Exponential Consensus for Nonlinear Multi‐Agent Systems with Communication and Input Delays via Hybrid Control

This paper aims to investigate the exponential leader‐following consensus for nonlinear multi‐agent systems with time‐varying communication and input delays by using hybrid control. Based on the Lyapunov functional method, impulsive differential equation theory and matrix analysis, we show that all the followers can achieve leader‐following consensus with the virtual leader exponentially even if only a fraction of followers can obtain the leader's information. Two classes of exponential consensus criteria as well as the convergence rates for the controlled multi‐agent systems are presented under very relaxed interaction topology conditions, i.e., the directed interaction topology among the followers is only required to have p(p>1) disjoint strong components. Finally, two numerical examples are given to validate the proposed theoretical results.     

Distributed MPC for Tracking and Formation of Homogeneous Multi‐agent System with Time‐Varying Communication Topology

The distributed model predictive control (MPC) is studied for the tracking and formation problem of multi‐agent system with time‐varying communication topology. At each sampling instant, each agent solves an optimization problem respecting input and state constraints, to obtain its optimal control input. In the cost function for the optimization problem of each agent, the formation weighting coefficient is properly updated so that the adverse effect of the time‐varying communication topology on the closed‐loop stability can be counteracted. It is shown that the overall multi‐agent system can achieve the desired tracking and formation objectives. The effectiveness of the results is demonstrated through two examples.     

Event‐Triggered Control for Multi‐Agent Systems with General Directed Topology and Time Delays

Recent years have witnessed a growing interest in event‐triggered strategies for coordination and cooperative control of multi‐agent systems. However, the most previous works and developments focus on the interactive network that has no communication delays. This paper deals with the consensus problem of an agent system with event‐triggered control strategy under communication time delays. We first propose a time delays system model, then present a novel event triggering function that not only avoids continuous communication but also excludes the Zeno behavior. Furthermore, we provide the consensus analysis using an inequality technique instead of the traditional linear matrix inequality method, and we demonstrate that the inter‐event times for each agent are strictly positive, which implies that the Zeno behavior can be excluded. Finally, simulation results show the effectiveness of the proposed approach and illustrate the correctness of the theoretical results.     

Adaptive Action for Multi‐Agent Persistent Coverage

Persistent coverage with a team of agents refers to the task of covering an area where the coverage degrades with time. This is a dynamic task as opposed to the deployment problem. A key issue here is the coverage degradation that prevents the complete coverage fulfilment and requires persistence in the action. We propose a new method for persistent coverage where the agents' actions are computed in a partially distributed manner. The contribution is a control strategy based on variable coverage action and variable coverage range of the agents. This control provides adaptive behaviour in terms of actuator power and actuator domain in order to reduce the coverage error and energy consumption. The proposal is tested in simulation, showing clear improvement in terms of efficiency, flexibility, and scalability.     

Formation Tracking for Nonlinear Multi‐Agent Systems with Delays and Noise Disturbance

This paper investigates the formation tracking problem of nonlinear multi‐agent systems with communication delays and noise disturbance under directed interconnection topologies. By using a novel stochastic analysis approach and matrix theory, one establishes three formation tracking protocols containing nonlinear coupling function and delays such that the desired formations can be achieved in the sense of mean square under a special “multiple leaders” framework. Some new sufficient conditions of time‐delay dependence for the formation tracking in mean square are also developed. A simple example is given to illustrate the effectiveness of the proposed theoretical results.     

“Kronecker Basis” Based Average Consensus Analyses for High‐Order Linear Multi‐Agent Systems with Multiple Time Delays

This paper investigates the average consensus for multi‐agent systems governed by high‐order linear dynamics with multiple time delays. Necessary and sufficient conditions for high‐order average consensus under balanced communication topology are provided by using a newly defined mathematical concept – the Kronecker basis. Furthermore, previous studies for average consensus governed by first‐order, or high‐order integrator can be regarded as special cases of our results. Simulation results are employed to demonstrate the effectiveness of our results for high‐order average consensus.     

Bounded Consensus Algorithms for Multi‐Agent Systems in Directed Networks

In this paper, the consensus problem is investigated via bounded controls for the multi‐agent systems with or without communication. Based on the nested saturation method, the saturated control laws are designed to solve the consensus problem. Under the designed saturated control laws, the transient performance of the closed‐loop system can be improved by tuning the saturation level. First of all, asymptotical consensus algorithms with bounded control inputs are proposed for the multi‐agent systems with or without communication delays. Under these consensus algorithms, the states’ consensus can be achieved asymptotically. Then, based on a kind of novel nonlinear saturation functions, bounded finite‐time consensus algorithms are further developed. It is shown that the states’ consensus can be achieved in finite time. Finally, two examples are given to verify the efficiency of the proposed methods.     

