A synthesis of observer-based controller for stabilizing uncertain T-S fuzzy systems

Robust observer synthesis for the uncertain large‐scale T–S fuzzy system

“…The original non‐linear system is transformed into the T–S fuzzy system by employing the non‐linear sector method or linear method [8, 9]. There exist a number of previous studies that focus on stability analysis [10], controller design [11], and observer synthesis [12] for the T–S fuzzy system. Moreover, recently, there has been considerable interest in modelling the large‐scale non‐linear system under the framework of the T–S fuzzy model, which is called the large‐scale T–S fuzzy system.…”

“…Hence, observer synthesis is considered as an alternative option to overcome these difficulties and has attracted a considerable attention from researchers. Various studies paying attention to the observer design for the T–S fuzzy system have been published in recent years [11, 12, 28–37]. For example, in [11], an observer‐based controller was designed for the uncertain T–S fuzzy system.…”

“…Various studies paying attention to the observer design for the T–S fuzzy system have been published in recent years [11, 12, 28–37]. For example, in [11], an observer‐based controller was designed for the uncertain T–S fuzzy system. However, the approach in [11] still has two limitations: first, the uncertainties must satisfy the bounded constraints; second, a controller is needed to eliminate the impacts of the uncertainties.…”

“…For example, in [11], an observer‐based controller was designed for the uncertain T–S fuzzy system. However, the approach in [11] still has two limitations: first, the uncertainties must satisfy the bounded constraints; second, a controller is needed to eliminate the impacts of the uncertainties. Additionally, the unknown input method was introduced in [32–34] to construct the observer for the unknown input T–S fuzzy system.…”

Observer‐based controller synthesis for uncertain polynomial systems

“…Several methods [1] were studied to design a controller for non-linear systems. Nowadays, the modelling non-linear system under the framework of Takagi-Sugeno (T-S) fuzzy model [2][3][4] is considered as the popular method, in which the non-linear system was represented by a set of sublinear systems and fuzzy rules. However, the T-S fuzzy system only represented exactly the nonlinear system within a compact set of state variables within a specific range.…”