Time-delay Multi-agent Systems Research Articles

Dynamic Event-Triggered Prescribed-Time Consensus Tracking of Nonlinear Time-Delay Multiagent Systems by Output Feedback

Dynamic Event-Triggered Prescribed-Time Consensus Tracking of Nonlinear Time-Delay Multiagent Systems by Output Feedback

Adaptive distributed fault estimation observer design for nonlinear time-delay multi-agent systems with directed graphs

This paper focuses the development of an adaptive observer-based distributed fault estimation observer (DFEO) for multi-agent nonlinear time-delay systems under a directed communication topology. The process involves constructing a fault estimation observer for each agent based on their relative output estimation errors. An adaptive DFEO design is proposed for multi-agent systems with a directed communication topology. Furthermore, investigating the effect of faulty agents on the criteria of fault detection on healthy agents. The proposed design is represented with Linear Matrix Inequalities (LMIs) to establish a systematic design procedure. The study also includes simulation results to demonstrate the effectiveness of the proposed design techniques.

Adaptive fuzzy event-triggered control for a class of nonlinear time-delay multi-agent systems with dead zone and partial state constraints

This paper presents an adaptive fuzzy event-triggered control (ETC) method for a class of time-delay nonlinear multi-agent systems (MASs) with dead zone (DZ) and partial state constraints (PSCs). It should be pointed out that the states considered in this paper are unmeasurable and part of the system states are constrained by time-varying boundary. By utilizing fuzzy logic systems (FLSs) and backstepping design framework, a fuzzy state observer is constructed to estimate the unmeasured states, while the introduction of a time-varying barrier Lyapunov function (BLF) addresses the partial state constrained problem. Furthermore, during the design process of the state observer, compensation for the influence of the unknown DZ input on the system is achieved through utilization of known designed event-triggered input signal and adaptive parameter. Building upon this foundation, employing the Lyapunov stability theory and adaptive backstepping technique with ETC strategy, the developed distributed control mechanism demonstrates that all variables of the closed-loop system are bounded, the consensus error of the system can converge to a small region of origin and Zeno behavior can be ruled out. Finally, two simulation examples further illustrate the proposed control strategy and theorem.

Novel consensus framework on discrete-time positive multi-agent systems

This paper investigates the consensus of discrete-time positive multi-agent systems. A framework on the consensus of positive multi-agent systems is constructed. By introducing a finite point and a self-feedback term, a novel consensus protocol is proposed to drive all states to common nonnegative finite values. An improved error model is established for positive multi-agent systems. Based on the consensus error model, the consensus of the agents is transformed into the stability of the error systems. Under the proposed consensus protocol and the new consensus error model, the consensus of agents is realized. A copositive Lyapunov function is chosen to derive the consensus of the multi-agent systems. Such a consensus approach is extended for time-delay multi-agent systems. All positivity and consensus conditions can be solved by virtue of linear programming. The main novelties of this paper lie in that: (i) A novel consensus error model is established, (ii) A finite value consensus is achieved, and (iii) Linear programming-based conditions are presented for the consensus design. Finally, two illustrated examples are given to verify the validity of the theoretical findings.

Output-mask-based adaptive NN control for stochastic time-delayed multi-agent systems with a unified event-triggered approach

This paper investigates a class of output-mask-based adaptive neural network (NN) tracking control for nonlinear stochastic time-delayed multi-agent systems (STMASs) based on a unified event-triggered approach. The output signal relies on an output mapping acted as a mask, defined as a privacy-protection-like method, so that the internal state of one agent cannot be identified by other distrustful eavesdroppers or attackers. Moreover, the construction of a unified event-triggered control scheme retains the advantages of the saturation threshold triggering strategy, incorporates distributed errors, and increases the flexibility of thresholds. Furthermore, for stochastic time-delay multi-agent systems, the initial value limitation of the conventional first-order filter is removed by a first-order Levant differentiator, and a new estimation term in the fuzzy observer is established to solve the nonlinear fault. The unknown function in pure-feedback form is addressed via combining Butterworth low-pass filter and radial basis function neural networks (RBF NNs). Finally, the boundedness of all signals in the closed-loop systems is demonstrated, and the effectiveness of the proposed algorithm is verified by some simulation results.

