1. 厦门理工学院 机构 机械与汽车工程学院,福建,厦门,361024
2. 福建理工大学 智慧海洋与工程研究院,福州,350118
3. 厦门大学 航空航天学院,福建,厦门,361005
[ "胡书恒,硕士研究生," ]
[ "高秀晶,教授,博士," ]
纸质出版:2026
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胡书恒, 高秀晶, 江杰洪, 等. 单节点驱动机器鱼动力学建模与分析[J]. 机械科学与技术, 2026,45(3):453-461.
胡书恒, 高秀晶, 江杰洪, et al. Dynamics Modeling and Analysis of A Single-node Driven Robotic Fish[J]. Mechanical Science and Technology for Aerospace Engineering, 2026, 45(3): 453-461.
胡书恒, 高秀晶, 江杰洪, 等. 单节点驱动机器鱼动力学建模与分析[J]. 机械科学与技术, 2026,45(3):453-461. DOI: 10.13433/j.cnki.1003-8728.20240051.
胡书恒, 高秀晶, 江杰洪, et al. Dynamics Modeling and Analysis of A Single-node Driven Robotic Fish[J]. Mechanical Science and Technology for Aerospace Engineering, 2026, 45(3): 453-461. DOI: 10.13433/j.cnki.1003-8728.20240051.
针对机器鱼自主游动过程中复杂的水动力建模问题,设计了一款单节点驱动的机器鱼,并应用大振幅细长体理论和刚体动力学建立了可用于控制的机器鱼动力学模型。为降低求解机器鱼模型中阻力系数、升力系数和阻力矩系数的实验成本,通过超带宽定位实验平台,将机器鱼的尾部关节摆动规律作为模型的控制输入进行实验,拟合实验数据得到这些关键的模型参数,并通过对数值仿真结果与物理模型实验结果进行对比,验证了模型的准确性。为进一步验证所构建模型在实际应用的控制能力,基于PID控制器进行了目标跟踪控制。仿真结果表明:模型在速度、角速度和轨迹方面都具有良好的预测效果,并且通过尾部关节摆动频率和幅值能够合理的改变机器鱼的游动方式,使机器鱼运动得到很好的控制。
To address the complex hydrodynamic modeling challenges during the autonomous locomotion of robotic fish
we devised a robotic fish with a single-joint actuationand grounded in the theory of the large amplitude elongated body theory (LEABT) and rigid body dynamics. In order to reduce the experimental costs associated with determining the resistance coefficients
lift coefficients
and resistance moment coefficients within the robotic fish model
an experimental approach was employed using a ultra-wide band motion tracking platform. The tail joint motion patterns of the robotic fish were used as control inputs
and these crucial model parameters were fitted from the experimental data. To validate the model′s accuracy
a comparison was made between numerical simulation results and outcomes from physical model experiments. Furthermore
to assess the control capabilities of the constructed model in practical applications
we implemented target tracking control employing a PID controller. Simulation results indicate that the model demonstrates excellent predictive performance in terms of speed
angular velocity
and trajectory. Additionally
by adjusting the frequency and amplitude of tail joint oscillations
effective control over the robotic fish′s locomotion can be achieved.
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