Szczegóły publikacji
Opis bibliograficzny
Output tracking control of a nonlinear system based on Takagi-Sugeno fuzzy model: generalized partial eigenstructure assignment approach / Farzad Soltanian, Mokhtar Shasadeghi, Saleh Mobayen, Paweł SKRUCH // IEEE Access [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2169-3536. — 2024 — vol. 12, s. 18520-18535. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 18534-18535, Abstr. — Publikacja dostępna online od: 2024-02-01
Autorzy (4)
- Soltanian Farzad
- Shasadeghi Mokhtar
- Mobayen Saleh
- AGHSkruch Paweł
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 151975 |
|---|---|
| Data dodania do BaDAP | 2024-03-28 |
| Tekst źródłowy | URL |
| DOI | 10.1109/ACCESS.2024.3361034 |
| Rok publikacji | 2024 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | IEEE Access |
Abstract
This paper introduces an innovative optimal control approach to achieve output tracking while incorporating H2 -performance specifications in a specific class of nonlinear dynamics modeled by the Takagi-Sugeno fuzzy model (TSFM). The primary innovation lies in extending partial eigenstructure assignment to TSFM-based nonlinear systems within the framework of sliding mode control (SMC). We propose a two-step methodology for designing optimal sliding surface gains. Initially, optimal state feedback gains are computed for each rule consequence containing a linear subsystem, adhering to predetermined eigenvalues and satisfying H2 -performance criteria. Subsequently, using a convex combination, the overall state feedback gain is calculated and utilized to design sliding matrix gains. The sliding matrix gains are then determined by strategically combining previously calculated state-feedback gains in a convex optimization problem. We reframe the output tracking strategy as a stabilization problem using a virtual control input and reformulate the optimization task concerning tracking state errors. This process yields state feedback gains, sliding gains, and the formulation of the virtual control input. The effectiveness of our approach is verified through comprehensive simulations, emphasizing its capability in addressing output tracking challenges within nonlinear systems.
