Parallel distributed neuro-fuzzy model predictive controller applied to a hydro turbine generator

2008 ◽  
Author(s):  
Michail Petrov ◽  
Albena Taneva ◽  
Teofana Puleva ◽  
Sevil Ahmed
Keyword(s):  
Fuzzy Model ◽  
Turbine Generator ◽  
Model Predictive Controller ◽  
Hydro Turbine ◽  
Neuro Fuzzy ◽  
Predictive Controller

scholarly journals Fuzzy Model Predictive Controller for Artificial Pancreas

2018 ◽  
Vol 9 (3) ◽  
pp. 1178
Author(s):  
Mohamed El Hachimi ◽  
Abdelhakim Ballouk ◽  
AbdNaceur Baghdad
Keyword(s):  
Fuzzy Logic ◽  
Artificial Pancreas ◽  
Fuzzy Model ◽  
Model Predictive Controller ◽  
Prediction Horizon ◽  
Predictive Controller ◽  
Fuzzy Logic Method ◽  
Model Predictive Controllers ◽  
Predictive Controllers ◽  
Commercial Platform

This work consists on new tuning of Model Predictive Controllers using Fuzzy Logic method. Tree relevant parameters are automatically adjusted the prediction horizon Np, the input weight R and the output weight Q. The proposed controller is implemented in an Artificial Pancreas and tested under realistic conditions in a commercial platform of simulation. The result of the simulations revealed the success of such a method to improve the controller’s performances compared to the previous ones.

NEURO-FUZZY MODEL FOR ENVIRONMENTAL IMPACT ASSESSMENT

2011 ◽  
Vol 10 (3) ◽  
pp. 381-386 ◽  
Author(s):  
Alexandru Trandabat ◽  
Marius Pislaru ◽  
Silvia Avasilcai
Keyword(s):  
Environmental Impact ◽  
Impact Assessment ◽  
Environmental Impact Assessment ◽  
Fuzzy Model ◽  
Neuro Fuzzy

Enlarging the region of stability in robust model predictive controller based on dual-mode control

2021 ◽  
pp. 014233122110123
Author(s):  
Fatemeh Khani ◽  
Mohammad Haeri
Keyword(s):  
Stability Region ◽  
Linear Matrix ◽  
Input State ◽  
Dual Mode ◽  
Model Predictive Controller ◽  
Mode Control ◽  
Robust Model ◽  
Output Constraints ◽  
Predictive Controller ◽  
The Stability

Industrial processes are inherently nonlinear with input, state, and output constraints. A proper control system should handle these challenging control problems over a large operating region. The robust model predictive controller (RMPC) could be an linear matrix inequality (LMI)-based method that estimates stability region of the closed-loop system as an ellipsoid. This presentation, however, restricts confident application of the controller on systems with large operating regions. In this paper, a dual-mode control strategy is employed to enlarge the stability region in first place and then, trajectory reversing method (TRM) is employed to approximate the stability region more accurately. Finally, the effectiveness of the proposed scheme is illustrated on a continuous stirred tank reactor (CSTR) process.

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