Multi-objective dynamic optimization of path-constrained switched systems

A multi-objective dynamic optimization algorithm is proposed for path-constrained switched systems to locate approximated local Pareto solutions with specified tolerances. The algorithm is based on iteratively solving single-objective modified ϵ-constraint dynamic optimization problems to avoid gene...

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Bibliographic Details
Published in:	Automatica (Oxford) Vol. 159; p. 111326
Main Authors:	Zhang, Chi, Fu, Jun
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.01.2024
Subjects:	Multi-objective dynamic optimization Semi-infinite programs Switched systems ε-constraint method Switched systems Multi-objective dynamic optimization Semi-infinite programs ε-constraint method
ISSN:	0005-1098, 1873-2836
Online Access:	Get full text
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Summary:	A multi-objective dynamic optimization algorithm is proposed for path-constrained switched systems to locate approximated local Pareto solutions with specified tolerances. The algorithm is based on iteratively solving single-objective modified ϵ-constraint dynamic optimization problems to avoid generating weak Pareto solutions. These problems are first reduced to semi-infinite programs embedded with ordinary differential equations by performing the control vector parameterization technique. Then the guaranteed feasibility is attained within a finite number of iterations by enforcing the path constraints at discretized time points with a restriction parameter on the right-hand side. Furthermore, the approximation error of the obtained local Pareto solutions is quantitatively analyzed. The result shows that the Pareto approximation error can be directly controlled via user-specified parameters. Finally, the effectiveness of the algorithm is illustrated via a numerical example.
ISSN:	0005-1098 1873-2836
DOI:	10.1016/j.automatica.2023.111326