Stability of multidimensional systems using bio-inspired meta-heuristics

ABSTRACT

Multidimensional or n-D systems (n>1) are models having several independent variables. Among the topics related with this type of systems, stability has been attracting the interest of many researchers. The extension of the stability theory extension from 1-D systems to high dimensions is not straightforward. In this paper, four known meta-heuristics (MH) are used to study systems stability based on their polynomial characteristics over the variables boundaries. The four MH consist of genetic algorithms, particle swarm optimisation, cuckoo search and differential evolution. The results obtained with these MH are compared and the best algorithm highlighted. The computational experiments demonstrate that MH can be applied in studding multidimensional system stability.

KEYWORDS:

• Multidimensional systems
• stability
• genetic algorithms
• particle swarm optimisation
• cuckoo search
• differential evolution

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

E. J. Solteiro Pires   http://orcid.org/0000-0003-3224-4926

P. B. deMoura Oliveira   http://orcid.org/0000-0003-4283-1243

J. A. Tenreiro Machado   http://orcid.org/0000-0003-4274-4879