The problem of dissipative stabilization for a class of T-S fuzzy systems (TSFS) is studied by generalized memory sampled-data control (SDC). A novel Lyapunov–Krasovskii functional (LKF) is developed, which extends existing looped-functional approaches by integrating augmented terms, triple integral functionals, and, notably, membership function information of the fuzzy system. This enables the LKF to more accurately capture sampling pattern characteristics, thereby reducing conservatism and enhancing dissipative performance of the closed-loop system. Based on a switching strategy and generalized free-matrix-based integral inequality (GFMBII), new criteria are established to ensure asymptotic stability and strict(Q,S,R)-ρ-dissipativity of the resulting fuzzy sampled-data system. Furthermore, the generalized SDC is specifically designed to ensure dissipativity of the considered system. Finally, the obtained dissipative criterion is applied to the truck-trailer system to verify the effectiveness and superiority of the proposed method.

This article is concerned with the stochastic finite-timeL1control problem of multi-loop networked control systems (NCSs) with network-induced delay, random packet loss, and external interference. Firstly, considering the data processing mode jumping, data transmission channel switching, and positive total amount of data, the multi-loop NCSs with network-induced delay, random packet loss, and external interference are modeled as a more general class of variable dual switching positive time-delay systems (VDSPTDSs) for the first time. Secondly, a new scheduling strategy that fully considers the random packet loss and the total amount of data, named positive minimum state expectation (PMSE), is proposed. Under this scheduling strategy, the channel with the smaller expectation of the total amount of data is selected to reduce the communication overhead. Subsequently, a stochastic multiple co-positive Lyapunov-Krasovskii functional (SMCPLKF) is constructed to establish the criteria of stochastic finite-time bounded (SFTB) and finite-timeL1-gain performance. A mode-dependent finite-timeL1-gain state feedback controller is further designed such that the closed-loop VDSPTDSs are positive and SFTB withL1-gain characterization. Finally, a multi-loop data communication NCS model is given to demonstrate the validity and generality of the proposed methods.

This work studies the average Age of Information (AoI) of a remote monitoring setup in which a multi-sensor system observes independent sources and updates the status to a common monitor using orthogonal channels. Considering the limited buffer size at the sensors, we first model each sensor as a first-come-first-served M/M/1/1 queue. Leveraging tools from stochastic hybrid systems, we derive the average AoI of a homogeneous single-source multi-sensor system in which all sensors’ arrival and service rates are the same. We then extend the results to the multi-source, multi-sensor system. For a multi-source dual-sensor system, we present an approximate optimal arrival rate for a given sum arrival rate at a light load. For heterogeneous cases with different arrival and service rates at sensors, the average AoI is derived for the single-source dual-sensor and more general multi-source systems. Our analysis shows that the average AoI decreases by 16.44% and 21.44% for the dual-sensor and three-sensor systems, respectively, compared to the single-sensor system when the service rate and the total arrival rate of the sensors are normalized. Numerical results confirm that the average AoI performance of the single-source dual-sensor system outperforms the M/M/2 system at high system load.

The stability and stabilization problems for T–S fuzzy systems with a periodic variable delay are analyzed in this article. First, an improved delay-dependent reciprocally convex inequality is presented to deal with the periodic variable delay, which contains some existing results. Second, according to the monotonicity of the delay interval, the interval of each period is divided into a monotonically increasing interval and a monotonically decreasing interval, and different looped functionals are constructed on the two intervals. A new monotone delay-interval-based functional is presented to introduce more delay information and system state information on the basis of augmented functional and looped functional methods. Then, a generalized memory controller is designed to assure robust stabilization of the system by considering the variable delay and its bounds, which is more general than conventional controllers. Finally, some examples are shown to elaborate on the feasibility and validity of the obtained results.

This work studies the average Age of Information (AoI) of a remote monitoring system in which two sensors observe the same physical process and update the status to a common monitor using orthogonal channels. While using redundant devices to update the status of a process can improve the information timeliness at the monitor, the out-of-order arrivals of updates impose a challenge to the AoI analysis. We first model the system as two parallel M/M/1/1 queues. By leveraging tools from stochastic hybrid systems, we obtain analytically the average AoI of the system. In particular, when the arrival or service rates are the same for the two sensors, the average AoI is given in closed form. Our analysis reveals that the average AoI of the considered system is reduced by 16.44% compared to the single-sensor system when the arrival and service rates are equal to 1. Numerical results show that the considered system outperforms the M/M/2 system in average AoI at high arrival rates.