Authors:
Ivan Ryzhikov
;
Christina Brester
and
Eugene Semenkin
Affiliation:
Siberian State Aerospace University, Russian Federation
Keyword(s):
Multi-output System, Linear Differential Equation, Multi-objective Optimization, Parameters Identification, Initial Value Estimation.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Engineering Applications
;
Evolutionary Computation and Control
;
Evolutionary Computing
;
Genetic Algorithms
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Optimization Algorithms
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
Soft Computing
;
System Identification
;
System Modeling
Abstract:
A multi-criteria multi-output dynamical system identification problem is considered. The inverse mathematical problem of estimating the parameters of a system of differential equations and its initial point using the measured data is provided for the hexadecane disintegration reaction. The aim of modelling is to approximate the dynamical behaviour of hexadecane and the concentrations of its products, which according to chemical kinetics are determined by a differential equation. Since the dynamical model adequacy is based on the error between its output and the sample data and the output itself depends on the initial point values, the inverse mathematical modelling problem is the simultaneous estimation of the model parameters and the initial point. At the same time, the initial point is unknown and the sample data is noisy, and for this reason, the inverse mathematical modelling problem is reduced to a two-objective optimization problem. The reduced problem is a sample of black-box
optimization problems; it is complex, multimodal and requires a reliable technique to solve it. This is why a specific heterogeneous multi-objective genetic algorithm with the island meta-heuristic is used and its efficiency in solving this problem is proved by the investigation results.
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