This study aims to explore the stabilization problem of state-based fuzzy switched dynamic systems with Lévy noise, non-differentiable delay and actuator saturation through a novel intermittent output feedback control mechanism. Firstly, the delay studied in this study is non-differentiable, eliminating the harsh condition that the delay in the existing conventional system must be differentiable or even require the derivative to be less than 1, and replacing the existing common Brownian motion with Lévy noise that is more realistic to simulate the inevitable stochastic noise in the system, which has more theoretical research significance and exploration value. Subsequently, by means of dynamic output feedback mechanism, a new intermittent output feedback control scheme is designed to replace the conventional intermittent state feedback control scheme, which has important practicability and flexibility in practical control. Especially, a novel stabilization criterion is developed by selecting a novel switching-Lyapunov function in combination with two novel lemma pairs for solving non-differentiable terms and actuator saturation. Furthermore, two additional algorithms are given to maximize the attraction domain of the closed-loop system and to minimize the control gain matrix in order to minimize the control cost. Finally, a numerical example is used to verify the validity of the developed results, and a meaningful additional practical electronic circuit model is provided to prove its practicability and superiority.

Different from continuous-time or discrete-time (CoD-T) systems, time scale-type systems (TTSs) can operate in a continuous-discrete mode, bridging the gap between continuous and discrete states. As a result, conventional methods such as the average impulsive interval (AII) and the impulsive density function (IDF) are not suitable for characterizing the frequency of impulses (FoI) required for stability analysis of TTSs with impulses. This is due to the possibility that all impulses may fall into the complementary set of time scales. In light of this, the number of impulses satisfying AII or IDF may not be sufficient to ensure stability. In response to this challenge, we introduce a novel definition in this paper, termed time scale-type impulsive density (TTID). The key feature of TTID lies in the consideration of the graininess function, which is determined by time scales, allowing for a more accurate characterization of the number of impulses required for the stability of the TTSs. Employing the proposed TTID, the criteria of asymptotical stability are presented for TTSs with stochastic and Markov-type impulses, respectively. The results presented in this paper encompass and generalize the discoveries of some existing CoD-T impulsive systems, which can be regarded as special cases of our results. We shed new light on the advantages of the TTID and the effectiveness of the theoretical results by an application of voltage control for micro-grids.

The event-triggered almost global attitude consensus problem is considered in this article for multiple rigid body systems with prescribed performance. Two kinds of attitude consensus protocols using axis-angle vectors are proposed at the kinematic level with different prescribed performance constraints. The first protocol aims to achieve the event-triggered attitude consensus almost globally under jointly connected graphs. Based on a prescribed performance function with local states, the configuration space of parameterized attitude representations is shown to be positively invariant which almost globally covers . The second protocol is designed to reach attitude consensus with the prescribed transient behavior guaranteed in the event-triggered setting. By defining a prescribed performance function using the metric on axis-angle spaces, a dynamic event-triggered framework is designed to ensure both the attitude geometric topology constraint and prescribed convergence performance. Finally, numerical results are given to show the validness of the two control protocols.

This article tackles the sampled-data control issue for a class of time-scale-type systems (TSTSs) subject to denial-of-service (DoS) attacks. A novel sampled-data control protocol, that incorporate the backward-jump-like operator (BJLO), is proposed to ensure compatibility with the discontinuity of time scales. Furthermore, a generalized Halanay-like inequality (GHLI) is proposed to address the effects of time scale discontinuities and DoS attacks on sampling intervals. Compared with the common Halanay inequality (CHI) used in continuous-time sampled-data systems, the GHLI accommodates TSTSs and permits some sampling intervals that exceed the constraints of the CHI. By leveraging the GHLI and the proposed sampled-data control protocol, the exponential stability criterion is derived for TSTSs under DoS attacks. This article culminates with two simulation examples and the micro-grid case study conducted to validate the proposed results.

This article investigates the almost sure consensus (ASC) problem for sampled-data multiagent systems (MASs) operating over semi-Markov switching networks (SMSNs) and facing different types of denial-of-service (DoS) attacks. During real-time information exchange among agents, communication failures between agents occur randomly, which may result in each possible network topology occurring with a certain probability, and its sojourn time is also stochastic. This necessitates the consideration of a more general switching signal to describe the stochastic switching phenomenon of networks. In pursuit of this goal, a semi-Markov chain is introduced to characterize the switching signal of stochastic interaction networks, whose sojourn time distribution allows for arbitrary continuous-time distribution and depends on the current and next state. Additionally, this article delves into the impact of two distinct types of DoS attacks on MASs. The first type involves random DoS attacks, which are also modeled by a semi-Markov chain to capture the stochastic nature of attack durations. The second type is deterministic DoS attacks, characterized by their frequency and duration. The proposed new stochastic analysis method, based on the law of large numbers, is used to analyze the ASC for MASs featuring SMSNs under the DoS attacks. The effectiveness of the proposed approach is demonstrated by evaluating the results obtained from two illustrative numerical examples.

