TS Fuzzy Robust Sampled-Data Control for Nonlinear Systems with Bounded Disturbances

Abstract

We investigate robust fault-tolerant control pertaining to Takagi–Sugeno (TS) fuzzy nonlinear systems with bounded disturbances, actuator failures, and time delays. A new fault model based on a sampled-data scheme that is able to satisfy certain criteria in relation to actuator fault matrix is introduced. Specifically, we formulate a reliable controller with state feedback, such that the resulting closed-loop-fuzzy system is robust, asymptotically stable, and able to satisfy a prescribed H∞ performance constraint. Linear matrix inequality (LMI) together with a proper construction of the Lyapunov–Krasovskii functional is leveraged to derive delay-dependent sufficient conditions with respect to the existence of robust H∞ controller. It is straightforward to obtain the solution by using the MATLAB LMI toolbox. We demonstrate the effectiveness of the control law and less conservativeness of the results through two numerical simulations.

Robust Control for Variable-Order Fractional Interval Systems Subject to Actuator Saturation

“…Theorem 2. System (2) for the case 0 < ν < ν(σ) < ν < 2 is robustly stable if there are X, Y ∈ R n×n subject to (6), and…”

“…In recent decades, there has been a continuing growth in the number of studies on the engineering applications of fractional-order systems (FOS) [1][2][3], and this control system has attracted more and more scholars' attention [4][5][6][7][8]. This is principally because numerous physical systems that have fractional properties in the real world are marked by fractional-order state equations [9,10].…”

Nonuniform Sampled‐Data Control for Synchronization of Semi‐Markovian Jump Stochastic Complex Dynamical Networks with Time‐Varying Delays

“…However, for the sake of greater use of modern computer techniques, communication technology, and digital hardware systems, sampled-data feedback control is applied. Tis control plays a signifcant role in attaining low consumption, high reliability, and simple system deployment [24][25][26][27]. At certain instants, the introduction of suitable irregularities provides more benefts than classical sampling methods.…”