Development of an attitude control system of a heavy-lift hexacopter using Elman recurrent neural networks

Kusumoputro, Benyamin; Suprijono, Herwin; Heryanto, M. Ary; Suprapto, Bhakti Yudho

doi:10.1109/iconac.2016.7604889

Cited by 13 publications

(11 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The artificial neural network's direct inverse control (DIC-ANN) method itself had shown terrific achievement in controlling nonlinear dynamics aspect of UAV [19,23,24]. Considering the quadrotor as a highly nonlinear, strongly coupled, interacting in multivariable dynamics, and underactuated system [4], the DIC-ANN will be suitable for controlling such system.…”

Section: Direct Inverse Control: Artificial Neural Network For Contromentioning

confidence: 99%

“…Generally, the artificial neural network has been utilized for system identification and controller in wide areas of applications from the industrial nonlinear process to the vehicle control system. These included the thermal dynamic of pulsating heat pipe [49] and greenhouse temperature [50] to the autonomous vehicle control [51] and UAVs [19,23,24].…”

Section: The Direct Inverse Control Of the Ann-based Controllermentioning

confidence: 99%

“…Artificial neural network (ANN) is a parallel distributed processor consisting of simple neurons that enabled memorizing the knowledge of a system by mimicking its nonlinear model after training process [19]. In the control areas, the ANN-based control system arises due to the drawbacks of the nonlinear control systems like backstepping, sliding mode controller, and so forth.…”

Section: Introductionmentioning

confidence: 99%

“…The research of DIC-ANN in UAV controller [19,23,24] has published the advantages of the method for UAV application. However, to validate their improvement, the results still not be comparable with the conventional control method.…”

Section: Introductionmentioning

confidence: 99%

“…The inversion technique initiates the direct inverse control (DIC) method with the use of ANN. The ANN method has been applied for nonlinear systems from chemical reactor [21] to nuclear purposes [22], whereas, in the field of unmanned system's controller, the DIC-ANN becomes research topics in UAV, for example, hexacopter [19], helicopter [23], and quadrotor [24] to the AUV [8].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Neural Network Control System of UAV Altitude Dynamics and Its Comparison with the PID Control System

Muliadi

Kusumoputro

2018

Journal of Advanced Transportation

Self Cite

View full text Add to dashboard Cite

This article proposes a comparative method to assess the performance of artificial neural network's direct inverse control (DIC-ANN) with the PID control system. The comparison served as an analysis tool to assess the advantages of DIC-ANN over conventional control method for a UAV attitude controller. The development of ANN method for UAV control purposes arises due to the limitations of the conventional control method, which is the mathematical based model, involving complex expression, and most of them are difficult to be solved directly into analytic solution. Although the linearization simplified the solving process for such mathematical based model, omitting the nonlinear and the coupling terms is unsuitable for the dynamics of the multirotor vehicle. Thus, the DIC-ANN perform learning mechanism to overcome the limitation of PID tuning. Therefore, the proposed comparative method is developed to obtain conclusive results of DIC-ANN advantages over the linear method in UAV attitude control. Better achievement in the altitude dynamics was attained by the DIC-ANN compared to PID control method.

show abstract

Section: Direct Inverse Control: Artificial Neural Network For Contromentioning

confidence: 99%