This article addresses the problem of resilient$H_\infty$control for direct-drive-wheel (DDW) systems by developing an adaptive hybrid-triggered (AHT) scheme that improves security and communication efficiency against hybrid cyberattacks. First, the attacked DDW system is modeled as a switched cyber-physical system (CPS) to effectively capture the impact of such attacks on signal transmission. Then, an attack-information-dependent AHT scheme is proposed, where triggering instants are determined by system states and attack information, and the adaptive threshold is tuned via a self-adaptive differential evolution (DE) algorithm to balance dynamic performance and communication frequency. By constructing a Lyapunov functional, sufficient conditions are derived to co-design the control gain and AHT parameters, ensuring global exponential stability and guaranteed$H_\infty$performance. Finally, the proposed method is validated on examples, showing its efficacy in maintaining system stability while considerably reducing communication overhead.

The stability and${\mathcal {H}}_\infty$filtering for delayed discrete-time T-S fuzzy systems are studied in this article. The primary objective is to obtain less conservative and more effective analysis and design methods by exploring a combination of the characteristics of T-S fuzzy systems and the delay-dependent methods. First, as the first step of the Lyapunov–Krasovskii functional (LKF) method, a membership-dependent (MD) LKF with delay-product-type term is established to contain more delay and membership function information. Then, to obtain the negative definite condition of the forward difference of the constructed functional, an MD-matrix-separation-based inequality is developed to obtain tighter estimations for the augmented summation terms and an MD-variable-augmented-based free-weighting matrix method is proposed to avoid the generation of delay-dependent nonlinear terms. Based on the abovementioned methods, a less conservative stability criterion and an${\mathcal {H}}_\infty$fuzzy filter design method are proposed. Finally, the merits of the proposed methods are verified via two examples.

This article is concerned with the stability and stabilization of delayed discrete-time T–S fuzzy systems. The purpose is to develop less conservative stability analysis and state-feedback controller design methods. First, a matrix-separation-based inequality is proposed, which can provide a tighter estimation for the augmented summation term. Then, by constructing a delay-product-type Lyapunov–Krasovskii functional, using the proposed inequality to estimate its forward difference and using a cubic functional negative-determination lemma to handle nonconvex conditions with respect to the delay, a delay and its variation-dependent stability criterion are obtained. Moreover, the corresponding controller design method for closed-loop delayed fuzzy systems is derived via parallel distributed compensation scheme. Finally, two examples are given to demonstrate the effectiveness and merits of the proposed approaches.