The finite-time output consensus (FTOC) issue of heterogeneous fractional-order multiagent systems (HFO-MASs) is investigated in this article. First, a new principle of finite-time convergence for absolutely continuous functions is developed if a fractional derivative inequality is satisfied. Next, in order to remove the assumption that the leader's system matrix is known to all agents in previous studies, a distributed adaptive finite-time observer is designed, which can estimate not only the leader's state but also the leader's system matrix. Then, a novel finite-time event-triggered compensator with intermittent communication is constructed to estimate the leader's state by introducing a dynamic threshold for a novel triggering function. In this case, the high frequency triggering is restrained and the triggering number is significantly reduced. The Zeno behavior does not exist by choosing parameters appropriately. In addition, two finite-time control strategies are constructed based on the above distributed observer and event-triggered compensator, respectively, to achieve output consensus in finite time. The feasibility of the proposed method is ensured by the comprehensive theoretical demonstration of the finite-time consensus stability and the analysis of the Zeno behavior. Finally, the examples are given to demonstrate the conclusion.

This study investigates the adaptive bipartite event-triggered time-varying output formation tracking for heterogeneous linear multi-agent systems (MASs) under signed directed communication topology. Both cooperative communication and antagonistic communication among agents are considered. The fully distributed bipartite compensator based on the novel composite event-triggered transmission mechanism is first put forward to estimate the state of the leader. Compared with the existing methods, our compensator can save communication resources using event-triggered transmission mechanism; is independent of the global information of the network graph; and is applicable for the signed directed graph. With the developed compensator, the distributed control protocol is designed to achieve the time-varying output formation tracking. Moreover, the case that the networked systems subject to external disturbances is also considered. To estimate the state of leader with disturbance, the fully distributed bipartite compensator based on an innovative composite event-triggered mechanism is presented. And the novel distributed control protocol is proposed to address the output formation tracking issue for linear MASs with heterogeneous dynamics and external disturbances. It is shown that the Zeno-behavior can be excluded in both transmission mechanisms. Finally, the effectiveness of the developed control methods is illustrated through three simulation examples.

This article considers the bipartite time-varying output formation-containment tracking control issue for general linear heterogeneous multiagent systems with multiple nonautonomous leaders, where the full states of agents are not available. Both cooperative interaction and antagonistic interaction between neighboring agents are taken into account. First, an observer is constructed using the output information to observe the state information. Then, based on the information between neighboring agents, an independent asynchronous fully distributed event-triggered bipartite compensator is put forward to estimate the convex hull spanned by the states of multiple leaders. Note that the compensator does not require to use of any global information. Subsequently, a formation-containment tracking control strategy based on the observer and compensator and an algorithm to determine its control parameters are given. The Zeno behavior is further proved to be excluded in any finite time. In addition, a novel self-triggered control strategy based only on the sampled information at triggering instants is also formulated, which avoids continuous communication among agents. Finally, a numerical example is given to validate the effectiveness and performance of the proposed control strategies.

This article focuses on the adaptive bipartite containment control problem for the nonaffine fractional-order multi-agent systems (FOMASs) with disturbances and completely unknown high-order dynamics. Different from the existing finite-time theory of fractional-order system, a lemma is developed that can be applied to actualize the aim of finite-time bipartite containment for the considered FOMASs, in which the settling time and convergence accuracy can be estimated. Via applying the mean-value theorem, the difficulty of the controller design generated by the nonaffine nonlinear term is overcome. A neural network (NN) is employed to approximate the ideal input signal instead of the unknown nonaffine function, then a distributed adaptive NN bipartite containment control for the FOMASs is developed under the backstepping structure. It can be proved that the bipartite containment error under the proposed control scheme can achieve finite-time convergence even though the follower agents are subjected to completely unknown dynamic and disturbances. Finally, the feasibility and validity of the obtained results are exhibited by the simulation examples.

This article discusses the fault estimation (FE) problem of nonlinear fractional-order (FO) systems subject to faults and unknown inputs through the T–S fuzzy approach. A novel fuzzy FO unknown input observer is well synthesized to not only achieve the desired FE but also decouple the unknown input in contrast to the traditional integer-order observer design technique. It is worth pointing out that the provided FE scheme can reconstruct the fault signal appearing in both input and output equations simultaneously. Furthermore, by resorting to linear matrix inequalities, the stability criteria of observation error dynamics are first formulated based on general quadratic Lyapunov functions, which are further extended via fuzzy Lyapunov functions containing the information of membership functions. Finally, the performance of theoretical results is verified through two elaborate examples.