The linear quadratic (LQ) optimal control problem with indefinite weighting matrices and the stabilization problem for discrete-time descriptor stochastic Markov jump systems (DSMJSs) involving state-dependent noises are studied. By using the Moore-Penrose generalized inverse of matrices and the equivalent transformation of restricted system, the indefinite LQ problem for DSMJSs is equivalently converted into the indefinite LQ problem for Markov jump systems (MJSs). Under some viable conditions and stabilization assumption, the generalized stochastic algebraic Riccati equation having a unique semi-positive definite solution is guaranteed. Then the necessary and sufficient conditions which ensure that DSMJSs are causal and mean-square stable are established. It is shown that the admissibility of the optimal closed-loop systems is equivalent to stabilizability in mean-square sense of the transformed MJSs. Besides, an efficient iterative algorithm is given to verify the mean-square stabilizability of DSMJSs by solving an optimization problem. Two examples including a practical RLC circuit system are presented as verifications of the theoretical results.

This article addresses the distributed cooperative protocol for nonlinear agents with the aim of attaining the optimal leader-following consensus. The main challenges encountered when deriving the cooperative optimal protocol are caused due to the conservatism of Lipschitz nonlinear dynamics, uncertainties, disturbances, and coupling of agents. Until now, the consensus optimal protocols for Lipschitz nonlinear agents are provided in the existing literature, which is conservative and has limited applications. To tackle these issues, a cooperative protocol is provided for intelligent nonlinear systems that are optimal for the performance index and robust against uncertainties and disturbances. The performance index of the optimal protocol depends on the Lipschitz nonlinearities is converted into linear parameter-varying (LPV) form. The LPV approach reduces the conservatism of the existing methods for Lipschitz nonlinearities that improves the scope of the design approach and is applicable to practical applications of nonlinear multiagents. The optimal solution is obtained by solving the algebraic Riccati equation. The proposed optimal scheme increases the region of the feasibility of the Lipschitz constant by extracting precise information about nonlinearities. Moreover, a robust cooperative optimal protocol is designed that has ensured optimal consensus for the nonlinear agents and eliminated the negative effects of parameter uncertainties and disturbances. Finally, the results are verified through a simulation example of multiple nonlinear robotic manipulators.

In this article, based on the classical Degroot and Friedkin–Johnsen model, two opinion dynamics models with antagonistic relationship and multiple interdependent topics are proposed. The proposed models aim to characterize the evolution of individual opinions when individuals in a signed social network are able to discuss multiple interdependent topics simultaneously. Considering that different individuals may have different perceptions of the same thing, a set of heterogeneous logical matrices is used to represent the logical interdependence between different topics. In Model I with time-varying topologies, both the structurally balanced and unbalanced network topologies are investigated. Some sufficient conditions for the modulus consensus about topics are obtained in our study. About Model II with the stubborn individuals, we rigorously concentrate on its convergence and stability for the structurally balanced and unbalanced social networks. And some conditions on the convergence and stability are obtained. All the obtained conditions depend on the network topology and logical matrices and fully show how the network topology and logical matrices influence the evolution of opinions. Finally, two examples are used to verify our results.

This paper is concerned with pth moment exponential stability of stochastic delayed neural networks. By using the Lyapunov function method, some stability criteria of impulsive stochastic delayed systems are obtained, and these results are applied to the study on the stability criteria of stochastic delayed neural networks. It is shown that if the continuous stochastic delayed neural network is stable and the impulsive effects are destabilizing, then the stochastic delayed neural network is exponentially stable with respect to a lower bound of the impulsive interval. Moreover, if the continuous stochastic delayed neural network is not stable, the impulsive effects can successfully stabilize the delayed neural network for a given upper bound of the impulsive interval. One example is presented to demonstrate the usefulness of the proposed results.

In this paper, the distributed exponential consensus of stochastic delayed multi-agent systems with nonlinear dynamics is investigated under asynchronous switching. The asynchronous switching considered here is to account for the time of identifying the active modes of multi-agent systems. After receipt of confirmation of mode's switching, the matched controller can be applied, which means that the switching time of the matched controller in each node usually lags behind that of system switching. In order to handle the coexistence of switched signals and stochastic disturbances, a comparison principle of stochastic switched delayed systems is first proved. By means of this extended comparison principle, several easy to verified conditions for the existence of an asynchronously switched distributed controller are derived such that stochastic delayed multi-agent systems with asynchronous switching and nonlinear dynamics can achieve global exponential consensus. Two examples are given to illustrate the effectiveness of the proposed method.