基于生物启发的水下机器人路径跟踪控制

Bio-inspired path following control for underwater vehicles

针对常规反步控制方法在路径跟踪中出现的速度跳变与推进器驱动饱和等问题,将生物启发神经动力学模型应用到水下机器人路径跟踪控制中。利用生物启发神经动力学模型的渐变和有界输出等特性,设计基于生物启发的反步路径跟踪控制器,并同传统反步跟踪控制器进行对比分析。仿真结果表明:在较大的初始跟踪误差下,所设计的跟踪控制器可以有效克服水下机器人跟踪控制中的速度跳变,避免推进器的驱动饱和,满足水下机器人推进器的推力约束。

To solve the speed jump and propeller-driven saturation problems in the conventional backstepping method, the bio-inspired neuraldynamic model was applied to the path following control for underwater vehicles. With gradient and bounded-output characters of bio-inspired neuraldynamic model, the bio-inspired backstepping path following controller was designed and comparison study and analysis with conventional backstepping controller are conducted. Through the simulation results, in the large initial tracking error condition, the proposed tracking controller can deal with speed jump and avoid driving saturation to meet propeller thrust constraints.