Speed trajectory tracking of a robotic fish based on iterative learning control approach

An Iterative Learning Control Approach to Multi-Agent Formations

Volume 3: Multiagent Network Systems; Natural Gas and Heat Exchangers; Path Planning and Motion Control; Powertrain Systems; Rehab Robotics; Robot Manipulators; Rollover Prevention (AVS); Sensors and Actuators; Time Delay Systems; Tracking Control Systems; Uncertain Systems and Robustness; Unmanned, Ground and Surface Robotics; Vehicle Dynamics Control; Vibration and Control of Smart Structures/Mech Systems; Vibration Issues in Mechanical Systems ◽

10.1115/dscc2015-9872 ◽

2015 ◽

Author(s):

Michael Quann ◽

Kira Barton

Keyword(s):

Trajectory Tracking ◽

Iterative Learning Control ◽

Learning Control ◽

Iterative Learning ◽

Stability And Convergence ◽

Individual Agent ◽

Convergence Conditions ◽

Control Approach ◽

Formation Tracking ◽

Multi Agent

This paper presents an iterative learning control (ILC) based method for trading off both individual and formation tracking for multiple agents with heterogeneous dynamics. The proposed framework provides precise trajectory tracking for systems involving repetitive, cooperative motion. The frequency domain based controller has the capability of being able to shift weighting between the desire for precise formations amongst the agents and precise trajectory tracking for each individual agent. Stability and convergence conditions are shown and the proposed controller is validated through simulations.

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An adaptive iterative learning control approach based on disturbance estimation for manipulator system

International Journal of Advanced Robotic Systems ◽

10.1177/1729881419852197 ◽

2019 ◽

Vol 16 (3) ◽

pp. 172988141985219

Author(s):

Keping Liu ◽

Yuanyuan Chai ◽

Zhongbo Sun ◽

Yan Li

Keyword(s):

Trajectory Tracking ◽

Iterative Learning Control ◽

Control Method ◽

Learning Control ◽

Iterative Learning ◽

Uncertain Parameters ◽

External Disturbances ◽

Adaptive Iterative Learning Control ◽

Control Approach ◽

Disturbance Estimation

An adaptive iterative learning control approach based on disturbance estimation has been developed for trajectory tracking of manipulators with uncertain parameters and external disturbances. The external disturbances are estimated by the feedback iterative learning method, whereas the uncertain parameters are compensated by adaptive control. This approach which is based on the disturbance estimation technique provides a rapid convergence of trajectory tracking errors. According to the Lyapunov theory, the sufficient condition of the asymptotic stability has been developed for the 2-degrees of freedom (DOFs) manipulator system. The numerical results show that the adaptive iterative learning control approach based on disturbance estimation is feasible and effective for the 2-DOFs manipulator. A comparison of the adaptive iterative learning control method and the iterative learning control method is completed, which shows that the adaptive iterative learning control method performs a faster convergence of the disturbance to the steady state.

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