This article investigates the fully distributed output feedback consensus-tracking control problem for multiple wheeled mobile robots (multi-WMRs) subject to dual-actuator faults (DAFs) under the directed graph. First, a fully distributed estimator is designed to asymptotically estimate the leader's states with nonzero input under event-triggered communication. Next, novel filters are introduced to compensate for unmeasured velocity information in the presence of DAF, and output feedback fault-tolerant controllers are developed to ensure asymptotic consensus tracking despite the faults of actuators. Each robot in the considered multi-WMR system is equipped with two controllers that are co-designed in a unified framework. The final control laws are obtained by solving a set of equations, for which the existence of a unique solution is rigorously established. The proposed scheme not only enables output feedback control under partial loss-of-effectiveness (PLOE) faults in dual actuators, but also ensures fully distributed consensus tracking with event-triggered communication. The simulation results validate the effectiveness of the proposed approach.

This paper presents an output feedback prescribed performance control method for a class of high-order nonlinear uncertain multiagent systems. General prescribed performance consensus control for multiagent systems requires that the initial consensus error is constraining within a boundary value. Unlike existing works, the conservative condition of prescribed performance consensus control for multiagent systems is relaxed as the consensus error is independent of the initial state. In this condition, we employ a control scheme with improved prescribed performance to constraint the transient behavior of the system. By designing reduce order dynamic gain K-filter, the state variables of the systems are reconstructed. Based on the baskstepping method and dynamic surface control technology, we introduce an innovative prescribed performance event-triggered approach aimed at ensuring prescribed performance levels for both transient and steady-state aspects of consensus control and reducing the communication bandwidth resource. Furthermore, we rigorously demonstrated through the Lyapunov function that all agents can achieve consensus with the leader driven by the controller. The simulation results have demonstrated the effective tracking performance of the developed control approach. Finally, the effectiveness and reliability of the proposed control strategy are verified through the successful execution of multi-QUAVs formation encirclement control.Note to Practitioners—This paper considers output feedback prescribed performance consensus control problem of multiagent systems, which can be applied to some practical systems, e.g., low-altitude formation flight of autonomous aerial vehicle with specified transient performance, multi underwater robot for oil field line-cruising, etc. Furthermore, in harsh working environments, the states of agent devices are difficult to measure or cannot be measured. Hence the control objective in these applications can be transformed into output feedback prescribed performance consensus control problem of multiagent systems. Besides, in military applications, high-speed aircraft need to fly at a certain height above the ground in order to avoid radar detection, which poses strong limitations on the position of the aircraft. This challenging issue can be well addressed through prescribed performance control. Compared with the existing results, this paper proposed a novel prescribed performance control strategy for multiagent systems with unrestricted initial state. It should be noted that in practical applications, communication bandwidth resources are extremely limited, so we propose event triggered control to effectively alleviate the communication pressure of multiagent system cooperative control. The nonlinear high-order system model studied in this article can be converted into a Lagrangian system, multi-complexity manipulator system and an autonomous aerial vehicle system, which has strong engineering practical significance.

This paper focuses on output feedback prescribed-time control problem of nonlinear system subject to bounded disturbance. Firstly, in order to observe and deal with unmeasurable states and disturbances, the prescribed-time observer and filter are constructed. The prescribed-time state stabilization problem of the original system is translated into how to design the controller to make the state of filter stable in a predetermined time. Then, to overcome the effect of unknown disturbance during the design process, a novel switched prescribed-time high-order sliding mode (HOSM) is constructed. The output feedback prescribed-time control scheme is presented in conjunction with the proposed prescribed-time HOSM to guarantee the prescribed-time stability of system. Finally, the effectiveness of the main result is demonstrated through two numerical simulations, a third order nonlinear system and the single-link robot system.

This article presents an adaptive fuzzy output-feedback control method for a class of nonlinear time-delay systems with prescribed tracking performance. Based on proper tuning functions and a pair of monotone tube boundary functions, a novel error transformation is proposed, which can constrain the tracking error within predefined monotone tube boundaries provided that the transferred variable is bounded. To this end, an adaptive output-feedback controller is designed to stabilize the transferred variable. We use fuzzy logic systems and adaptive control techniques to approximate the unknown nonlinear functions, and a reduced-order observer with less dynamics is proposed to estimate the unmeasurable state. In order to reduce the computation burden, we adopt command-filters method, which can avoid the complexity explosion problem in backstepping controller design procedure. Our article presents a way to constrain the tracking error with improved performance indices, such as overshoot, and convergence time. In addition, the method is independent of the initial values. Numerical simulations are given to verify the effectiveness of the proposed approach.

