Speed trajectory tracking of a robotic fish based on iterative learning control approach
Xuefang Li, Qinyuan Ren, Jian‐Xin Xu
- 发表年份
- 2015
- 引用次数
- 2
摘要
In this paper, a novel work is presented, where iterative learning control (ILC) approach is applied to a precise speed control approach for a two-link robotic fish. First, by virtue of the Lagrangian mechanics method, we establish a mathematical model for the two-link carangiform robotic fish, which is highly nonlinear and non-affine in control input. According to the structure of the constructed dynamical model, a P-type iterative learning control (ILC) algorithm is proposed for speed tracking tasks of the robotic fish. The convergence analysis of the proposed controller is derived based on composite energy function (CEF). Moreover, its efficiency is not only illustrated by simulations, but also verified through experimental results. It is shown that ILC is an effective control approach for the motion control of robotic fish because of its model-free property and the simplicity of the algorithm.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991