Robust Control Based on Adaptive Neural Network for the Process of Steady Formation of Continuous Contact Force in Unmanned Aerial Manipulator.

Qian Fang, Pengjun Mao, Lirui Shen, Jun Wang

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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0 citing papers in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Qian FangSchool of Mechanical and Electrical Engineering, Henan University of Science and Technology, Luoyang 471000, China.

Pengjun MaoSchool of Mechanical and Electrical Engineering, Henan University of Science and Technology, Luoyang 471000, China.ORCID 0000-0003-0852-1268

Lirui ShenSchool of Mechanical and Electrical Engineering, Henan University of Science and Technology, Luoyang 471000, China.ORCID 0000-0002-8307-7884

Jun WangSchool of Mechanical and Electrical Engineering, Henan University of Science and Technology, Luoyang 471000, China.

Funding

Major Program for Science and Technology of Henan 181100110100Major Program for Science and Technology of Luoyang 2101018A

6 · The paper itself

Abstract

Contact force control for Unmanned Aerial Manipulators (UAMs) is a challenging issue today. This paper designs a new method to stabilize the UAM system during the formation of contact force with the target. Firstly, the dynamic model of the contact process between the UAM and the target is derived. Then, a non-singular global fast terminal sliding mode controller (NGFTSMC) is proposed to guarantee that the contact process is completed within a finite time. Moreover, to compensate for system uncertainties and external disturbances, the equivalent part of the controller is estimated by an adaptive radial basis function neural network (RBFNN). Finally, the Lyapunov theory is applied to validate the global stability of the closed-loop system and derive the adaptive law for the neural network weight matrix online updating. Simulation and experimental results demonstrate that the proposed method can stably form a continuous contact force and reduce the chattering with good robustness.

Indexed as

CephapirinNeural Networks, ComputerComputer SimulationUncertaintyCephapirinadaptive neural networkcontact procedureforce controlrobust controllerunmanned aerial manipulator

Identifiers

PMID36679794

DOI10.3390/s23020989

PMCPMC9865819

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.