Distributed Saturated Impulsive Control for Local Consensus of Nonlinear Time-Delay Multiagent Systems With Switching Topologies

In this paper, the local consensus problem of nonlinear time-delay multi-agent systems with switching topologies via distributed saturated impulsive control is discussed and the maximum domain of attraction is well estimated. Specifically, we develop a new estimation approach that is quite distinct from the contractive invariant set to estimate the domain of attraction. Moreover, a novel composite impulsive-instant-dependent Lyapunov function is constructed and an improved convex hull representation with more slack variables is adopted to minimize the conservativeness. And then, some delay-independent sufficient criteria in the form of bilinear matrix inequalities that guarantee local consensus of nonlinear time-delay multi-agent systems are obtained by means of the Lyapunov-Razumikhin technique and proof by contradiction. Through appropriate transformation, some linear matrix inequalities-based optimization problems constrained by the proposed local consensus criteria are formulated, and the corresponding numerical solutions are solved by the Yalmip. Finally, a simulation example is given to confirm the validity and superiority of the proposed theoretical results.

Sampled-Data-Based Distributed Output Feedback Leader–Following Consensus for Time-Delay Multiagent Systems

This paper addresses the distributed output feedback leader-following consensus problem for high-order nonlinear multiagent systems (MASs) with time delays and disturbances under the directed network. Using sampled relative outputs to neighbors and the discrete control input, the continuous-discrete time compensator is constructed in each agent to compensate for the consensus errors, where the sampling time instants can be asynchronous and aperiodic without exceeding an explicit upper bound of sampling intervals. Based on the compensator, we propose a co-design algorithm for constructing the dynamic event-triggered protocol with a corresponding event-triggering mechanism which is a combination of discrete-time control input, continuous dynamic variables of each agent's own compensator, and a given threshold. The proposed methods can not only achieve consensus tracking under the effects of time delays in states and communications but also implement the discrete-time execution of measurement, communication, and control. Based on the novel lemmas, it is proved that the resulting closed-loop consensus error system is globally stable. Finally, a simulation is given to illustrate the effectiveness of proposed methods.

Adaptive fault-tolerant formation tracking control of networked mobile robots with input delays

This paper addresses a fault-tolerant formation tracking problem for multiple mobile robots, where the dynamics of each robot is nonholonomic with time-varying input delays and actuator faults. The control problem is challenging since the actuator faults (e.g., loss of effectiveness and biased faults) are unknown in the time-delay multi-agent systems. To this end, an adaptive compensator is proposed for the uncertain time-delay systems induced by the loss of effectiveness faults. With the aid of neural networks and auxiliary variables, a novel adaptive fault-tolerant formation tracking controller for each robot is developed without any restrictions on the rate of their unknown variables induced by the biased faults. The uniformly ultimately boundness for the closed-loop system is derived according to the Lyapunov–Krasovskii functional. Numerical simulations verify the effectiveness of the proposed method.

A Delay Classification-Based Approach to Distributed Consensus of Nonlinear Time-Delay Multiagent Systems

This paper investigates the problem of the fixed directed topology-based leader-following consensus control for nonlinear multiagent systems with output delays. Diverging from existing results, this study focuses on large time-varying output delay. Taking this condition into account, a novel delay classification-based distributed output feedback consensus algorithm is developed. First, we divide the output delay into two types through a designed constant and introduce a switching signal to distinguish these two types. Then, we build a distributed compensator for each follower using relevant outputs to reconstitute the leader-following tracking errors. This compensator relies on the output delay and is irrelevant to the nonlinear dynamics of the system. Then, we design a distributed linear controller for each follower with the compensator's assistance. Subsequently, a new unified Lyapunov-Krasovskii functional is developed to prove that all agents can realize leader-following full-state consensus with the action of the controller. We also provide sufficient conditions to demonstrate the controller's validity. Finally, a simulation example is supplied to validate the efficiency of our algorithm.

