基于稳态自适应技术的水下机器人系统在线辨识

针对水下机器人运动和作业过程中的有效载荷变化使得机器人动态特性也相应地发生变化的特点,以开架式无缆水下机器人为研究对象,在对其动力学模型进行简化的基础上,提出了一种基于稳态自适应技术的在线参数辨识方法,进行了与基于最小二乘法的离线参数辨识的对比实验以及水下机器人特性发生变化时的在线辨识实验,水池实验结果验证了基于稳态自适应技术的参数在线辨识方法对开架式水下机器人进行系统辨识的有效性和可行性.

Online Identification of Autonomous Underwater Vehicle Based on Stable Adaptive Technique

Considering the changing of the dynamical model parameters for the autonomous underwater vehicle when it worked in underwater environments with variable payload, based on the simplification of the dynamical model, a stable adaptive technique based online parameters identification for the dynamical model was proposed for an open-frame autonomous underwater vehicle. Experiments with stable adaptive dynamical model parameters online identification and conventional least-squares dynamical model parameters identification were performed, and experiment results show that the stable adaptive technique based online parameters identification dynamical model is more valuable than the conventional least-squares dynamical model.