Sampled-Data-Based Consensus and $L_{2}$ -Gain Analysis for Heterogeneous Multiagent Systems

Distributed Optimization Design for Computation of Algebraic Riccati Inequalities

This article proposes a distributed optimization design to compute continuous-time algebraic Riccati inequalities (ARIs), where the information of matrices is distributed among agents. We propose a design procedure to tackle the nonlinearity, the inequality, and the coupled information structure of ARI; then, we design a distributed algorithm based on an optimization approach and analyze its convergence properties. The proposed algorithm is able to verify whether ARI is feasible in a distributed way and converges to a solution if ARI is feasible for any initial condition.

Distributed Adaptive Control for Asymptotically Consensus Tracking of Uncertain Nonlinear Systems With Intermittent Actuator Faults and Directed Communication Topology

In this article, we investigate the output consensus tracking problem for a class of high-order nonlinear systems with unknown parameters, uncertain external disturbances, and intermittent actuator faults. Under the directed topology conditions, a novel distributed adaptive controller is proposed. The common time-varying trajectory is allowed to be totally unknown by part of subsystems. Therefore, the assumption on the linearly parameterized trajectory signal in most literature is no longer needed. To achieve the relaxation, extra distributed parameter estimators are introduced in all subsystems. Besides, to handle the actuator faults occurring at possibly infinite times, a new adaptive compensation technique is adopted. It is shown that with the proposed scheme, all closed-loop signals are globally uniformly bounded and asymptotically output consensus tracking can be achieved.

Stability analysis and stabilization of discrete-time switched Takagi-Sugeno fuzzy systems

We endeavor to investigate the H_∞ synthesis problem of switched fuzzy systems composed by several discrete-time subsystems. By designing a novel QTD-MD Lyapunov function, novel criteria assuring stability as well as an expected H_∞ performance are first developed. Based on these sufficient conditions, some other conditions for solving the fuzzy H_∞ controllers are derived subsequently. Furthermore, the criteria are given as LMIs, thus the implementations are easy to execute. Simulations are also provided to confirm the feasibility of the presented strategy.

Delayed Impulsive Control for Consensus of Multiagent Systems With Switching Communication Graphs

Delayed impulsive controllers are proposed in this paper to enable the agents in a class of second-order multiagent systems (MASs) to achieve state consensus, based, respectively, on the relative full-state and partial-state sampled-data measurements among neighboring agents. It is a challenging task to analyze the consensus behaviors of the considered MASs as the dynamics of such MASs will be subjected to joint effects from delay-dependent impulses, aperiodic sampling, and switchings among different communication graphs. A novel analytical approach, based upon the discretization method, state augmentation, and linear state transformation, is developed to establish the sufficient consensus criteria on the range of the impulsive intervals and the control parameters. Remarkably, it is found that consensus in the closed-loop MASs can be always ensured by skillfully selecting the control parameters as long as the nonuniform delays and the impulsive intervals are bounded. A numerical example is finally performed to validate the effectiveness of the proposed delayed impulsive controllers.

A class of cooperative relay analysis of multi-agent systems with tracking number switching and time delays

This paper investigates a complicated class of cooperative tracking problems with time-varying number of tracking agents and communication time delays. During the entire tracking process, tracking agents are dynamically changing and the number is not fixed. This results in jumping of tracking errors and dynamic dimensions of the corresponding Laplacian matrices. Consequently, the stability analysis turns to be difficult especially when the effect of communication time delays is taken into consideration. In order to solve this issue, a new type of average Lyapunov function is constructed to compensate the unmatched dimensions of communication topologies over different time intervals. Generalized reciprocally convex Lemma and a more relaxed switched technique are employed to achieve a less conservative switched stability condition for the multi-agent system with variable tracking number and time delays. Finally, through a series of numerical simulations, the effectiveness and feasibility of derived results are verified. The relationship between maximum allowable communication time delays and various control parameters is obtained in a quantitative way.

Quantized Consensus of Multi-Agent Networks With Sampled Data and Markovian Interaction Links

This paper investigates the joint effect of quantization, sampled data, and general Markovian interaction links on consensus networks with a leader under directed graphs. The diversity of edges formed by all the followers and the leader is also considered. Each agent in the network possesses continuous-time general linear dynamics. Each agent's state is measured only at sampling time instants, which is encoded before transmission. Subsequently, the encoded state is transmitted through noiseless digital communication links with Markovian switching rates. For this problem, a sufficient condition is derived to guarantee the convergence of the encoded states, based on which a necessary and sufficient condition is obtained to achieve consensus tracking in the mean-square sense. In addition, two sufficient conditions on coupling gain, one of which is fully distributed, are provided by proposing an optimal linear quadratic regulator-based gain matrix to ensure consensus tracking and then, the analysis of consensus region is presented. Finally, a numerical example is presented for illustrating the effectiveness of the theoretical results.

Tracking Control of a Class of Cyber-Physical Systems via a FlexRay Communication Network

Due to properties of flexibility, adaptiveness, error tolerance, and time-determinism performance, the FlexRay communication protocol has been widely used to investigate robot systems and new generation of automobiles. In this paper, with the FlexRay communication protocol, the tracking problem of a class of cyber-physical systems are investigated by developing a general hybrid model, in which an emulation controller is utilized. Based on the proposed hybrid model, some sufficient conditions are established to guarantee the convergence of tracking errors. Then, the maximum allowable transmission interval (MATI) of the static/dynamic segment is obtained with a more general formula than the ones in some the previous works. The obtained MATI over the FlexRay communication network can be adjusted via the appropriate length of the static/dynamic segment, which reflects the flexibility of FlexRay. Finally, the results are verified by considering the tracking problem of a single-link robot arm system as well as the stabilization of a batch reactor system.

Scaled Group Consensus in Multiagent Systems With First/Second-Order Continuous Dynamics

We investigate scaled group consensus problems of multiagent systems with first/second-order linear continuous dynamics. For a complex network consisting of two subnetworks with different physical quantities or task distributions, it is concerned with this case that the agents' states in one subnetwork converge to a consistent value asymptotically, while the states in the other subnetwork approach another value with a ratio of the former. For the case of the information exchange being directed, novel consensus protocols are designed for both first-order and second-order dynamics to solve the scaled group consensus problems. By utilizing algebra theory, graph theory, and Lyapunov stability theory, several necessary and sufficient conditions are established to guarantee the agents' states reaching the scaled group consensus asymptotically. Finally, several simulation results are presented to demonstrate the effectiveness of the theoretical results.

Distributed Optimization Design of Continuous-Time Multiagent Systems With Unknown-Frequency Disturbances

In this paper, a distributed optimization problem is studied for continuous-time multiagent systems with unknown-frequency disturbances. A distributed gradient-based control is proposed for the agents to achieve the optimal consensus with estimating unknown frequencies and rejecting the bounded disturbance in the semi-global sense. Based on convex optimization analysis and adaptive internal model approach, the exact optimization solution can be obtained for the multiagent system disturbed by exogenous disturbances with uncertain parameters.