Event-Triggered Consensus Tracking for Time-Delay Multi-Agent Systems with Input Saturation Via Dynamic Output Feedback

Event-Triggered Consensus Tracking for Time-Delay Multi-Agent Systems with Input Saturation Via Dynamic Output Feedback

Control for Nonlinear Fuzzy Time-Delay Multiagent Systems: Two Kinds of Distributed Saturation-Constraint Impulsive Approach

The impulsive consensus problems of nonlinear time-delay multi-agent system under communication constraints are analyzed and investigated in the paper. In view of the limited communication channel, global input saturation constraint is integrated into the design of impulse control protocol. Furthermore, in order to reduce energy consumption and communication cost, two kinds of impulsive control protocols are designed which conclude general impulsive control protocols and event-triggered impulsive control protocols. For event-triggered impulsive control protocols, by setting event decision time at impulse time, this novel consensus control protocols not only decrease communication frequency and energy consumption, but also avoid “Zeno behavior”. Through theoretical derivation, some sufficient conditions that guarantee the leader-following consensus of multi-agent system are presented. In the end, for the sake of explaining the superiority of impulse control combined with event-triggered control strategy in more detail, the simulations of two control methods are given respectively for the same multi-agent system, which can be better compared and explained.

Quantized iterative learning control for singular nonlinear fractional-order time-delay multi-agent systems with iteration-varying reference trajectories and switching topologies

This paper addresses the consensus tracking of the leader-following singular nonlinear fractional-order system with state time-delay in face of iteration-varying communication topologies and reference trajectories via an iterative learning control scheme. Firstly, by means of the neighbor information, the closed-loop Dα-type quantized iterative learning protocol is constructed based on output tracking errors. Secondly, sufficient conditions of consensus errors between each follower agent and leader agent are given in a fixed time interval and convergence analysis is also presented under the fixed topology and reference trajectory. Thirdly, the extension to iteration-varying reference trajectory tracking and switching topologies cases are investigated. It is shown that the developed protocol can also effectively work along the iteration axis on a finite time interval, although the communication topologies and reference trajectories vary dynamically with respect to iteration. Finally, numerical examples are shown to verify the effectiveness of the obtained results.

Sampled-data consensus control for nonlinear time-delay multi-agent systems under false data injection attacks

Sampled-data consensus control for nonlinear time-delay multi-agent systems under false data injection attacks

Research on Consensus of Multi-agent System Under Saturation Constrained Impulse Control

This paper mainly analyzes and studies the impulse consensus of nonlinear time-delay multi-agent systems under communication constraints. Firstly, considering the inherent attribute of the actuator -- each agent communication channel is finite, the control protocol design considers the global input saturation constraint and introduces the general case that the upper and lower bounds of saturation constraint are ±1. Secondly, due to the complexity of the real communication environment, it is often difficult for the agent to ensure real-time and continuous communication in the communication process, so this paper mainly considers the impulse control method in the discontinuous control. In addition, when the communication environment of the agent is complex, time delay is also a common phenomenon, so the nonlinear system with time delay is studied in this paper. Based on Lyapunov theory, convex hull theory and other theoretical methods, the sufficient conditions to ensure the lead-following consensus of multi-agent systems are given in view of the above saturated constraints. Finally, the correctness and effectiveness of the proposed method are verified by a simulation example.

Bipartite consensus for nonlinear time-delay multiagent systems via time-varying gain control method

Bipartite consensus for nonlinear time-delay multiagent systems via time-varying gain control method

Frequency domain resilient consensus of multi-agent systems under IMP-based and non IMP-based attacks

This paper presents a frequency domain resilient consensus problem of time-delayed multi-agent systems (MASs) under attacks. An internal model principle-based attack, a kind of network attack, is firstly analyzed and modeled in frequency domain. Then, a Quasi-H∞ robust controller is designed for resilient consensus of the MAS with the help of an internal model controller. This scheme is different from the existing works in the sense that the attacker may inject an attacking signal on the node of an agent instead of a communication link. It is also novel because it can eliminate the impacts of attack without excluding compromised nodes and restricting the number of compromised nodes. The proposed control scheme is applied to a linear delayed MAS with single-input single-output agents and then transformed into multi-input and multi-output agents. An innovative approach is employed for the tuning of the proposed controller to track the performance of the MAS and its robustness. Some necessary and sufficient conditions are extracted using Padé approximation and graph theory to minimize the impacts of time delay and attacks simultaneously. The results are extended for resilient consensus of the MAS under non-internal model principle-based attack. The simulation results are presented to demonstrate the validity of the proposed control strategy.

