This article investigates the adaptive resilient flexible output containment (FOC) control problem for semi-Markov jump fully heterogeneous multiagent systems (FHMASs) under random switching topologies and denial-of-service (DoS) attacks. In contrast to most existing containment control results, the proposed control strategy can address the challenges posed by the full heterogeneity of multiagent systems (MASs), particularly when multiple leaders exhibit different system dynamics. To better reflect real-world MASs and communication networks, multiple asynchronous semi-Markov chains are employed for the first time to capture system parameter variations and communication topology switching, incorporating generally uncertain transition rates (TRs). In order to deal with this problem, a novel adaptive observer-based FOC control framework is developed. First, by introducing an adaptive gain, the adaptive resilient observers can observe leaders' states without prior knowledge of global topology information and TRs, while resisting the impacts of random switching topologies and DoS attacks. Then, a dynamic output feedback controller is designed to ensure the achievement of FOC. Notably, the containment coefficients in the controller design are no longer tied to the Laplacian matrix and can be flexibly predefined to align with specific task requirements. Furthermore, the linear matrix inequalities (LMIs) to obtain estimator gain matrices and controller gain matrices are derived for the case of generally uncertain TRs, respectively. Finally, the effectiveness of the theoretical method is demonstrated through the simulation.

This article proposes a novel fuzzy secure containment control strategy in an adaptive framework for fully heterogeneous nonlinear multi-agent systems (FHNMASs), which can resist the combined impacts of randomly switching topologies and denial-of-service (DoS) attacks. Unlike existing containment control protocols that rely on multiple leaders sharing the same system matrices, our approach is applicable to more general systems, where multiple leaders and followers are allowed to be equipped with non-identical system matrices and even state dimensions. The switching signal of communication graphs is regulated by the random Markov process, and the connectivity assumption is relaxed by merely requiring the union graph of possible subgraphs to be connected. Firstly, new adaptive observers are constructed, that can observe leaders' states without access to global topology information, even under randomly switching topologies and DoS attacks. Secondly, based on fuzzy logic systems and output regulation methods, fuzzy system state estimators are introduced to address challenges associated with unknown nonlinear functions and unmeasurable states of followers. Further, a new fuzzy controller is developed to guarantee the achievement of flexible secure output containment, where containment coefficients no longer depend on the Laplacian matrix and can be flexibly preset to accommodate various tasks. Finally, the theoretical algorithm is validated through simulation results.

This work proposes a memory fusion controller design methodology for sampled-data control of fractional-order (FO) systems with sliding memory window. Composed of finite-dimensional previous inputs, the devised controller is capable of handling hereditary effect and meanwhile enabling pseudo state to satisfy general integer-order (IO) discrete plant at sampling instants. Additionally, the asymptotical stability of controller and sampling error are further guaranteed. The developed fusion controller provides an "out-of-the-box" method for users who are not familiar with FO calculus and significantly facilitates the corresponding analysis. The above mentioned approach is thereafter employed in a more sophisticated case, that is, the coordination control of FO multiagent systems (MASs) subjects to intermittent sampled-data transmission. It is proved that the achievement of consensus only relates to the connectivity of communication graph. Numerical results are presented finally to substantiate the proposed control strategy.

This paper addresses the adaptive fuzzy faulttolerant output containment control of fully-heterogeneous nonlinear multi-agent systems (FHNMASs) subject to stochastic disturbances, where not only followers but also leaders are equipped with non-identical dynamics. Firstly, fully distributed fixed-time observers are designed to observe active leaders' information including system matrices, positions, and external inputs, which are only accessible to a limited group of followers. Subsequently, adaptive algorithms are utilized, informed by the observations of leaders' system matrices, to solve the regulator equations. Then, the state observer-based controller is proposed, which employs the adaptive fuzzy-based approximation law to approximate the unknown nonlinear item and integrates the adaptive gains to cope with the actuator faults in the follower's dynamics. Additionally, a set of modest conditions and rigorous proofs is constructed to guarantee the accomplishment of predetermined output containment through the output regulation method and Lyapunov stability theory. Finally, the theoretical analysis is validated through performing a numerical simulation.

This article aims to model and investigate the dynamical properties of a grid-connected permanent magnet synchronous motor (PMSM) in wind energy conversion systems (WECSs). Considering the dc-link capacitor in voltage equations of PMSM can cause hyperchaotic solution behavior, whereas the conventional PMSM model exhibits chaotic solutions. In addition, disturbances are inevitable in WECS hence in this study the aerodynamics of PMSM is considered as stochastic disturbances that can degrade the performance of the WECSs. As a result, grid-connected PMSM is modeled as stochastic differential equations with nonlinear characteristics. Due to nonlinearity, investigating the stability properties of PMSM with dc-link is economically expensive. In this regard, an equivalent Takagi–Sugeno (T–S) fuzzy model can be derived to mimic the dynamical characteristics of the stochastic PMSM model with the help of fuzzy membership grades. Overall this study focuses on designing a suitable control algorithm that guarantees the global stable performance of T–S-based linear hyperchaotic PMSM model involving stochastic disturbances. Among various controllers, an event-triggered-based sampled-data control scheme with continuous-type network transmission delay is considered to be effective for the proposed model with disturbances. Theoretically, the Lyapunov stability theory is employed to derive sufficient stability conditions in terms of solvable linear matrix inequalities. Technically, the numerical simulations are performed with the experimental range of parameter values to validate the effectiveness of the proposed theoretical frameworks.

