In:
International Journal of Electrical and Computer Engineering (IJECE), Institute of Advanced Engineering and Science, Vol. 12, No. 4 ( 2022-08-01), p. 3607-
Abstract:
〈 span 〉 When the controlled system is subject to parameter variations and external disturbances, a fixed-parameter proportional integral derivative (PID) controller cannot ensure its stabilization. In this case, its control requires online parameter adjustment. Specifically, as the quadrotor is a multi-input multi-output, nonlinear, and underactuated system, robust control is necessary to ensure efficient trajectory tracking flights. In this paper, an adaptive proportional integral derivative (APID) controller is proposed to control the quadrotor systems. This APID-based control strategy uses a two hidden layer deep feedforward network (DFN), where the one-step secant algorithm is chosen for initializing the DFN parameters. All the design steps of the proposed adaptive controller are described. The multidimensional particle swarm optimization (PSO) algorithm is used for tuning the DFN parameters. Then, using two simulation efficiency tests, a comparison between the proposed PSO-based APID-DFN, the (non-optimized) APID-DFN, the feedforward network APID, and the fixed-parameter PID controllers proves much efficiency of the proposed adaptive controller. The results illustrate that the proposed PSO-based APID-DFN controller can ensure good quadrotor system stabilization and achieve minimum overshoot and faster convergence speed for all quadrotor motions. Thus, the proposed control strategy could be considered an additional intelligent method-based adaptive control for unmanned aerial vehicles. 〈 /span 〉
Type of Medium:
Online Resource
ISSN:
2722-2578
,
2088-8708
DOI:
10.11591/ijece.v12i4
DOI:
10.11591/ijece.v12i4.pp3607-3619
Language:
Unknown
Publisher:
Institute of Advanced Engineering and Science
Publication Date:
2022
detail.hit.zdb_id:
2667127-X
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