This article investigates the distributed leader-following consensus for a class of nonlinear stochastic multiagent systems (MASs) under directed communication topology. In order to estimate unmeasured system states, a dynamic gain filter is designed for each control input with reduced filtering variables. Then, a novel reference generator is proposed, which plays a key role in relaxing the restriction on communication topology. Based on the reference generators and filters, a distributed output feedback consensus protocol is proposed by a recursive control design approach, which incorporates adaptive radial basis function (RBF) neural networks to approximate the unknown parameters and functions. Compared with existing works on stochastic MASs, the proposed approach can significantly reduce the number of dynamic variables in filters. Furthermore, the agents considered in this article are quite general with multiple uncertain/unmatched inputs and stochastic disturbance. Finally, a simulation example is given to demonstrate the effectiveness of our results.

This article considers the prescribed performance tracking problem for a class of nonlinear interconnected time-delay systems, in which system states are unavailable and each subsystem is subject to unmodeled dynamics. Based on a novel performance function, the effect of initial values is eliminated in the prescribed performance method and the dynamic surface control method is employed to avoids the complexity explosion problem. With the reduced-order observer and fuzzy logic system, decentralized adaptive fuzzy output feedback control approach is proposed and the output feedback control strategy is further explored concerning global tracking performance constraint provided that the nonlinear time-delay functions are known or satisfy other mild assumptions. A numerical simulation is provided to substantiate our method.

This article studies the distributed adaptive failures compensation output-feedback consensus for a class of nonlinear multiagent systems (MASs) with multiactuator failures allowing unmatched redundancy under directed switching graphs. With estimated information of neighbors, a novel distributed reference generator is designed. To compensate the unmeasured state variables of each agent, a reduced-order dynamic gain filter is constructed. Based on the generator and filter, and using the recursive design method, a distributed adaptive protocol is designed, where the adaptive technique is used to compensate the actuator failures. The proposed scheme can significantly relax conditions on the communication graph, which allows the graph to be disconnected at any time instant. The number of introduced variables in the filter and its dimension is greatly reduced and, thus, reduces the numerical challenge. The output-feedback consensus for nonlinear MASs with actuator failures and possible unmatched actuator redundancy is addressed for the first time. The consensus error can converge to an arbitrarily small set not affected by actuator failures, and the resulting closed-loop system is semiglobally stable. Finally, simulation results are given to illustrate the effectiveness of the proposed method.

In this article, we consider the input-to-state stability (ISS) problem for a class of time-delay systems with intermittent large delays, which may cause the invalidation of traditional delay-dependent stability criteria. The topic of this article features that it proposes a novel kind of stability criterion for time-delay systems, which is delay dependent if the time delay is smaller than a prescribed allowable size. While if the time delay is larger than the allowable size, the ISS can be preserved as well provided that the large-delay periods satisfy the kind of duration condition. Different from existing results on similar topics, we present the main result based on a unified Lyapunov-Krasovskii function (LKF). In this way, the frequency restriction can be removed and the analysis complexity can be simplified. A numerical example is provided to verify the proposed results.

In this article, we consider the load frequency control problem for a class of power systems based on the dynamic event-triggered control (ETC) approach. The transmission networks are unreliable in the sense that malicious denial-of-service (DoS) attacks may arise in the power system. First, a model-based feedback controller is designed, which utilizes estimated states, and thus can compensate the error between plant states and the feedback data. Then, a dynamic event-triggered mechanism (DETM) is proposed by introducing an internal dynamic variable and a timer variable with jump dynamics. The proposed (DETM) can exclude Zeno behavior by regularizing a prescribed strictly positive triggering interval. Incorporated in the ETC scheme, a novel hybrid model is established to describe the flow and jump dynamics of the power system in the presence of DoS attacks. Based on the hybrid dynamic ETC scheme, the power system stability can be preserved if the attacks frequency and duration sustain within an explicit range. In addition, the explicit range is further maximized based on the measurement trigger-resetting property. Finally, a numerical example is presented to show the effectiveness of our results.

In this article, the output-feedback tracking control problem is considered for a class of nonlinear time-delay systems in a strict-feedback form. Based on a state observer with reduced order, a novel output-feedback control scheme is proposed using the backstepping approach, which is able to guarantee the system transient and steady-state performance within a prescribed region. Different from existing works on prescribed performance control (PPC), the present method can relax the restriction that the initial value must be given within a predefined region, say, PPC semiglobally. In the case that the upper bound functions for nonlinear time-delay functions are unknown, based on the approximate capacity of fuzzy-logic systems, an adaptive fuzzy approximation control strategy is proposed. When the upper bound functions are known in prior, or in a product form with unknown parameters and known functions, an output-feedback tracking controller is designed, under which the closed-loop signals are globally ultimately uniformly bounded, and tracking control with global prescribed performance can be achieved. Simulation results are given to substantiate our method.