In this article, we establish an experience-correction (E-C) framework to deal with sampled-data fractional-order systems in the manner of general integer-order discrete-time model at sampling instants by coping with the memory effect. The designed E-C controller can be partitioned into local input and history input, respectively. Generated by current sampling, the local input is in a sense analogous to the input of integer-order system. In particular, the history input can correct all previous experience via incorporating earlier local inputs. Emphasize that the weights of earlier local inputs, norm of E-C controller together with corresponding sampling error are proved to descend to origin no slower than the Pareto function, i.e.,$\mathcal {O}(t^{-\alpha })$, where$\alpha $represents the derivative’s order. Similar to the well-known forgetting curve, we witness a rapid decline in the proportion of earlier past in E-C controller, which is with respect to one of the memory failures: transience, the deterioration of memory with the passage of time. The closer the order$\alpha $is to 1, the faster the forgetting is. The above analysis accounts for a phenomenon not previously understood: well-performed simulation results could still be expected in existing research who ignored memory effect and only considered local input. This is owing to the fractional orders are usually hypothesized to be larger than 0.5 and thus the weight of earlier past decays sharply over time. Furthermore, both absolute and proportional decline of earlier past’s weight will slow down when time goes by, which is consistent with memory consolidation and Jost’s law in psychology. Overall, the E-C method keeps an elegant formulation which theoretically describes the evolution of hereditary effect. Meanwhile, it is also suitable for first-order systems. Thereafter, we address related applications in fractional-order multiagent systems (MASs) subject to intermittent sampled-data communication. Numerical simulations are provided finally to substantiate the effectiveness of theoretical results.

This article deals with the fully distributed dual-terminal dynamic event-triggered bipartite output containment control of heterogeneous linear multiagent systems (HLMASs) subject to actuator faults. First, a class of fully distributed dynamic event-triggered observers is proposed over the directed signed communication network for each follower to estimate the leaders’ system matrices and (symmetric) combination states, which are merely available to a small fraction of followers. Then, based on the estimations of leaders’ system matrices, adaptive algorithms are employed to solve the regulator equations. Furthermore, the fully distributed observer-based dynamic event-triggered controllers are proposed by integrating the adaptive gains to compensate for actuator faults. Dual-terminal dynamic event-triggered mechanisms (ETMs) are addressed to exclude not only continuous control updates but also continuous communication among agents. Correspondingly, some mild criteria and the rigorous proofs are established to ensure the implementation of bipartite output containment through the Lyapunov stability theory. Moreover, the strictly positive lower bounds of intervals between two adjacent event-triggered time instants are derived, which indicates that Zeno behavior is ruled out in the dual-terminal dynamic ETMs. Finally, numerical simulations are performed to demonstrate the theoretical analysis.

The fully distributed consensus tracking of stochastic nonlinear multiagent systems (MASs) is investigated with Markovian switching topologies and intermittent control strategy, where the dynamics of agents are depicted by Itô differential equations and the leader’s information is just known for a fraction of followers. The switching mechanism of interaction topologies is modeled as a Markov process. A novel class of fully distributed control protocols is proposed via intermittent control method, which is only associated with the relative state measurements of neighbors and does not involve any global information. Meanwhile, the control gains are designed to be intermittently adaptive, which can effectively reduce energy consumption and avoid the gains being larger than those needed in practice. Several sufficient conditions and corresponding proofs are provided by using the Lyapunov stability theory. Finally, numerical simulation is presented to state the feasibility of the theoretical results.

This paper investigates the controllability problem for controlled switching linear systems. Causal manipulations on the bond graph models are carried out in order to determine graphically the controllable state subspaces. Graphical conditions are derived by using these controllable state subspaces.

Multipath routing scheme for load balancing consists in two steps: selection of multiple candidate paths and splitting the traffic among selected paths. New traffic splitting scheme is proposed using prospect of the effective repartition and three hybrid multipath algorithms are organized by combining each step of LDM (load distribution over MPLS network) and WDP (widest disjoint path) selected among the existing schemes, and proposed new traffic splitting algorithm. For performance estimation, we have simulated some existing routing algorithms using ns-2 and have compared their results with three hybrids' results in terms of maximum link utilization ratio. The results show that three hybrid algorithms, especially LBWDP with our new traffic splitting scheme, surpasses the others as the number of demands grows.