Efficient Cooperative Structured Control for a Multijoint Biomimetic Robotic Fish
Efficient Cooperative Structured Control for a Multijoint Biomimetic Robotic Fish
复制标题
多关节仿生机器鱼的高效协同结构控制
DOI：
10.1109/tmech.2020.3041506
复制
发表时间：
2021-10-01
影响因子：
6.4
通讯作者：
Yu, Junzhi
中科院分区：
文献类型：
--
作者：
Yan, Shuaizheng;Wu, Zhengxing;Yu, Junzhi
在这篇文章中，我们提出了一个有效的运动控制方法的二维跟踪任务的仿生四关节机器鱼。将此问题视为一个综合优化过程，提出了一种基于优化的协同结构控制框架，采用进化策略和深度确定性策略梯度相结合的方法对同一目标函数进行优化。为了进一步提高中心模式发生器模型参数优化的效果，提出了一种非一致优化方法。此外，为了更高的回报和更好的鲁棒性的控制器由深度强化学习，我们提出了一个线性加权控制器训练周期的方法。大量的仿真和实验结果验证了该方法在跟踪任务中的显着节能。与滑模控制、自抗扰控制和比例-积分-微分控制相比，协同结构控制分别节省了23.97%、22.13%和38.72%，为仿生机器鱼在复杂水环境中的长期智能工作提供了良好的条件。
In this article, we propose an efficient locomotion control method for a two-dimensional tracking task of a biomimetic four-joint robotic fish. Regarding this issue as a comprehensive optimization procedure, we propose an optimization-based cooperative structured control framework, in which the combination of evolutionary strategy and deep deterministic policy gradient is employed to optimize the same objective function. An inconsistent optimization method is presented to further enhance the effect of parameter optimization on central pattern generator model. Moreover, for the sake of a higher reward and better robustness of controllers governed by deep reinforcement learning, we propose a linear weighted controller trained with periodic method. Extensive simulation and experimental results verify the significant energy saving of the proposed method in tracking tasks. Noticeably, the cooperative structured control can save 23.97%, 22.13%, and 38.72% energy compared with sliding mode control, active disturbance rejection control, and proportional-integral-differential control in experiments, respectively, holding a great promise for the long-term intelligent work of the biomimetic robotic fish in complex aquatic environments.