观察型水下机器人预测控制器优化设计研究

观察型水下机器人在水下运动时受暗流、波浪影响严重、造成操控困难、系统稳定性差等问题。常规的运动控制算法存在动态响应差、自适应能力不足的缺点,难以有效抑制水流干扰。为提高系统的稳定性,提出了一种水下机器人艏向及垂向控制的预测控制优化算法。首先对观察型水下机器人进行了水中运动特性分析,从而建立观察型水下机器人系统的运动学和动力学模型,再使用FLUENT软件对水下机器人参数进行数值模拟辨识,最后设计了在初始阶段经过增量式PID算法优化的广义预测控制器。经过仿真与实验结果验证,相比于传统的广义预测控制器,提出的优化广义预测控制器提高了系统稳定性,减小了震荡,缩短了响应时间,满足观察型机器人水下稳定运行的要求。

Research on Optimization Design of Predictive Controller for Observational Underwater Vehicle

Observing underwater robots are subject to problems such as undercurrent,severe wave impact,difficulty in handling,and poor system stability during underwater movement.Conventional motion control algorithms have the disadvantages of poor dynamic response and insufficient adaptive ability,and it is difficult to effectively suppress water flow interference.In order to improve the stability of the system,this paper proposes a predictive control optimization algorithm for the heading and vertical control of underwater robots.Firstly,the underwater motion characteristics of the observation type underwater robot are analysed,and the kinematics and dynamics model of the observation type underwater robot system is established.Then the FLUENT software is used to numerically simulate the underwater robot parameters,and finally the initial stage is established.Generalized predictive controller optimized by incremental PID algorithm.The simulation and experimental results verify that,compared with the traditional generalized predictive controller,the optimized generalized predictive controller proposed in this paper improves the stability of the system,reduces the oscillation,shortens the response time,and satisfies the underwater stability of the underwater observation robot.Operational requirements.