Stabilization of gas-lift oil wells by a nonlinear model predictive control scheme based on adaptive neural network models

Salahshoor, Karim; Zakeri, Sepide; Sefat, Morteza Haghighat

doi:10.1016/j.engappai.2013.03.007

Cited by 31 publications

(10 citation statements)

References 15 publications

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“…Due to the flexibility and outstanding approximation ability for nonlinear functions, NN has been a topic issue and plenty of researchers try to apply it in the problems of nonlinear system. Salahshoor et al 17 proposed a method of adaptive growing and pruning radial basis function (GAP-RBF) NNs to recursively capture the essential dynamics of casing-heading instability in a nonlinear model structure. Mehraeen et al 18 introduced a novel decentralized state feedback stabilization controller for a class of nonlinear interconnected discrete-time systems in affine form with unknown subsystem dynamics, control gain matrix and interconnection dynamics by employing NNs.…”

Section: Adaptive Neural Networkmentioning

confidence: 99%

Improved adaptive neural network control for humanoid robot hand in workspace

Liu

Zheng

et al. 2014

Proceedings of the Institution of Mechanical Engineers, Part C:

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In order to improve the control performance of humanoid robot hand in workspace, an adaptive control method based on improved neural network was proposed. rival-penalized competitive learning and recursive orthogonal least-squares algorithms were applied to reinforce the learning capability of Gaussian radial basis function neural network and realize the real-time of neural network. Moreover, an improved neural network model for humanoid robot hand was established with Ge-Lee matrix and its operator, and a controller was designed. Finally, an example of humanoid robot hand finger was provided. The results showed that the proposed control method could effectively control the unknown nonlinear dynamic properties and load disturbances of the finger with a much smaller tracking errors.

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Section: Adaptive Neural Networkmentioning

confidence: 99%

Improved adaptive neural network control for humanoid robot hand in workspace

Liu

Zheng

et al. 2014

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…Nevertheless, the positive nonlinear systems [8] have a notable wide range of practice application. It has been proven that T-S fuzzy model is an excellent representation for nonlinear system [9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Stability analysis for switched positive T–S fuzzy systems

et al. 2016

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“…As a parallel, distributive and adaptive system, it can be effectively applied in complex and non-linear problems in different engineering disciplines [35][36][37]. Nowadays, ANN is a computational tool in petroleum engineering studies because not only it is a model-free function predictor but also it does not require any detailed knowledge regarding the process [38][39][40].…”

Section: Artificial Neural Networkmentioning

confidence: 99%

Multi-Objective Optimization of Microemulsion Flooding for Chemical Enhanced Oil Recovery

Karambeigi

Asl

Nasiri

2018

Oil & Gas Science and Technology - Rev. IFP Energies nouvel

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-Microemulsion flooding is one of the most effective methods of Chemical Enhanced Oil Recovery (CEOR), particularly for the production of residual oil trapped in unconventional reservoirs. A critical step for successful application of this technique is to achieve a suitable formulation. Previous studies have almost focused on the technical aspects while considering both practical and economic matters as conflicting objectives have been neglected. In the present paper, the formulation of microemulsion is optimized based on the trade-off between scientific and financial responses using a hybrid workflow in which experimental design and artificial intelligence methodologies are composed. To appraise the efficiency of developed algorithm, a challenge case study is first evaluated and compared to previous approaches. Thereafter, the second case is examined in which a newly developed formulation of microemulsion for high temperature carbonate reservoirs is optimized. The outcomes of this multi-attribute workflow are compared to a single-objective algorithm. The results indicate the outstanding performance of the proposed approach for multi-objective optimization of microemulsion formulation. Eventually, the possible concerns regarding the application of microemulsion flooding in unconventional reservoirs are discussed.

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Stabilization of gas-lift oil wells by a nonlinear model predictive control scheme based on adaptive neural network models

Cited by 31 publications

References 15 publications

Improved adaptive neural network control for humanoid robot hand in workspace

Improved adaptive neural network control for humanoid robot hand in workspace

Stability analysis for switched positive T–S fuzzy systems

Multi-Objective Optimization of Microemulsion Flooding for Chemical Enhanced Oil Recovery

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