Cooperative Adaptive Fuzzy Output Feedback Control for Synchronization of Nonlinear Multi‐Agent Systems in the Presence of Input Saturation

This paper considers the leader‐following synchronization problem of nonlinear multi‐agent systems with unmeasurable states in the presence of input saturation. Each follower is governed by a class of strict‐feedback systems with unknown nonlinearities and the information of the leader can be accessed by only a small fraction of followers. An auxiliary system is introduced and its states are used to design the cooperative controllers for counteracting the effect of input saturation. By using fuzzy logic systems to approximate the unknown nonlinearities, local adaptive fuzzy observers are designed to estimate the unmeasurable states. Dynamic surface control (DSC) is employed to design distributed adaptive fuzzy output feedback controllers. The developed controllers guarantee that the outputs of all followers synchronize to that of the leader under directed communication graphs. Based on Lyapunov stability theory, it is proved that all signals in the closed‐loop systems are semiglobally uniformly ultimately bounded (SGUUB), and the tracking error converges to a small neighborhood of the origin. An example is provided to show the effectiveness of the proposed control approach.     

Robust Adaptive Neural Control for a Class of Time‐Varying Delay Systems with Backlash‐like Hysteresis Input

This paper proposes a robust adaptive dynamic surface control (DSC) scheme for a class of time‐varying delay systems with backlash‐like hysteresis input. The main features of the proposed DSC method are that 1) by using a transformation function, the prescribed transient performance of the tracking error can be guaranteed; 2) by estimating the norm of the unknown weighted vector of the neural network, the computational burden can be greatly reduced; 3) by using the DSC method, the explosion of complexity problem is eliminated. It is proved that the proposed scheme guarantees all the closed‐loop signals being uniformly ultimately bounded. The simulation results show the validity of the proposed control scheme.     

Robust Adaptive Fuzzy Control of Nonlinear Systems with Unknown and Time‐Varying Saturation

In this paper, a robust adaptive fuzzy control approach is proposed for a class of nonlinear systems in strict‐feedback form with the unknown time‐varying saturation input. To deal with the time‐varying saturation problem, a novel controller separation approach is proposed in the literature to separate the desired control signal from the practical constrained control input. Furthermore, an optimized adaptation method is applied to the dynamic surface control design to reduce the number of adaptive parameters. By utilizing the Lyapunov synthesis, the fuzzy logic system technique and the Nussbaum function technique, an adaptive fuzzy control algorithm is constructed to guarantee that all the signals in the closed‐loop control system remain semiglobally uniformly ultimately bounded, and the tracking error is driven to an adjustable neighborhood of the origin. Finally, some numerical examples are provided to validate the effectiveness of the proposed control scheme in the literature.     

Output Feedback Stabilization for a Class of Stochastic High‐Order Feedforward Nonlinear Systems with Time‐Varying Delay

This paper considers the output feedback control problem for a class of stochastic high‐order feedforward nonlinear systems with time‐varying delay. Compared with existing works, the features of our system include different bounded time‐varying delays, more general high‐order power and homogeneous feedforward growth conditions. Firstly, we use the adding one power integrator technique to construct an output feedback controller without nonlinearities. Then, by introducing a scaling gain into the controller and choosing an appropriate Lyapunov–Krasovskii functional, the closed‐loop system can be rendered globally asymptotically stable in probability. A simulation example is provided to illustrate the effectiveness of the designed controller.     

Formation Maneuvering and Target Interception for Multi‐Agent Systems via Rigid Graphs

In this paper, we introduce control laws for multi‐agent formation maneuvering and target interception problems. In the target interception problem, we consider that the target velocity is unknown. Using a single‐integrator agent model, the proposed controls consist of a formation acquisition term, dependent on the graph rigidity matrix, and a formation maneuvering or target interception term. The control laws are only a function of the relative position of agents in an infinitesimally and minimally rigid graph, and either the desired maneuvering velocity of the formation or the target's relative position to the leader. The target interception control includes a continuous dynamic estimation term to identify the unknown target velocity. A Lyapunov‐like stability analysis is used to prove that the control objectives are met.     

Event‐triggered Control for Cluster Consensus in Multi‐agent Networks

This paper considers the issue of cluster consensus for multiple agents in fixed and undirected networks. Agents in a network are supposed to split into several clusters, and a fraction of the agents in each cluster are pinned by virtual leaders. According to the Lyapunov stability theory and graph theory, some appropriate event‐triggered protocols are developed for consensus of the agents belonging to the same cluster, which can greatly reduce both the number of communication updates and that of control actuation updates. Finally, a numerical example is shown to demonstrate the effectiveness of the proposed theoretical results.     

