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Fuzzy model predictive control of non-linear processes using genetic algorithms

Haralambos Sarimveis, George Bafas
2003 Fuzzy sets and systems (Print)  
The method is based on a dynamic fuzzy model of the process to be controlled, which is used for predicting the future behavior of the output variables.  ...  The problem is solved on line using a specially designed genetic algorithm, which has a number of advantages over conventional non-linear optimization techniques.  ...  based on a non-linear model of the process [3] .  ... 
doi:10.1016/s0165-0114(02)00506-7 fatcat:64voxvnjinb5blnzzjhvp35yhe

Intelligent modelling of the indoor climate in buildings by soft computing

Alexander E. Gegov
2001 European Society for Fuzzy Logic and Technology  
Takagi-Sugeno fuzzy models are built by subtractive clustering to provide initial values of the antecedent non-linear membership functions parameters and the consequent linear algebraic equations coefficients  ...  The paper considers the application of soft computing techniques for predictive modelling in the built sector.  ...  Another advantage of the TS fuzzy model is its capability to approximate non-linear input-output mappings by a number of linearised models at a number of operating points.  ... 
dblp:conf/eusflat/Gegov01 fatcat:xbqv7reqvbethn3o6oi45qeply

Hybrid fuzzy predictive control based on genetic algorithms for the temperature control of a batch reactor

Javier Causa, Gorazd Karer, Alfredo Núñez, Doris Sáez, Igor Škrjanc, Borut Zupančič
2008 Computers and Chemical Engineering  
In this paper we describe the design of hybrid fuzzy predictive control based on a genetic algorithm (GA).  ...  We also present a simulation test of the proposed algorithm and a comparison with two hybrid predictive control methods: Explicit Enumeration and Branch and Bound (BB).  ...  Acknowledgement This work was supported in part by the Ministry of Science, Higher Education and Technology of the Republic of Slovenia and by Fondecyt grants 1061156 (Chile) and 7070293 (Chile-Slovenia  ... 
doi:10.1016/j.compchemeng.2008.05.014 fatcat:pjktkte5pnh6beaon2ahcqmqai

A Summary of PID Control Algorithms Based on AI-Enabled Embedded Systems

Yi Zhou, Muhammad Arif
2022 Security and Communication Networks  
based on genetic algorithms, and PID control based on ant colony algorithms.  ...  PID controllers and corresponding improved ones are utilized in 90% of industrial control processes. In this paper, PID control algorithms are summarized.  ...  Successfully using PID controllers for controlling complex objects is a main research area. e optimal PID control methods are sought among various models such as fuzzy models, non-parametric predictive  ... 
doi:10.1155/2022/7156713 fatcat:ks5tjrftwnhi3eczofiw7z3xym

An ant colony optimization-based fuzzy predictive control approach for nonlinear processes

S. Bououden, M. Chadli, H.R. Karimi
2015 Information Sciences  
optimization controller and adaptive fuzzy model predictive controller.  ...  Then the optimization problem is solved based on an ACO algorithm, used at the optimization process in AFMPC to determine optimal controller parameters of RST control.  ...  The proposed method applies, firstly; a technique for the modeling of nonlinear control processes by using fuzzy modeling approach based on the T-S fuzzy model.  ... 
doi:10.1016/j.ins.2014.11.050 fatcat:32ad4uavsjcm5i4dqlyqcbgiky

Fuzzy model predictive control using Takagi-Sugeno model

Mai Van Sy, Phan Xuan Minh
2008 2008 International Conference on Control, Automation and Systems  
Keywords: Model predictive control, nonlinear control, Takagi-Sugeno fuzzy model, branch and bound, genetic algorithms, fuzzy adaptive alternatives.  ...  The ideas appearing in model predictive controllers are basically: • Explicit use of a model to predict the process output at future time instants (horizon). • Calculation of a control sequence by minimizing  ... 
doi:10.1109/iccas.2008.4694579 fatcat:k635c4k445gbxi6zz4sqtgney4

A Genetic Fuzzy System Based On Improved Fuzzy Functions

Asli Celikyilmaz, I. Burhan Turksen
2009 Journal of Computers  
The new fuzzy function approach optimized with genetic algorithms is proposed to replace the fuzzy operators and operations of FRBs and improve accuracy of the fuzzy models.  ...  Fuzzy inference systems based on fuzzy rule bases (FRBs) have been successfully used to model real problems.  ...  non-linearity of the fuzzy functions.  ... 
doi:10.4304/jcp.4.2.135-146 fatcat:dtlzr4qvarcpnaiujixk6cdmhi

Computationally intelligent modeling and control of fluidized bed combustion process

Cojbasic Zarko, Nikolic Vlastimir, Ciric Ivan, Cojbasic Ljubica
2011 Thermal Science  
Also, efficient fuzzy non-linear fluidized bed combustion process modelling strategy by combining several linearized combustion models has been presented.  ...  Finally, fuzzy and conventional process control systems for fuel flow and primary air flow regulation based on developed models and optimized by genetic algorithms have also been developed.  ...  Applied ANFIS networks were capable of capturing the non-linearities in process data, the training was efficient and prediction accuracy of the obtained models was good.  ... 
doi:10.2298/tsci101205031c fatcat:djwuzlyi4rarzf6ahx5eckg3hu