Adaptive event-triggered control for time-delay multi-agent systems with actuator faults and asymmetric error constraints

This article proposes an adaptive event-triggered control strategy for the consensus tracking control problem in nonlinear multi-agent systems. First, by introducing the asymmetric barrier function, output error can satisfy asymmetric constraints. The Lyapunov-Krasovskii (L-K) functional and Young inequality are then used to eliminate the influence of state time delays. The fuzzy logic system is used to approximate the unknown nonlinear function. Furthermore, using a bound estimation approach and a smooth function, the effects of the actuator faults, as well as the network-induced error, are effectively compensated for. According to the Lyapunov stability theory, the closed-loop systems have semi-globally bounded stability. Finally, the validity of the designed control strategy is verified by simulation.

Multi-leader-follower group consensus of stochastic time-delay multi-agent systems subject to Markov switching topology.

The multi-leader-follower group consensus issue of a class of stochastic time-delay multi-agent systems subject to Markov switching topology is investigated. The purpose is to determine a distributed control protocol to make sure that the followers' states converge in mean square to a convex hull generated by the leaders' states. Through a model transformation, the problem is transformed into a mean-square stability issue of a new system. Then, an easy-to-check sufficient condition for the solvability of the multi-leader-follower group consensus issue is proposed by utilizing the Lyapunov stability theory, graph theory, as well as several inequality techniques. It is shown that the required feedback gain can be acquired once the condition is satisfied. Finally, an example is used to illustrate the effectiveness of the control protocol.

Quasi-Consensus Control for a Class of Time-Varying Stochastic Nonlinear Time-Delay Multiagent Systems Subject to Deception Attacks

This article focuses on the consensus control problem for a class of time-varying stochastic nonlinear time-delay multiagent systems (MASs) attacked by deception attacks. The stochastic deception attack is considered in the procedure of propagating measurement information among agents. To solve the consensus control problem for addressed MASs under stochastic deception attacks, a definition of quasi-consensus is put forward. The objective of our investigation is to devise a consensus protocol to drive all agents to stay within an allowable range despite the existence of stochasticity and external malicious attacks. With the help of recursive linear matrix inequality and stochastic analysis methods, sufficient conditions are acquired to guarantee that all agents are constrained in the desirable range. Subsequently, an optimization algorithm is presented, which is to seek the locally optimal allowable distance among agents. Finally, a simulation example is presented to demonstrate the availability of our proposed algorithm.

Event-triggered consensus control and fault estimation for time-delayed multi-agent systems with Markov switching topologies

This paper focuses on the consensus control and fault estimation problems for a class of time-delayed multi-agent systems with Markov switching topologies. Two different event-triggered mechanisms are adopted with hope to reduce burden of shared network and improve energy efficiency. Under Markov process, by establishing the consensus control protocol and designing a novel adaptive fault estimation observer, the consensus control and fault estimation problems are transformed into two stochastic stability problems in different forms. Then, according to the switching Lyapunov function method and free-weighting matrix technique, two delay-dependent stability criteria on the consensus control and fault estimation are derived, respectively. However, the two criteria containing nonlinear coupling terms are not standard linear matrix inequalities (LMIs) and cannot be solved directly with the LMI toolbox. In order to eliminate the coupling terms, two improved path-following algorithms are presented. These algorithms depend on the initial conditions, so it is very crucial to choose the appropriate preset parameters. The computational complexity is increasing with the number of iterations, system size and matrix dimension, which is a fully new challenge for the study of consensus control and fault estimation of multi-agent systems. Based on the algorithms, the switching consensus controller gains and model gain matrices of fault estimation can be efficiently solved out. Finally, a simulation example of tailless fighter airplanes is given to illustrate the practicality and validity of the theoretical results.