In this article, we pay our attention on exploring observer-based actuator fault and sensor fault reconstruction associated with fault-tolerant control (FTC) for nonlinear systems, which are approximated by the Takagi–Sugeno (T-S) fuzzy method. By designing a brand-new unknown input observer (UIO), unknown state, sensor, and actuator faults can be reconstructed simultaneously, where some constraints imposed on the actuator fault such as the first derivative of fault being equal to zero required in the previous results are not needed in our work. With the support of this estimation information, a FTC scheme is well established, by which the system may recover its performance even in the occurrence of faults. Another contribution of the developed method is that all the stability criteria are deduced via fuzzy Lyapunov functions. It makes the obtained conditions more relaxed than the ones derived by quadratic Lyapunov functions. Finally, simulation results conducted on two practical dynamics are provided to show the validity of the achieved procedure.

This study investigates the bipartite fixed-time time-varying output formation-containment tracking issue for heterogeneous linear multiagent systems with multiple leaders. Both cooperative communication and antagonistic communication between neighbor agents are taken into account. First, the bipartite fixed-time compensator is put forward to estimate the convex hull of leaders' states. Different from the existing techniques, the proposed compensator has the following three highlights: 1) it is continuous without involving the sign function, and thus, the chattering phenomenon can be avoided; 2) its estimation can be achieved within a fixed time; and 3) the communication between neighbors can not only be cooperative but also be antagonistic. Note that the proposed compensator is dependent on the global information of network topology. To deal with this issue, the fully distributed adaptive bipartite fixed-time compensator is further proposed. It can estimate not only the convex hull of leaders' states but also the leaders' system matrices. Based on the proposed compensators, the distributed controllers are then developed such that the bipartite time-varying output formation-containment tracking can be achieved within a fixed time. Finally, two examples are given to illustrate the feasibility of the main theoretical findings.

In this article, the leader-following exponential consensus problem of fractional-order descriptor multiagent systems (FOD-MASs) with event-triggered control (ETC) protocol is investigated, which includes integer-order descriptor multiagent systems as the special case. Two classes of control schemes and the corresponding event-triggered conditions are presented, respectively. First, a distributed state feedback ETC protocol is developed to reach the leader-following exponential consensus. The leader-following exponential consensus is achieved in the sense of the Mittag-Leffler stability of fractional-order systems. Second, when full-state measurements are not available, a novel observer-type output feedback ETC strategy with some desirable characteristics is provided. For two distributed ETC protocols, consensus conditions are derived and convergence rate of the system can be adjusted. Also, the integral inequality is applied to get the fact that Zeno behavior is excluded, which verifies the feasibility of ETC schemes. Finally, the effectiveness of conclusions is demonstrated by the examples.

In this article, the bipartite fixed-time output consensus problem of heterogeneous linear multiagent systems (MASs) is investigated. First, a distributed bipartite fixed-time observer is proposed, by which the follower can estimate the leader's state. The estimate value is the same as the leader's state in modulus but may not in sign due to the existence of antagonistic interactions between agents. Then, an adaptive bipartite fixed-time observer is further proposed. It is fully distributed without involving any global information. This adaptive bipartite fixed-time observer can estimate not only the leader's system matrix but also the leader's state. Next, distributed nonlinear control laws are developed based on two observers, respectively, such that the bipartite fixed-time output consensus of heterogeneous linear MASs can be achieved. Moreover, the upper bound of the settling time is independent of initial states of agents. Finally, the examples are given to demonstrate the results.

A novel multiscale topomorphologic approach for opening of two isointensity objects fused at different locations and scales is presented and applied to separating arterial and venous trees in 3-D pulmonary multidetector X-ray computed tomography (CT) images. Initialized with seeds, the two isointensity objects (arteries and veins) grow iteratively while maintaining their spatial exclusiveness and eventually form two mutually disjoint objects at convergence. The method is intended to solve the following two fundamental challenges: how to find local size of morphological operators and how to trace continuity of locally separated regions. These challenges are met by combining fuzzy distance transform (FDT), a morphologic feature with a topologic fuzzy connectivity, and a new morphological reconstruction step to iteratively open finer and finer details starting at large scales and progressing toward smaller scales. The method employs efficient user intervention at locations where local morphological separability assumption does not hold due to imaging ambiguities or any other reason. The approach has been validated on mathematically generated tubular objects and applied to clinical pulmonary noncontrast CT data for separating arteries and veins. The tradeoff between accuracy and the required user intervention for the method has been quantitatively examined by comparing with manual outlining. The experimental study, based on a blind seed selection strategy, has demonstrated that above 95% accuracy may be achieved using 25-40 seeds for each of arteries and veins. Our method is very promising for semiautomated separation of arteries and veins in pulmonary CT images even when there is no object-specific intensity variation at conjoining locations.