Design, Modeling and Dynamic Compensation PID Control of a Fully-Actuated Aerial Manipulation System
Le Ma, Dong Wang, Zixu Hao, Jie Liu, Jiasen Sun, Siyu Wang

TL;DR
This paper introduces a novel fully-actuated aerial manipulation system with a new mechanical design, accurate modeling, and a dynamic-compensation PID control method that enhances control performance and disturbance rejection.
Contribution
It presents a new mechanical structure, detailed modeling using Craig parameters and Newton-Euler equations, and a dynamic-compensation PID control approach for fully-actuated aerial manipulators.
Findings
The proposed control achieves full actuation with high accuracy.
Simulation results show improved disturbance rejection over traditional methods.
Experimental validation confirms the effectiveness of the dc-PID control.
Abstract
This paper addresses design, modeling and dynamic-compensation PID (dc-PID) control of a novel type of fully-actuated aerial manipulation (AM) system. Firstly, design of novel mechanical structure of the AM is presented. Secondly, kinematics and dynamics of AM are modeled using Craig parameters and recursion Newton-Euler equations respectively, which give rise to a more accurate dynamic relationship between aerial platform and manipulator. Then, the dynamic-compensation PID control is proposed to solve the problem of fully-actuated control of AM. Finally, uniform coupled matrix equations between driving forces/moments and rotor speeds are derived, which can support design and analysis of parameters and decoupling theoretically. It is taken into account practical problems including noise and perturbation, parameter uncertainty, and power limitation in simulations, and results from…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdaptive Control of Nonlinear Systems · Robotic Path Planning Algorithms · Teleoperation and Haptic Systems