Leader‐Following Output Synchronization for a Class of Uncertain Nonlinear Multi‐Agent Systems Under Uniformly Connected Network

In this paper we study the cooperative global output regulation problem of a class of uncertain nonlinear multi‐agent systems under dynamic network topology. Distributed dynamic observers are introduced to estimate the states of the leader system or the called exosystem. Furthermore, we propose a multi‐channel input version of the changing supply rate theorem, through which the changing supply rate technique can be applied to the subsystem with multiple channels of the control inputs, and therefore control laws can be designed in a fully distributed way. As opposed to the existing results, in the current paper we allow the communication network topology to be uniformly connected. Finally, we apply our result to a group of well‐known Lorenz systems.     

Adaptive Finite‐Time Robust Control of Nonlinear Delay Hamiltonian Systems Via Lyapunov‐Krasovskii Method

This paper investigates the adaptive finite‐time robust control problem of a class of nonlinear time‐delay Hamiltonian systems via the Lyapunov‐Krasovskii (L‐K) method, and proposes some delay‐dependent results on the issue. Different from existing works, this paper first presents a time‐varying finite‐time stability (FTS) criterion via an L‐K functional approach, and obtains two FTS conditions by constructing specific L‐K functionals. Then, the adaptive finite‐time robust control problem is investigated for nonlinear time‐delay port‐controlled Hamiltonian (PCH) systems, and a control design procedure is presented. Finally, the effectiveness of the results is demonstrated by an illustrative example.     

Reset Control Systems With Time‐Varying Delay: Delay‐Dependent Stability And Gain Performance Improvement

This paper considers the stability analysis of reset control systems with time‐varying delay. Based on sector reset conditions, delay‐dependent exponential stability and finite gain stability conditions are proposed, and piecewise Lyapunov functions are used such that less conservative results can be obtained, moreover, gain performance improvement results are presented to show the advantage of reset control. Numerical examples are given to show the effectiveness.     

Passive Control for Stochastic Interval Systems with Interval Time‐Varying Delay

This paper is concerned with the problem of delay‐dependent passive analysis and control for stochastic interval systems with interval time‐varying delay. The system matrices are assumed to be uncertain within given intervals, and the time delay is a time‐varying continuous function belonging to a given range. By the transformation of the interval uncertainty into the norm‐bounded uncertainty, partitioning the delay into two segments of equal length, and constructing an appropriate Lyapunov–Krasovskii functional in each segment of the delay interval, delay‐dependent stochastic passive control criteria are proposed without ignoring any useful terms by considering the information of the lower bound and upper bound for the time delay. The main contribution of this paper is that a tighter upper bound of the stochastic differential of Lyapunov–Krasovskii functional is obtained via a newly‐proposed bounding condition. Based on the criteria obtained, a delay‐dependent passive controller is presented. The results are formulated in terms of linear matrix inequalities. Numerical examples are given to demonstrate the effectiveness of the method.     

Supervised Multi‐Rejector of Periodic Disturbances for Nonlinear Systems Using Decoupled State Multimodel

In this paper, a multi‐rejector of periodic disturbances is proposed for discrete‐time nonlinear systems represented by a decoupled state multimodel. We report a decoupled state multimodel repetitive‐predictive control based on a supervised algorithm to ensure reference trajectory tracking and periodic disturbances rejection. Partial predictors associated to the local controllers make the best choice of the most valid partial controller that meets the desired closed loop performances. The effectiveness of the supervised multi‐rejector is shown via a simulation example. The obtained results are satisfactory and show a good rejection of periodic disturbances and reference trajectory tracking.     

Robust Stability Analysis for Systems with Time‐Varying Delays: A Delay Function Approach

This paper is concerned with the robust stability of time‐varying delay systems with structured uncertainties. Stability conditions are provided through a Lyapunov‐Krasovskii functional (LKF) method. The proposed method introduces a linear function of the time‐varying delay to construct the LKF. With this function, two‐dimensional partition is conducted on the integral domain in the derivative of LKF. Quadratic convex combination then is employed to present stability criteria in the form of linear matrix inequalities (LMIs). The method not only exploits the information of delay at different time instants, but also enables the handling of its derivative to reduce conservatism. Numerical examples are given to show the effectiveness of our method.     

Improved Stabilization for Continuous Dynamical Systems with Two Additive Time‐Varying Delays

This paper studies the problem of stabilization criteria for systems with two additive time‐varying delays. First, the delay‐dependent stability condition for the systems is established through computing the more general Lyapunov functional. The Lyapunov functional is constructed by making full use of the property and the information of the systems, and the condition has advantages over the existing ones in the skillful combination of the delay decomposition and the reciprocal convex approach. Second, considered to be more flexible for the controller design with the introduced positive scalar, a new controller method is presented. Finally, two examples are provided to demonstrate the advantage of the results in this paper.