This article investigates the distributed dynamic output-feedback bipartite consensus for a class of stochastic nonlinear multiagent systems (MASs) with time delays and actuators faults under directed switching graphs. First, a distributed extended state compensator is constructed for each agent to compensate for the consensus errors and actuators’ faults only using the output information of neighbors. Then, based on the compensator, a linear memoryless output-feedback controller is designed. Using a technical lemma and the stochastic Lyapunov stability theory, it is proved that combined with the given constraint conditions on graphs switching the 2nd-moment asymptotic bipartite consensus for the MASs can be achieved. Different from existing results, the proposed compensator can not only save the network bandwidth but also compensate for the actuators’ faults. The proposed scheme also significantly relaxes the conditions on the communication network to directed switching graphs and even allows the graph to be disconnected over some time intervals. The common design parameters under any graphs can avoid the detection of graph switching, which will need global topology information. Finally, a numerical simulation is given to illustrate the effectiveness of the proposed method.

In this article, we investigate the consensus problem of multiagent systems (MASs) based on the event-triggered control (ETC) method. The communication between agents is transmitted through unreliable networks with denial-of-service (DoS) attacks. By equipping the MAS with estimation capabilities so as to estimate the lost measurements caused by DoS attacks, we present a hybrid dynamic event-triggered strategy (HDETS) for the consensus of MAS subject to unreliable networks. Based on the proposed HDETS, we can preserve the consensus of MASs provided that the DoS attacks satisfy a condition on its frequency and duration. In addition, it can guarantee the Zeno-freeness with a designed strictly positive minimum event-triggered interval as well. Furthermore, we revisit the estimator with the trigger-resetting property, and present a finite time resetting condition for the estimation error, which illustrates the maximal DoS attacks intensity that the MASs can tolerate. Finally, the developed results are verified by a spacecraft formation simulation example.

This article investigates the stabilization control and stabilizing data-rate condition problems for networked control systems, which transmit signals from the sensor to the controller over the communication network with denial-of-service (DoS) attacks. Considering a class of DoS attacks that only constrain its frequency and duration, we aim to explore the constraint condition for stabilization and minimum stabilizing data rate of the networked control systems. The framework consists of two main parts. The first part considers the stabilizing control by the state-feedback approach under ideal bandwidth capacity. While the second part characterizes the average stabilizing data rate in terms of the eigenvalues of system matrix and DoS constraint functions to explicitly reveal the relationship between the attacks and the network bandwidth capacity. The stabilizing result is novel in the sense that the DoS-attack intensity, which is characterized by its frequency and duration, can vary for different time intervals. With this feature, the minimum average data-rate condition can vary for different time intervals according to the intensity of DoS attacks.

The adaptive neural network tracking control problem is investigated for a class of interconnected switched systems. The considered systems are with unmodeled dynamics, some of which do not satisfy the input-to-state stable (ISS) condition. By utilizing the neural network to approximate the composite unknown nonlinear functions, the corresponding decentralized tracking controller is designed for each subsystem with the help of dynamic surface control method. Some subsystems are stable with the designed controller, while other subsystems may not be stable because of non-ISS unmodeled dynamics, but they have some special properties with the designed controller. Then, a novel switching signal scheme is established such that the interconnected switched system is stable in the sense of semi-global boundedness, and the tracking errors can converge to predefined residual sets with prescribed performance index. Moreover, the switching scheme allows the number of switches to grow faster than traditional average dwell time method. Finally, a numerical example is provided to demonstrate the effectiveness of the presented results.

This paper investigates the cooperative stabilization problem for a class of linear switched systems under asynchronous switching. Based on a novel class of switching signals which prevail over the traditional average dwell time scheme, a sufficient condition of global asymptotic stability is proposed for the considered system. Unlike the existing results, the provided condition permits the Lyapunov-like function to increase not only in the period of mode-identifying process but also in normal-working period with matched controller. Compensating the increment by an increased decrement, the proposed approach can guarantee the decrease of the Lyapunov-like function from a whole perspective. Moreover, the solvability condition is established as well to obtain the gains for corresponding controllers. Finally, a simulation example is provided to verify the validity of the presented method.

This paper considers the adaptive fuzzy output feedback tracking control problem for a class of uncertain nonlinear switched systems with time delay and unmodeled dynamics. Based on a kind of switched K-filters, a prescribed performance control scheme is proposed to guarantee the tracking performance and restrain the fluctuation caused by switches between submodes as well. In addition, fuzzy logic systems (FLSs) are use to approximate unknown nonlinear functions and dynamic surface control (DSC) method is employed to eliminate the explosion of complexity problem inherent in traditional backstepping method. The proposed controllers of corresponding subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time (ADT). A numerical simulation is performed to illustrate the effectiveness of the proposed approach.