Fuzzy-logical Control Models of Nonlinear Dynamic Objects

Siddikov Isamiddin Xakimovich, Umurzakova Dilnoza Maxamadjonovna
2020 Advances in Science, Technology and Engineering Systems  
At the first step, the genetic algorithm is used to tune the linear PID controller; it is shown that the obtained coefficients are used at the output of each channel of the fuzzy PID controller.  ...  In the simplest version, three fuzzy controllers are used with one input and one output and separate rule bases. Parameters of fuzzy controllers are optimized using a genetic algorithm.  ...  This result is predictable, since the controller can be considered as an inverse model of the object. Figure 10 .  ... 
doi:10.25046/aj050449 fatcat:rb2g4egxfjbkdluacytvxh5kqy

Online elicitation of mamdani-type fuzzy rules via TSK-based generalized predictive control

M. Mahfouf, M.F. Abbod, D.A. Linkens
2003 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
Generalised Predictive Control (GPC) algorithm using a Takagi-Sugeno Kang (TSK) based CARIMA model structure.  ...  The new generic approach, named Generalised Predictive Self-Organising Fuzzy Logic Control (GPSOFLC), is applied to a well-known non-linear chemical process, the distillation column, and is shown to lead  ...  a fuzzy logic system to provide a computing paradigm for modelling the non-linear process dynamics when a sufficiently accurate model of the process to be controlled is unavailable.  ... 
doi:10.1109/tsmcb.2003.810901 pmid:18238192 fatcat:ssacp5ecana2jkuk6ron25n7au

Artificial Intelligence Techniques in Solar Energy Applications [chapter]

Soteris Kalogirou, Arzu Senc
2010 Solar Collectors and Panels, Theory and Applications  
Therefore, the possibilities of applying AI in solar energy applications will be shown.  ...  Solar Collectors and Panels, Theory and Applications 316 estimation of solar radiation, solar heating, photovoltaic (PV) systems, sun tracking systems, solar air-conditioning systems and many others.  ...  The proposed ANN model proved to be superior over the empirical model because it is capable of reliably capturing the non-linearity nature of solar radiation.  ... 
doi:10.5772/10343 fatcat:5zepz6ek2bfg3l57harzkxx3au

A Review of an Expert System Design for Crude Oil Distillation Column Using the Neural Networks Model and Process Optimization and Control Using Genetic Algorithm Framework

Lekan Taofeek Popoola, Gutti Babagana, Alfred Akpoveta Susu
2013 Advances in Chemical Engineering and Science  
Artificial neural network (ANN), fuzzy logic (FL) and genetic algorithm (GA) framework were chosen as the best methodologies for design, optimization and control of crude oil distillation column.  ...  The use of dynamic mathematical models was also challenging as these models were also time dependent.  ...  Torgashov [14] designed self-optimizing control of complex crude distillation column control using non-linear process model-based method. Khairiyah et al.  ... 
doi:10.4236/aces.2013.32020 fatcat:jpsbojhkjzhclftsxq7jpku6ny

Integration of intelligent systems in development of smart adaptive systems

Esko K. Juuso
2004 International Journal of Approximate Reasoning  
The integration of intelligent systems is based on understanding the different tasks of smart adaptive systems: modelling, intelligent analysers, detection of operating conditions, control and intelligent  ...  efficient statistical analysis, signal processing and mechanistic modelling and simulation.  ...  Fuzzy modelling and control was earlier the main application area. Neural networks and genetic algorithms are integrated to the tuning algorithms.  ... 
doi:10.1016/j.ijar.2003.08.008 fatcat:ew7ku3hkpffkfopsnfjypc6ffm

ON USING SOFT COMPUTING TECHNIQUES IN SOFTWARE RELIABILITY ENGINEERING

HENRIK MADSEN, POUL THYREGOD, BERNARD BURTSCHY, GRIGORE ALBEANU, FLORIN POPENTIU
2006 International Journal of Reliability, Quality and Safety Engineering (IJRQSE)  
Previous investigations have shown the importance of evaluating computer performances and predicting the system reliability.  ...  This paper considers soft computing techniques in order to be used for software fault diagnosis, reliability optimization and for time series prediction during the software reliability analysis.  ...  Acknowledgements This project, partially, has been developed under the NATO-STI program within the framework of the collaborating linkage grant EST.CLG.979542.  ... 
doi:10.1142/s0218539306002094 fatcat:s3opy4twvzb37ks24pwpgwa7ae

Casting Process Improvement by the Application of Artificial Intelligence

Nedeljko Dučić, Srećko Manasijević, Aleksandar Jovičić, Žarko Ćojbašić, Radomir Radiša
2022 Applied Sciences  
One of the segments of smart foundry design is the application of artificial intelligence in the improvement of the casting process.  ...  On the way to building smart factories as the vision of Industry 4.0, the casting process stands out as a specific manufacturing process due to its diversity and complexity.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app12073264 doaj:8123a70c3a564c5e90386a71809f7138 fatcat:2lz3qlq5efaixherzubdb2jlje
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