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首页> 外文期刊>IAENG Internaitonal journal of computer science >Enhanced Fireworks Algorithm-Auto Disturbance Rejection Control Algorithm for Robot Fish Path Tracking
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Enhanced Fireworks Algorithm-Auto Disturbance Rejection Control Algorithm for Robot Fish Path Tracking

机译:增强型烟花算法 - 用于机器人鱼路径跟踪的自动干扰抑制控制算法

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摘要

The robot fish is affected by many unknown internal and external interference factors when it performs path tracking in unknown waters. It was proposed that a path tracking method based on the EFWA-ADRC (enhanced fireworks algorithmauto disturbance rejection control) to obtain high-quality tracking effect. ADRC has strong adaptability and robustness. It is an effective method to solve the control problems of nonlinearity, uncertainty, strong interference, strong coupling and large time lag. For the optimization of parameters in ADRC, the enhanced fireworks algorithm (EFWA) is used for online adjustment. It is to improve the anti-interference of the robot fish in the path tracking process. The multi-joint bionic robot fish was taken as the research object in the paper. It was established a path tracking error model in the Serret-Frenet coordinate system combining the mathematical model of robotic fish. It was focused on the forward speed and steering speed control rate. It was constructed that the EFWA-ADRC based path tracking system. Finally, the simulation and experimental results show that the control method based on EFWAADRC and conventional ADRC makes the robotic fish track the given path at 2:8s and 3:3s respectively, and the tracking error is kept within plus or minus 0:09m and 0:1m respectively. The new control method tracking steady-state error was reduces by 10% compared with the conventional ADRC. It was proved that the proposed EFWA-ADRC controller has better control effect on the controlled system, which is subject to strong interference.
机译:当它在未知水域执行路径跟踪时,机器人鱼受许多未知的内部和外部干扰因素的影响。提出了一种基于EFWA-ADRC(增强型烟花算法扰乱抑制控制)的路径跟踪方法,以获得高质量的跟踪效果。 ADRC具有强大的适应性和鲁棒性。这是解决非线性,不确定性,强烈干扰,强耦合和大时间滞后的控制问题的有效方法。为了优化ADRC中的参数,增强型烟花算法(EFWA)用于在线调整。它是改善路径跟踪过程中机器人鱼的抗干扰。多关节仿生机器人鱼作为论文中的研究对象。结合机器人鱼数学模型的Serret-Frenet坐标系中建立了路径跟踪误差模型。它专注于前进速度和转向速度控制率。它构建了基于EFWA-ADRC的路径跟踪系统。最后,模拟和实验结果表明,基于EFWAADRC和常规ADRC的控制方法使机器人捕获给定的路径分别为2:8s和3:3s,并且跟踪误差保持在加号或09m内和0:1m分别。与传统ADRC相比,新的控制方法跟踪稳态误差减少了10%。事实证明,建议的EFWA-ADRC控制器对受控系统具有更好的控制效果,受到强烈干扰的影响。

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