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Summary: This article concerns the estimation and tracking control problems for Takagi–Sugeno systems with disturbances and norm bounded uncertainties in presence of sensor and actuator faults (SAF). First, we propose a robust fuzzy observer (RFO) design method to estimate both state and SAF for the considered class of the nonlinear systems. Then, this RFO‐based fault tolerant tracking control is developed not only to compensate the SAF effects but also to ensure the state convergence to desired trajectories in spite of their presence. To reduce the conservatism of design conditions, observer and controller gains are calculated in a single step by solving a set of linear matrix inequality constraints. H∞ criterion is used to attenuate disturbance effects and to reduce the tracking error. Finally, simulation results by considering two types of actuator fault and comparative study on a single link flexible joint manipulator are provided to underline the performances of the mentioned process. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates the H∞ model reduction problem over finite frequency ranges for continuous time Takagi‐Sugeno (T‐S) fuzzy systems. Given an asymptotically stable system, our aim is to find a stable reduced‐order system in such a way that the error of the transfer function between the original system and the reduced‐order one is bounded over a finite frequency range. By using the Finsler's lemma, new sufficient conditions in terms of linear matrix inequalities are derived in different frequency ranges. These conditions provide extra degrees of freedom in the optimization of the H∞ performance when the frequency range of noises is known beforehand. Finally, we demonstrate via numerical examples that our method can achieve much smaller approximation error than existing approaches. [ABSTRACT FROM AUTHOR]

Summary: This paper addresses the sliding mode control problem for a class of uncertain Takagi‐Sugeno fuzzy singular systems with state delay and subject to input nonlinearity. Our purpose is focused on designing an adaptive sliding mode controller for such a complex system. First, a new fuzzy integral‐type sliding function is designed. Then, an adaptive sliding mode control scheme is established such that the resulting closed‐loop system is insensitive to all admissible uncertainties and satisfies the reaching condition. Moreover, delay‐dependent sufficient conditions are derived such that the admissibility and the L2‐L∞ performance requirement of the sliding mode dynamics can be guaranteed in the presence of time delays, external disturbances, and sector nonlinearity input. Finally, the validity and applicability of the proposed theory are illustrated by a numerical example. [ABSTRACT FROM AUTHOR]

The topology based on permanent magnet generator (PMSG) and diode bridge rectifier is frequently used in small wind energy conversion system since it is robust and easy to control. This paper presents a robust control for the wind conversion system based on PMSG and boost DC/DC converter in the aim to maintain the generator rectified voltage at a reference voltage corresponding to the reference power imposed by the supervisory module. The reference power control is guaranteed without measuring the wind speed. The sufficient conditions for state feedback stabilizing designed controller are given in terms of solutions to a linear matrix inequality (LMI) and H ∞ . Simulation tests results are carried out for this wind conversion system topology which operates in a multi-source system, in order to visualize the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: In the paper from Shaocheng Tong and Hiong Li [Observer-based robust fuzzy control of nonlinear systems with parametric uncertainties, Fuzzy Sets and Systems (131) (2002) 165–184], a method to design an observer-based robust fuzzy control of uncertain fuzzy models is proposed. However, the results obtained are not correct. This note intends to circumvent these problems by modifying the result proposed in the aforementioned paper. [Copyright &y& Elsevier]