Solution of Fractional Optimal Control Problems by using orthogonal collocation and Multi-objective Optimization Stochastic Fractal Search

In this contribution the solution of Fractional Optimal Control Problems (FOCP) by using the Orthogonal Collocation Method (OCM) and the Multi-objective Optimization Stochastic Fractal Search (MOSFS) algorithm is investigated. For this purpose, three classical case studies on engineering are conside...

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Bibliographic Details
Published in:Advances in computational intelligence 2021-10, Vol.1 (4), p.3, Article 3
Main Authors: Lima, J. V. C. F., Lobato, F. S., Steffen Jr, V.
Format: Article
Language:English
Subjects:
Algorithms
Approximation
Artificial Intelligence
Calculus
Collocation methods
Computational Intelligence
Control theory
Engineering
Fractals
Lagrange multiplier
Machine Learning
Multiple objective analysis
Numerical analysis
Optimal control
Optimization
Optimization techniques
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Summary:In this contribution the solution of Fractional Optimal Control Problems (FOCP) by using the Orthogonal Collocation Method (OCM) and the Multi-objective Optimization Stochastic Fractal Search (MOSFS) algorithm is investigated. For this purpose, three classical case studies on engineering are considered. Initially, the concentration profiles of laccase enzyme production process are analyzed to evaluate the influence of fractional order. Then, two classical FOCP (Catalyst Mixing and Batch Reactor) are solved by using the association between OCM and MOSFS approachesthrough the formulation and solution of a multi-objective optimization problem. The results indicate that the variation of the fractional order impliesdifferent values for the original objective function. In addition, physicallyincoherent profiles can be obtained by considering the fluctuation of the fractional order. Finally, the proposed MOSFS is considered as apromising methodology to solve multi-objective optimization problems.
ISSN:2730-7794
2730-7808
DOI:10.1007/s43674-021-00003-x