This paper presents a decentralized control problem for stabilizing the nonlinear large-scale descriptor (LSD) systems that use the proportional-plus-derivative state (PD) feedback scheme. The descriptor systems have a great focus on the research because they can contain more physical characteristics than standard state-space systems. At first, each nonlinear subsystem in the LSD system can be represented by Takagi-Sugeno (T-S) LSD systems with interconnections. In order to be more realistic, we additionally consider external disturbances and perturbations that affect the system. Our goal is to design a decentralized (DPD) fuzzy controller, such that the T-S LSD system is stable while the external disturbances and perturbations that affect the system. For the controller design process, sufficient conditions were developed based on the quadratic Lyapunov approach, PD feedback scheme, robust constraint, passivity constraint, and linear matrix inequality (LMI) sufficient criteria. At last, two numerical examples are given to show the application of the main results.

This article addresses the decentralized multi-performance (MP) fuzzy control problem of nonlinear large-scale descriptor (LSD) systems. The considered LSD system contains several subsystems with nonlinear interconnection and external disturbances, and the Takagi–Sugeno fuzzy model (TSFM) is adopted to represent each nonlinear subsystem. Based on the proportional-plus-derivative state feedback (PDSF) scheme, we aim to design a decentralized MP fuzzy controller that guarantees the stabilization, mixed H_∞, and passivity performance control (MHPPC), and the guaranteed cost control (GCC) performance of the closed-loop Takagi–Sugeno LSD (TSLSD) systems. Furthermore, we introduce the Lyapunov stability theory and the free-weighting matrix scheme to analyze the stability of the TSLSD system. The proposed sufficient conditions can be transformed as linear matrix inequality (LMI) forms through Schur’s complement, which can be easily solved with the LMI Toolbox. Finally, to illustrate the proposed approach, two examples and simulation results are presented.

This paper investigates the decentralized fuzzy control problems for nonlinear-state-unmeasured interconnected descriptor systems (IDSs) that utilize the observer-based-feedback approach and the proportional–derivative feedback control (PDFC) method. First of all, the IDS is represented as interconnected Takagi–Sugeno (T–S) fuzzy subsystems. These subsystems can effectively capture the dynamic behavior of the system through fuzzy rules. For the stability analysis of the system, this paper uses the free-weighing Lyapunov function (FWLF), which allows the designer to set the weight matrix, to achieve the desired control performance and design the controller more easily. Furthermore, the control problem can be transformed into a set of linear matrix inequalities (LMIs) through the Schur complement, which can be solved using convex optimization methods. Simulation results confirm the effectiveness of the proposed method in achieving the desired control objectives and ensuring system stability.

This paper proposes a decentralized robust constrained cost fuzzy controller (DRCCFC) design for nonlinear descriptor interconnected systems (DIS) with uncertainties. The considered nonlinear DIS is modeled using Takagi–Sugeno fuzzy model (T-S FM) with fuzzy rules and strong interconnections. To derive sufficient stability conditions, the quadratic Lyapunov function (QLF) and free-weighting function (FWF) are defined. In contrast to the existing control approaches, the proportional–derivative feedback (PDF) control is introduced in this paper. Using the PDF control techniques, the regular and causal problems of the system can be solved easily. Based on the PDF control technique and constrained cost control (CCC) function, a set of fuzzy controllers are designed to effectively control the Takagi–Sugeno descriptor interconnected systems (T-S DIS). Then, the proposed sufficient conditions for the T-S DIS are derived in the form of linear matrix inequalities using the Schur complement technique. Finally, two simulation examples are provided to demonstrate the validity of the proposed control scheme.