Stable Takagi-Sugeno Fuzzy Control Designed by Optimization
| dc.citation.epage | 29 | |
| dc.citation.spage | 17 | |
| dc.citation.volume | 15 | |
| dc.contributor.author | Vrkalovic, Sasa | |
| dc.contributor.author | Teban, Teodor-Adrian | |
| dc.contributor.author | Borlea, Ioan-Daniel | |
| dc.date.accessioned | 2023-08-29T07:46:57Z | |
| dc.date.available | 2023-08-29T07:46:57Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | This paper presents the design of Takagi-Sugeno fuzzy controllers in state feedback form using swarm intelligence optimization algorithms. Three such algorithms are used: Particle Swarm Optimization, Simulated Annealing and Gravitational Search Algorithms. Sufficient stability conditions are expressed in terms of linear matrix inequalities considered as constraints in the optimization problem solved by swarm intelligence algorithms. Simulation results concerning an inverted pendulum system are given for illustration of the proposed design. | |
| dc.identifier.uri | https://vaseljena.ues.rs.ba/handle/123456789/596 | |
| dc.language.iso | en | |
| dc.source | International Journal of Artificial Intelligence | |
| dc.subject | fuzzy control, Gravitational Search Algorithms, inverted pendulum system, Particle Swarm Optimization, Simulated Annealing, stability conditions. | |
| dc.title | Stable Takagi-Sugeno Fuzzy Control Designed by Optimization | |
| dc.type | Article |
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