This article focuses on the dynamic quantized control for Takagi–Sugeno fuzzy semi-Markov jump systems (T–S FSMJSs) under fading channels and deception attacks, employing an improved event-triggered mechanism (ETM) strategy. Specifically, a more generalized semi-Markov process (SMP) that is governed by a higher-level deterministic switching signal (HLDSS) is addressed. A novel dynamic ETM is skillfully developed based on the information of quantization and two internal dynamic adjusting variables to further enhance the network bandwidth utilization. The dual asynchronous phenomenon between the plant and controller (asynchronous modes and mismatched premise variables) is addressed. This implies that the designed controller is not required to share the same membership functions and modes as the plant, establishing a more rational structure. The hidden semi-Markov model (HSMM) is attained to characterize the stochastic varying channel fading amplitudes. The Lyapunov function incorporating mode and fuzzy information is constructed to establish sufficient criteria ensuring the strictly dissipative performance and mean-square exponential stability (MSES) of the resulting closed-loop systems, and a new security fuzzy dual asynchronous controller is then developed. Finally, the efficacy and applicability of the results are demonstrated through numerical and practical examples.

This paper explores the dissipative fault detection filtering (FDF) issue for unmanned surface vehicles (USVs) within a network environment, considering switching channels and random occurrence of packet losses. Specifically, a multi-channel transmission mechanism is adopted to enhance the reliability of the system, and the switching channel is orchestrated by a Markov chain. The random intermittent data dropouts in each channel between the system and FDF modeled as a Bernoulli process are considered. Leveraging the Lyapunov theory and slack matrix technique, switching-channel-dependent FDF is crafted to detect faults for USVs and ensure that the augmented system keeps stochastic stability while attaining a strictly dissipative performance. Finally, an illustrative example is presented to validate the effectiveness of the proposed method for USVs.

This article investigates the dynamic-memory event-triggered (DMET)-based double asynchronous dissipative control issue for Takagi–Sugeno fuzzy semi-Markov jump systems (T-S FSMJSs) under redundant channel strategy. To mitigate the network burden and improve the system control performance, a new DMET mechanism is skillfully developed by adopting weighted past released packets of measured output and dynamically adjusted thresholds. Due to the impact of network environment, a novel framework of DMET-based controller scheme is constructed by considering the premise variable asynchronous and mode asynchronous phenomena between the plant and controller simultaneously. The imperfect premise matching and hidden semi-Markov model approaches are employed to resolve two types of mismatches. The redundant channel communication strategy with quantization measurement is used to improve the nonfragility of signal transmission. In terms of the stochastic theory and fuzzy model technique, some criteria are forwarded to ensure the stochastic stability and strict dissipative performance for closed-loop T-S FSMJSs. By the matrix decoupling method, the control scheme is established. Lastly, a single-link robot arm system example is presented to certify the effectiveness of the developed result.

This article is concerned with the security$\mathcal {H}_{\infty }$fuzzy control problem for Takagi–Sugeno (T–S) fuzzy semi-Markov switching systems (SMSSs) with event-based strategy and hybrid cyber-attacks. To efficiently use network resources and avoid unnecessary signal transmission, a new mode-dependent dynamic event-triggered mechanism (ETM), whose threshold parameter changes with varying states and modes is developed for each subsystem of fuzzy SMSSs. A more practical network environment subject to deception and denial-of-service (DoS) attacks is considered, and two Bernoulli distributed variables are adopted to characterize the randomly occurring hybrid attacks in a unified framework. By the mode-dependent Lyapunov function, sufficient conditions are attained to assure that the closed-loop system is stochastically stable with an$\mathcal {H}_{\infty }$attenuation performance. Finally, the validity and superiority of the proposed theoretical approach is demonstrated via its application to the Duffing–Van der Pols oscillator.

This paper studies the stability and$\mathscr{L}_{1}$-gain control of positive systems with Markov switching parameters and impulses. Markov process is applied to describe the switching parameters and structures. The positivity constraint, Markov stochastic processes and impulsive jumps are taken into account in a unified framework. By utilizing the stochastic co-positive Lyapunuov function, some new conditions on stochastic stability and$\mathscr{L}_{1}$-gain characterization of positive impulsive Markov switching systems (PIMSSs) are acquired. The stochastic stability and$\mathscr{L}_{1}$-gain characterization of the closed-loop systems can be ensured via the$\mathscr{L}_{1}$-gain mode-dependent state-feedback controller. Moreover, an example is presented to exhibit the usefulness of the obtained results.

In this study, the Takagi-Sugeno (T-S) fuzzy impulsive control problem is investigated for a class of nonlinear positive systems with time delay. The time delay under consideration is both in the continuous-time dynamics and at the impulsive instants, which can model practical systems more accurately. An impulse-time-dependent copositive Lyapunov function (IDCLF) is constructed, and the Razumikhin technique is adopted to develop conditions that ensure the globally exponential stability of T-S fuzzy positive systems with delayed impulses. The size constraint between the impulse delay and the bound of impulsive intervals is removed. A T-S fuzzy impulsive controller is designed in terms of the solutions to certain vector inequalities that are readily solvable. Numerical examples and a practical example of lipoprotein metabolism and potassium ion transfer model are given to demonstrate the effectiveness, advantages, and practicality of the proposed results.

This article focuses on the design problem of fault detection (FD) observer for a class of continuous-time nonlinear systems. The$\mathcal {H_{-}}$index is employed to measure the worst cast fault sensitivity. First, the nonlinear systems are represented by the Takagi–Sugeno (T–S) fuzzy dynamic models. Then, a novel fuzzy Lyapunov function (FLF) analyzing approach is proposed to reduce the conservatism in stability analysis and$\mathcal {H_{-}}$index estimation for the T–S fuzzy model. In particular, employing this new type of the FLF, the stability analysis of the T–S fuzzy systems perfectly overcomes the difficulty of evaluating the upper bound of the time derivative of the membership function. Based on the descriptor system approach, some new sufficient conditions on the existence of fuzzy FD observers are obtained in terms of linear matrix inequalities (LMIs). Finally, illustrative examples are given to show the effectiveness of the proposed method.

This study addresses the stability and L1-gain analysis for impulsive positive systems (IPSs). By constructing a discretized copositive Lyapunov function, a sufficient condition ensuring the asymptotic stability is established for IPSs under the range dwell time constraint. Based on the stability result, the L1-gain characterization is further analyzed. The obtained criteria can be checked by the linear programming method. The theoretical results obtained are demonstrated by a numerical example.