Lead-lag Controller Design for Time Delay Systems Using Genetic Algorithms

Hassen, Nidhal Ben; Saadaoui, Karim; Benrejeb, Mohamed

doi:10.24846/v26i1y201710

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…In addition, the control of real systems is characterized by the presence of constraints, which make the task of multiobjective optimization more difficult. In the context of optimization problems, various evolutionary computation approaches have been developed in the past two decades [9,10]. In the field of evolutionary multiobjective optimization, there exist Pareto-based approaches and other techniques [11].…”

Section: Introductionmentioning

confidence: 99%

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

Thamallah¹,

Sakly²,

M’Śahli³

2018

Turk J Elec Eng & Comp Sci

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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. The T-S fuzzy modeling technique is applied to forecast the behaviors of the nonlinear system. It also aims at establishing some conditions so that the proposed control loop is asymptotically stable. The obtained experimental results show that the combination of the philosophy of the T-S fuzzy model and multiobjective PSO is very good in the controlling of nonlinear multivariable processes. The satisfactory tracking results with small values of MRE demonstrate the proof of capability of the proposed algorithm and the accuracy of the T-S modeling approach. Meanwhile, experimental results show that, compared with the ones obtained with standard MPC, the proposed method is of high effectiveness in term of the control increments optimization and the errors in the presence of disturbances.

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Section: Introductionmentioning

confidence: 99%

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

Thamallah¹,

Sakly²,

M’Śahli³

2018

Turk J Elec Eng & Comp Sci

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“…Genetic Algorithms (GAs) are original methods that can be used in many fields, i.e. like [1] as well as for feature selection [5]. Often, selection methods that use GA are based on some wrapper methods for the evaluation of individuals.…”

Section: Introductionmentioning

confidence: 99%

A Novel Face Recognition Approach Based on Genetic Algorithm Optimization

Moussa¹,

Hmila²,

Douik³

2018

STUD INFORM CONTROL

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Abstract:In the field of image processing and recognition, discrete cosine transform (DCT) and principal component analysis (PCA) are two widely used techniques. In this paper we present a face recognition approach based on them. Feature selection (FS) is a global optimization problem in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, and results in acceptable recognition accuracy. It is the most important step that affects the performance of a face recognition system. Genetic Algorithms (GA), one of the most recent techniques in the field of feature selection, are a type of evolutionary algorithms that can be used also to solve this issue. The application of a GA in the resolution of a problem requires the coding of the potential solutions to this problem in finite bit chains in order to constitute the chromosomes coming from a population formed by candidate points. The aim is to find a selective function allowing good discrimination between chromosomes and to define the genetic operators that will be used. In this sense, this approach seeks to develop a system of face recognition using Genetic Algorithm and a DCT-PCA combination for feature selection and dimensionality reduction, to be applied to an archive of images of human faces. The proposed approach is applied on various Face Databases. Experimental results demonstrate the effectiveness of this approach compared to state of the art in face recognition.

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Lead-lag Controller Design for Time Delay Systems Using Genetic Algorithms

Cited by 2 publications

References 14 publications

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

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

A Novel Face Recognition Approach Based on Genetic Algorithm Optimization

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