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Optimization problems in multivariable fuzzy predictive control

L.F. Mendonça, J.M. Sousa, J.M.G. Sá da Costa
2004 International Journal of Approximate Reasoning  
The application of model predictive control (MPC) to complex, nonlinear processes results in a non-convex optimization problem for computing the optimal control actions.  ...  This paper proposes a solution for non-convex optimization problems in multiple-input multiple-output (MIMO) systems.  ...  The B&B optimization applied to MIMO predictive control is presented in Section 3. Multivariable fuzzy predictive filters are introduced in Section 4.  ... 
doi:10.1016/j.ijar.2003.10.006 fatcat:zfu4nlyr3bflvnfvifjlxsx5le

Application of Fuzzy Model Predictive Control in Multivariable Control of Distillation Column

R. Sivakumar, K. Suresh Manic, V. Nerthiga, R. Akila, K. Balu
2010 International journal of chemical Engineering and Applications  
In this paper, a fuzzy model predictive control strategy is proposed for multivariable nonlinear control problem in a distillation column.  ...  An optimization technique is developed to minimize the difference between the model predictions and the desired prediction horizon. Comparisons are made with conventional controllers.  ...  Fig.2 gives the general idea of a general model predictive control. The MPC optimization problem can be formulated as a search in the discrete space of control actions.  ... 
doi:10.7763/ijcea.2010.v1.7 fatcat:fdkgcsnijzg6xfdu4lmq4c6tzy

State-of-the-art in control engineering

Štefan Kozák
2014 Journal of Electrical Systems and Information Technology  
Main ideas covered in this paper are motivated namely by the development of new advanced control engineering methods (predictive, hybrid predictive, optimal, adaptive, robust, fuzzy logic, and neural network  ...  The paper deals with new trends in research, development and applications of advanced control methods and structures based on the principles of optimality, robustness and intelligence.  ...  2 , Fuzzy Control (PID, MPC Hinf, IMC) FPGA) Cascade Control (CC) Multivariable Control Model Predictive Control Neural Network Control Methods (State Space and (MPC-DMC, MPC-GPC) (Optimal, MPC, FPGA)  ... 
doi:10.1016/j.jesit.2014.03.002 fatcat:hxcl5r2325eljcguo54p5lj53i

Fuzzy–neural Model Predictive Control of Multivariable Processes [chapter]

Michail Petrov, Sevil Ahmed, Alexander Ichtev, Albena Tanev
2011 Advanced Model Predictive Control  
In this chapter, Nonlinear Model Predictive Control (NMPC) is studied as a more applicable approach for optimal control of multivariable processes.  ...  Introduction Predictive control is a model-based strategy used to calculate the optimal control action, by solving an optimization problem at each sampling interval, in order to maintain the output of  ...  Description of the multi tank system as a multivariable controlled process Liquid levels Н 1 , Н 2 , Н 3 in the tanks are the state variables of the system (Fig. 4 ).  ... 
doi:10.5772/16828 fatcat:wxvy7ysj3vfmhbgm5dwwmic26u


S. Vieira, J.M.C. Sousa, F.O. Durão
2005 IFAC Proceedings Volumes  
In this paper, model predictive control is applied to a column flotation process using a nonlinear fuzzy model.  ...  Accurate nonlinear models using soft computing (e.g. fuzzy and neural) techniques are increasingly being used in model based control.  ...  When a nonlinear model of the process is used, the resulting optimization problem in model predictive control is often non-convex.  ... 
doi:10.3182/20050703-6-cz-1902.01700 fatcat:uexmk37ypfbr7akpu3hdqwrlvy

Book Announcements

1992 Journal of Guidance Control and Dynamics  
; cascade control systems; feedfor- ward control; structures of multivariable processes; parame- ter-optimized multivariable control systems; multivariable ma- trix polynomial control systems; multivariable  ...  versus probability; fuzzy associative memories; comparison of fuzzy and neural truck backer-upper control systems; fuzzy image transform coding; comparison of fuzzy and Kalman filter target tracking control  ... 
doi:10.2514/3.56568 fatcat:xgdb24qnardvxlx6husadcjgrm

Nonlinear multivariable supervisory predictive control

X.J. Liu, L.X. Niu, J.Z. Liu
2009 2009 American Control Conference  
While model predictive control has been widely used in CCPP, incorporating of constraints is a major problem.  ...  GPC, a nonlinear long-range predictive controller based on neural networks [2], and a nonlinear generalized predictive controller based on neuro-fuzzy network [3] .  ...  This paper proposes a nonlinear multivariable supervisory predictive control scheme.  ... 
doi:10.1109/acc.2009.5160006 dblp:conf/amcc/LiuNL09 fatcat:o5nb2bak6zb2hpu3sshlrqor7i

