水面无人艇模糊神经网络航向控制器设计

针对常规PID控制器在无人艇航向控制系统中表现出抗干扰能力弱，控制精度低等问题，本文提出了一种应用模糊神经网络算法的航向控制器设计方法.首先通过神经网络分类回归确定隶属度函数，然后经由模糊控制在线整定PID控制器KP、KI、KD三个参数，确保对无人艇航向的实时控制.仿真结果表明，该控制器满足航向控制所需的实时性，具有控制精度高和鲁棒性好的特点，并且提高了无人艇在复杂环境中的自适应能力.

Design of fuzzy neural network heading controller for unmanned surface vehicles

This paper presented a design method of heading controller based on fuzzy neural network algorithm to solve the problem that conventional PID controller has low anti-interference ability and low control precision. First，the membership function is determined by neural network classification regression， then three parameters of PID controller are adjusted online via Fuzzy control algorithm to ensure control the course of USV in real time. The simulation results show that this controller is capable to meets the need of heading control for real time， and it has the characteristics of high control precision and robustness， improves the adaptability of the USV in complex environment.