:1

Variable Centroid Control for Low Speed AUV Based on Adaptive Neural Network
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摘要 为克服低速情况下舵效低的问题,研究了自治水下航行器(AUV)的变质心控制方法.通过控制布置在AUV三个惯性主轴上的三个可移动质量块的运动,改变系统的质心,进一步改变了AUV受到的流体动力,从而实现对于AUV的控制.基于Kane的多刚体动力学理论推导变质心控制AUV的4刚体9自由度动力学模型,为设计AUV变质心控制系统奠定了基础.之后基于多输入多输出(MIMO)不确定非线性系统理论,设计自适应神经网络控制系统,并用李亚普诺夫稳定理论对该系统进行了稳定性分析.仿真验证了控制方法的合理性. In order to overcome the low efficiency of rudder at low speed,a variable centroid control method for AUV (autonomous underwater vehicle) is investigated.The centroid of AUV system is changed by controlling the motion of three moving masses on three inertia axes of AUV,thus the hydrodynamic will be changed and then AUV can be controlled.The AUV dynamic model with four rigid bodies and nine degrees of freedom is derived based on the Kane's multiple rigid body systems dynamic theory,and the model lays the foundation for designing AUV variable centroid control system.Then the adaptive neural network control system is designed based on the uncertain MIMO(multiple input multiple output) nonlinear system theory,and the Lyapunov stability theory is used to analyze the stability of system.Simulation indicates the validity of the control method.
出处 《信息与控制》 CSCD 北大核心 2011年第5期619-626,共8页 Information and Control
基金 国家自然科学基金资助项目(60775022) 中国博士后科学基金资助项目(20100470119)
关键词 变质心 自治水下航行器 KANE方程 多输入多输出非线性系统 神经网络自适应控制 variable centroid autonomous underwater vehicle(AUV) Kane equation MIMO(multiple input multiple output) nonlinear system neural network adaptive control
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参考文献6

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