Adaptive Backstepping control of wind turbine two mass model

Gaidi, Abderrahmane; Lehouche, Hocine; Belkacemi, S.; Tahraoui, Souad; Loucif, Mourad; Guenounou, Ouahib

doi:10.1109/icosc.2017.7958648

Cited by 10 publications

(6 citation statements)

References 15 publications

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“…Adaptive systems can be distinguished as a third group. In general, two types of adaptive control are mentioned in the literature [27][28][29][30][31][32][33][34][35][36]. The first one is called indirect adaptive control.…”

Section: Introductionmentioning

confidence: 99%

“…The second approach is called direct adaptive control, in which the parameters of the controller are changed directly, due to the changes of the tracking error (specified as output between the desired trajectory and real output of the plant) [28][29][30][31][32][33][34][35][36][37][38]. For linear systems the suitable solution could be a classical PI controller.…”

Section: Introductionmentioning

confidence: 99%

“…In the literature, different types of controllers are proposed. In [33][34][35][36][37] NN (neural networks) based approaches are implemented. A comparison of four different types of NN controllers is presented in [34].…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy Adaptive Type II Controller for Two-Mass System

et al. 2022

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This paper presents original concepts of control systems for an electrical drive with an elastic mechanical coupling between the motor and the driven mechanism. The synthesis procedure of the speed controller uses a proposed quality index (cost function) of system operation ensures the minimization of both tracking errors and torsional vibrations. Proper selection of the cost function focusses more on the reduction of torsional vibrations due to their negative influence on the drive’s mechanical coupling vitality. The omission of the plant identification of an adaptive fuzzy controller was proposed. Two types of fuzzy controllers were analyzed, namely with type I and type II fuzzy membership functions. The novelty of the presented approach is in the application of a Petri transition layer in a type II fuzzy controller which reduces the numerical complexity in case of a large number of complicated type II fuzzy sets. The presented simulation and experimental results prove that the best dumping of mechanical vibrations ensures the adaptive fuzzy controller with type II functions and a Petri transition layer.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fuzzy Adaptive Type II Controller for Two-Mass System

et al. 2022

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“…Applying the MPC allows to obtain optimal transients (according to the specified cost function) and at the same time, implement limitations of the control signal and the internal states of the plant. Additionally, examples of other, control methodologies can be found in the literature [25,26].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Control Structure with Neural Data Processing Applied for Electrical Drive with Elastic Shaft

Kaminski

Szabat

2021

Energies

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This paper presents issues related to the adaptive control of the drive system with an elastic clutch connecting the main motor and the load machine. Firstly, the problems and the main algorithms often implemented for the mentioned object are analyzed. Then, the control concept based on the RNN (recurrent neural network) for the drive system with the flexible coupling is thoroughly described. For this purpose, an adaptive model inspired by the Elman model is selected, which is related to internal feedback in the neural network. The indicated feature improves the processing of dynamic signals. During the design process, for the selection of constant coefficients of the controller, the PSO (particle swarm optimizer) is applied. Moreover, in order to obtain better dynamic properties and improve work in real conditions, one model based on the ADALINE (adaptive linear neuron) is introduced into the structure. Details of the algorithm used for the weights’ adaptation are presented (including stability analysis) to perform the shaft torque signal filtering. The effectiveness of the proposed approach is examined through simulation and experimental studies.

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“…One-mass model is widely used accepted in wind power system modelling in literature [57], [58]. Some researchers use the two-mass model to deal with flexible modes from shaft stiffness effects [60]- [62]. The limitation of simple one-mass model and application of other models such as the two-mass model might be of interest in future works.…”

Section: Shaft Modelmentioning

confidence: 99%

Advanced control of large-scale power systems with integration of renewable energy sources

Jiang¹

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Adaptive Backstepping control of wind turbine two mass model

Cited by 10 publications

References 15 publications

Fuzzy Adaptive Type II Controller for Two-Mass System

Fuzzy Adaptive Type II Controller for Two-Mass System

Adaptive Control Structure with Neural Data Processing Applied for Electrical Drive with Elastic Shaft

Advanced control of large-scale power systems with integration of renewable energy sources

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