Fuzzy rule-based classifier for Fault Prediction in a Thermoelectric Unit

Otacílio José Pereira, Cristiano Hora de Oliveira Fontes, Carlos Arthur M. Teixeira Cavalcante, Sérgio Torres Sá Barretto, Luciana de Almeida Pacheco
2014 Brazilian Journal of Operations & Production Management  
This paper presents the implementation of a fuzzy inference system for fault prediction in a gas turbine of a thermoelectric unit.  ...  Pattern recognition from data is a potential alternative for the extraction of knowledge about processes and it may be useful for predicting failures, control and support decision making, among others.  ...  and its application in industrial process (fault detection, control tuning, optimal control, among others) may pose challenges but also knowledge discovery.  ... 
doaj:4a55284dd19b47138ab6de907fdae8e0 fatcat:dns7wxvjrve4begy5pltmlsfqq

Integration of cuckoo search and fuzzy support vector machine for intelligent diagnosis of production process quality

Huiqin Zhang, College of Management Science, Chengdu University of Technology, Chengdu 610059, China, JinChun Wang, Meng Wang, Xudong Chen
2017 Journal of Industrial and Management Optimization  
Using multivariate exponentially weighted moving average (MEWMA) control chart to joint monitor the multiple quality characteristics.  ...  The quality of High-tech products usually influenced by numerous cross-correlation quality characteristics in production process.  ...  However, the problem of abnormal diagnosis and control of multivariable process quality has its own complexity.  ... 
doi:10.3934/jimo.2020150 fatcat:3c44cdypljccxfp5s5bxq7o43i

Constrained multiobjective PSO and T-S fuzzy models for predictive control

2018 Turkish Journal of Electrical Engineering and Computer Sciences  
Multiobjective optimization problems are still a challenging area in the field of control system engineering.  ...  In this context, the current study describes a new multivariable predictive control scheme formulated by using the T-S fuzzy modeling method and a new constrained multiobjective PSO algorithm.  ...  In order to tackle the nonlinearity and the coupling problems typically seen in MIMO systems, some works have designed multivariable predictive controllers based on advanced techniques of modeling and  ... 
doi:10.3906/elk-1803-14 fatcat:6bzncfbdkbah5ixprz4nrs6yr4

A Stable Model-Based Fuzzy Predictive Control Based on Fuzzy Dynamic Programming

Khaled Belarbi, FayÇal Megri
2007 IEEE transactions on fuzzy systems  
A stable model based fuzzy predictive controller based on fuzzy dynamic programming is introduced.  ...  His current interests include control of nonlinear systems and fuzzy and predictive control.  ...  The model based fuzzy predictive control problem is cast as a multistage decision making problem.  ... 
doi:10.1109/tfuzz.2006.890656 fatcat:cuq2eptggvforkvhgsuotwdvfq


2016 Procedia Computer Science  
Logic in Job Satisfaction Performance Problem S.Z.  ...  of Multivariable Properties of Reservoir Rocks by Using Fuzzy Clustering R.Y.  ... 
doi:10.1016/s1877-0509(16)32664-3 fatcat:3655czqppvemrkzborsn3kyhou

Cumulative subject index

1978 Information and Control  
policies, optimal: for zero-memory re- placement problem, 37, 90 Control networks asynchronous, interconnecting, 38, 343 Convolutional codes generalized permutations in, 38, 213 Correlations multivariate  ...  decision problems: formulation, with fuzzy information, 38, 135 events: probability measures of, use in fuzzy decision problems, 38, 135 information, fuzzy decision problems with, 38, 135 logic  ... 
doi:10.1016/s0019-9958(78)90707-6 fatcat:3g6qa5hi2zc2lgyyvndbar65di

Fuzzy model predictive control using Takagi-Sugeno model

Mai Van Sy, Phan Xuan Minh
2008 2008 International Conference on Control, Automation and Systems  
INTRODUCTION Model Predictive Control (MPC) is a powerful tool for controlling industrial processes, especially nonlinear and multivariable cases.  ...  FUZZY MODEL PREDICTIVE CONTROL Fuzzy Modeling Fuzzy Inference Systems can be considered the universal approximators [1] .  ... 
doi:10.1109/iccas.2008.4694579 fatcat:k635c4k445gbxi6zz4sqtgney4

Page 2716 of Mathematical Reviews Vol. , Issue 98D [page]

1998 Mathematical Reviews  
SISO control problems in the open-loop struc- ture.  ...  Moreover, both of the nonlinear optimization problems can be formulated as linear matrix inequality (LMI) problems, i.e., convex optimization problems.  ... 
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