多船舶的神经网络自适应同步控制

Neural Network Adaptive Synchronization Control of Multiple Vessels

为了实现多艘船舶的同步运动,提出了多艘船的自适应同步控制策略。由于船舶模型参数不确定,采用了径向基神经网络来逼近不确定项,建立船舶的数学模型;其次,利用了数学图论来描述船舶之间的信息交流;接着为每艘船预先设定期望路径,并且将船舶的同步误差引入到控制器,控制船舶的运动使其不但沿各自期望路径运动,而且与多艘船舶保持同步;利用李雅普诺夫稳定性理论,证明了所设计的自适应同步控制器的稳定性;通过对三艘船舶的仿真表明,所提出神经网络自适应同步控制可以很好地解决多艘船同步控制问题。

In order to implement the synchronization of multiple vessels, we put forward a neural network adaptive synchronization movement strategy. Firstly, based on the uncertainty of vessels in mode designing, a radial basis function network is used to approach the uncertainty, so the mode of the vessel is established. Secondly, the mathe-matical graph is introduced to describe the communication of vessels. Then, desired path for each vessel is designed. Meanwhile, a synchronization error introduced into controller to control each vessel to follow desired path as well as achieve synchronization movement. Thirdly, the stability of the adaptive synchronization controller is proved based on the Lyapunov theory. Finally, simulations with three vessels indicate the proposed neural network adaptive synchronization strategy can perfectly resolve the synchronization movement methodology.