Articles
Publication Date: 2025
International Journal of Robust and Nonlinear Control (10498923)35(18)pp. 8131-8143
This paper focuses on the challenge of integrated active fault-tolerant control (IAFTC) for linear discrete-time systems utilizing compatible linear matrix inequality (LMI) techniques. The presence of input nonlinearity, additive faults, external disturbances, and uncertainty in the system matrix makes this problem more applicable to real-world systems while expanding the complexity and functional range. In such a situation, the designer must take an integrated approach instead of synthesizing fault estimation (FE) and fault-tolerant control (FTC) as separate modules; yet, the LMI-based design conditions can be overly conservative. As a result, the reduction of the bi-directional interaction effect between FE and FTC units does not lead to satisfactory improvements in the overall behavior of the control system. To provide an integrated design approach, we propose a dynamic output feedback controller that plays the role of the FTC unit. This scheme incorporates two effective decision parameters and a descriptor observer (As FE), contributing to the IAFTC block's functionality. The design criteria are formulated using tractable LMI constraints in a convex optimization problem, and the (Formula presented.) -stability criterion is proved for the overall closed-loop system. The superiority and effectiveness of the proposed IAFTC are demonstrated through three comparative simulation examples. © 2025 John Wiley & Sons Ltd.
Publication Date: 2024
JVC/Journal of Vibration and Control (10775463)30(9-10)pp. 2251-2270
This paper addresses the problem of maximum power point tracking of photovoltaic (PV) systems in the presence of model uncertainty as well as varying load and atmospheric conditions using techniques based on a Takagi–Sugeno fuzzy model. The proposed approach relies on the linear matrix inequality tool, Lambert W function, and the Newton–Raphson method. First, adopting a quadratic Lyapunov function, an active observer-based fuzzy non-parallel distributed compensation (non-PDC) controller is designed for asymptotic tracking of the desired reference input. Next, to subdue the impact of uncertainty on the PV system, the closed-loop nominal system is regarded as a reference model, and then the main control law is developed using an online lumped uncertainty estimator and keeping the nominal control law within the staple controller. This control law does not require that the bounds on uncertainties be known. The reference voltage is determined by a novel maximum power point-seeking algorithm that is organized based on the one-diode model of PV panel, Lambert W function, and Newton–Raphson method. Finally, simulations are performed for three scenarios to point out the merits and effectiveness of the proposed methodology in the presence of system uncertainties, environmental changes, and load variations. © The Author(s) 2023.
