Displaying similar documents to “Nonlinear system identification with a real-coded genetic algorithm (RCGA)”

Structural identifiability analysis of nonlinear time delayed systems with generalized frequency response functions

Gergely Szlobodnyik, Gábor Szederkényi (2021)

Kybernetika

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In this paper a novel method is proposed for the structural identifiability analysis of nonlinear time delayed systems. It is assumed that all the nonlinearities are analytic functions and the time delays are constant. We consider the joint structural identifiability of models with respect to the ordinary system parameters and time delays by including delays into a unified parameter set. We employ the Volterra series representation of nonlinear dynamical systems and make use of the frequency...

Boyd index and nonlinear Volterra equations.

Jesús M. Fernández Castillo, W. Okrasinski (1991)

Extracta Mathematicae

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In mathematical models of some physical phenomena a new class of nonlinear Volterra equations appears ([5],[6]). The equations belonging to this class have u = 0 as a solution (trivial solution), but with respect to their physical meaning, nonnegative nontrivial solutions are of prime importance.

A comparative and experimental study on gradient and genetic optimization algorithms for parameter identification of linear MIMO models of a drilling vessel

Stanisław Bańka, Michał Brasel, Paweł Dworak, Krzysztof Jaroszewski (2015)

International Journal of Applied Mathematics and Computer Science

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The paper presents algorithms for parameter identification of linear vessel models being in force for the current operating point of a ship. Advantages and disadvantages of gradient and genetic algorithms in identifying the model parameters are discussed. The study is supported by presentation of identification results for a nonlinear model of a drilling vessel.

Analysis of an isopetype dual algorithm for optimizing control and nonlinear optimization

Wojciech Tadej, Piotr Tatjewski (2001)

International Journal of Applied Mathematics and Computer Science

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First results concerning important theoretical properties of the dual ISOPE (Integrated System Optimization and Parameter Estimation) algorithm are presented. The algorithm applies to on-line set-point optimization in control structures with uncertainty in process models and disturbance estimates, as well as to difficult nonlinear constrained optimization problems. Properties of the conditioned (dualized) set of problem constraints are investigated, showing its structure and feasibility...

An improved ant algorithm for Multi-mode Resource Constrained Project Scheduling Problem

Peng Wuliang, Huang Min, Hao Yongping (2014)

RAIRO - Operations Research - Recherche Opérationnelle

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Many real-world scheduling problems can be modeled as Multi-mode Resource Constrained Project Scheduling Problems (MRCPSP). However, the MRCPSP is a strong NP-hard problem and very difficult to be solved. The purpose of this research is to investigate a more efficient alternative based on ant algorithm to solve MRCPSP. To enhance the generality along with efficiency of the algorithm, the rule pool is designed to manage numerous priority rules for MRCPSP. Each ant is provided with an...