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To improve the efficiency and performance of a photovoltaic system (PV) an observer-based fuzzy controller design methodology is provided in the study. The desired controller is achieved by employing a combination of linear matrix inequalities (LMIs). The system consists of a photovoltaic generator (PVG) connected to a boost converter. A battery is linked to the boost converter to stock additional energy for further use. A fuzzy controller based on a T–S fuzzy type observer that guarantees a predefined L2performance is suggested to achieve maximum power point tracking (MPPT) even under changing weather conditions. An optimal trajectory should be tracked to ensure maximum power operation. For this aim, a specific reference fuzzy model is proposed to create the aimed trajectories. Using this method, the system dynamics are precisely reproduced over a large range of operations. The whole T–S fuzzy methodology, suggested in this paper, aims to ensure the most efficient energy recovery to recharge a battery under partially shaded conditions, resulting in high system efficiency. The proposed method is simulated with MATLAB/SIMULINK and the simulation results, with realistic reference trajectories, are driven while taking into account climate variations. The analysis of these simulations, along with a comparison with two other commonly used approaches, led to the conclusion that the suggested strategy succeeded in reducing the tracking time, as well as eliminating the oscillation that often occurs around maximum power point (MPP).

By using Takagi–Sugeno (T–S) fuzzy set approach, this paper proposes a robust dynamic output feedback (DOF) control for nonlinear fractional-order systems satisfying 0<α<1. First, using a Fractional Lyapunov function, the novel DOF controller guarantees the stability of the closed-loop system. The proposed approach allows avoiding appearance of crossing terms between the controller’s and the T–S system’s input matrices leading to easier LMI formulation. Second, a new controller is developed by combining a fuzzy dependent Lyapunov function and some special derivations on the controller parameters. This leads to some sufficient conditions in the form of strict linear matrix inequalities (LMIs). When compared with previous work, the proposed method not only has abilities to handle the fuzzy system with the time-derivatives of the membership functions but also can deal with the parametric uncertainties effectively. Simulation examples are provided to demonstrate the validity of the proposed conditions.

This study addresses the issue of robust dynamic output feedback control (DOF) for polynomial Takagi–Sugeno (T-S) fuzzy systems in the Finite Frequency (FF) domain. Sufficient conditions for designing the robust DOF control are derived in terms of the sum of squares (SOS). The proposed strategy is built in the FF domain to reduce conservation-generated by the techniques established in the whole frequency domain. In addition, there are no transformation matrices or equality constraints under these conditions, which simplifies the numerical solution. To show the validity of the suggested technique, several numerical examples are presented.

This paper deals with static output-feedback H∞control for a system of the vehicle lateral dynamics, represented by Takagi–Sugeno (T–S) fuzzy models. Sufficient conditions of the existence of H∞control based on the static output-feedback are presented. The bilinear matrix inequalities are converted to a set of linear matrix inequalities, with the aid of some special derivations. Simulation results demonstrate the effectiveness of the proposed method.