Bipartite Consensus of Linear Multi-Agent Systems by Distributed Event-Triggered Control

For multi-agent systems with competitive and collaborative relationships, signed graph can more intuitively express the characteristics of their interactive networks. In this paper, the bipartite consensus is investigated for multi-agent systems with structurally balanced signed graph. In order to reduce actuation burden in dynamical network environment, the event-triggering strategy is applied to bipartite consensus protocol for the multi-agent systems. The triggered condition for each agent is designed by using its own information and transmitted information of its neighbors at sampling instant and make the number of triggers of the whole systems be reduced. Based on the distributed eventtriggered control, some sufficient conditions are derived to guarantee the leaderless and leader-following bipartite consensus. Finally, some numerical examples are shown to demonstrate the effectiveness of the theoretical results.     

Event-Triggered Sampled-Data Consensus of Nonlinear Multi-Agent Systems with Control Input Losses

This paper investigates the leader-following consensus problem for multi-agent systems with event-triggered mechanism and control packet losses. Based on the local synchronization error, event-triggered mechanisms are proposed in order to reduce the number of controller update. The control packet may lose due to unreliability of communication channel. With the assumption that once the packet loss happens the controller will be set to zero, sufficient consensus criteria for multi-agent system with event-triggered mechanism and control packet losses is obtained. It is also shown that the interplay among the allowable packet loss rate, event-triggered mechanism and sampling period. An illustrative example is given to demonstrate the effectiveness of the theoretical results.     

Optimal Control of Unknown Discrete-Time Linear Systems with Additive Noise

The optimal control problem with a long run average cost is investigated for unknown linear discrete-time systems with additive noise. The authors propose a value iteration-based stochastic adaptive dynamic programming(VI-based SADP) algorithm, based on which the optimal controller is obtained. Different from the existing relevant work, the algorithm does not need to estimate the expectation(conditional expectation) and variance(conditional variance) of states or other relevant variables, and th...     

Stabilization of Discrete-Time Dynamical Systems Under Event-Triggered Impulsive Control with and Without Time-Delays

This paper investigates the issue of stabilization for discrete-time dynamical systems (DDS) by event-triggered impulsive control (ETIC). Based on some relatively simple threshold constants, three levels of event conditions are set and thus the ETIC scheme is designed. Three cases for ETIC with and without time-delays and data dropouts are studied respectively, and the criteria on exponential stability are derived for the controlled DDS. The stabilization in the form of exponential stability is achieved for DDS under the designed ETIC with or without time-delays. And in the case of the ETIC data dropouts, the conditions of exponential stabilization are derived for DDS and the maximal allowable dropout rates for ETIC are estimated. Finally, one example with numerical simulations is worked out for illustration.     

Event-Triggered Consensus for Discrete-Time Multi-agent Systems with Parameter Uncertainties Based on a Predictive Control Scheme

In this paper, the event-triggered consensus for linear discrete-time multi-agent systems with parameter uncertainties is investigated. The parameter uncertainty is assumed to be normbounded. An event-triggered consensus protocol based on the predictive control method is proposed to make the multi-agent system achieve consensus. And for the design of the consensus protocol, the problem of estimating the control input is transformed into the problem of estimating state differences between agents. Furthermore, the event-triggered consensus protocol proposed in this paper only demands each agent to mornitor its state to determine its event-triggered instants. A sufficient existence condition for the consensus protocol is proposed based on the linear matrix inequality. And a sufficient condition for the nonexistence of the Zeno-like behaviour is also derived. Finally, a numerical example is given to illustrate that the event-triggered consensus protocol proposed in this paper can make the multi-agent system with parameter uncertainties achieve consensus effectively.     

Bipartite Consensus of Discrete-Time Double-Integrator Multi-Agent Systems with Measurement Noise

The effects of measurement noise are investigated in the context of bipartite consensus of multi-agent systems. In the system setting, discrete-time double-integrator dynamics are assumed for the agent, and measurement noise is present for the agent receiving the state information from its neighbors. Time-varying stochastic bipartite consensus protocols are designed in order to lessen the harmful effects of the noise. Consequently, the state transition matrix of the closed-loop system is analyzed, and sufficient and necessary conditions for the proposed protocol to be a mean square bipartite consensus protocol are given with the help of linear transformation and algebraic graph theory. It is proven that the signed digraph to be structurally balanced and having a spanning tree are the weakest communication assumptions for ensuring bipartite consensus. In particular, the proposed protocol is a mean square bipartite average consensus one if the signed digraph is also weight balanced.     

Event-Triggered Control for Multi-Agent Systems: Event Mechanisms for Information Transmission and Controller Update

Journal of Systems Science and Complexity - This paper investigates the state consensus of linear multi-agent systems in a graph where each agent is equipped with two novel event-triggering...     

Distributed Event-Triggered Formation Control of USVs with Prescribed Performance

Journal of Systems Science and Complexity - In this paper, the formation control problem is investigated for a team of uncertain underactuated surface vessels (USVs) based on a directed graph....     

Consensus of Heterogeneous Multi-Agent Systems with Intermittent Communication

This paper studies consensus of a class of heterogeneous multi-agent systems composed of first-order and second-order agents with intermittent communication. For leaderless multi-agent systems, we propose a distributed consensus algorithm based on the intermittent information of neighboring agents. Some sufficient conditions are obtained to guarantee the consensus of heterogeneous multi-agent systems in terms of bilinear matrix inequalities(BMIs). Meanwhile, the relationship between communication duration and each control period is sought out. Moreover, the designed algorithm is extended to leader-following multi-agent systems without velocity measurements. Finally, the effectiveness of the main results is illustrated by numerical simulations.     

Time-Variant Consensus Tracking Control for Networked Planar Multi-Agent Systems with Non-Holonomic Constraints

A time-variant consensus tracking control problem for networked planar multi-agent systems with non-holonomic constraints is investigated in this paper. In the time-variant consensus tracking problem, a leader agent is expected to track a desired reference input, simultaneously, follower agents are expected to maintain a time-variant formation. To solve the time-variant consensus tracking problem of planar multi-agent systems with non-holonomic constraints, a time-variant consensus tracking control strategy is designed on the basis of an unidirectional topology structure. One of main contributions of this paper is the time-variant consensus tracking protocol for general time-variant formations of planar multi-agent systems with non-holonomic constraints, the other main contribution of this paper is an active predictive control strategy, where predictions of agents are generated actively, so that the computational efficiency is improved than passive approaches. The proposed control strategy is verified by two types of time-varying formations of wheeled mobile robots, and the experimental results show that the proposed control strategy is effective for general time-variant consensus tracking problems of planar multi-agent systems with non-holonomic constraints in local and worldwide networked environments.     

Adaptive Asymptotic Tracking Control for Stochastic Nonlinear Systems with Unknown Backlash-Like Hysteresis

In this study, an adaptive asymptotic tracking control problem is considered for stochastic nonlinear systems with unknown backlash-like hysteresis. By utilizing backstepping technology and bound estimation approach, an adaptive asymptotic tracking control scheme is designed, where fuzzy systems are applied to approximate unknown function terms, the effect of hysteresis and stochastic disturbances is compensated appropriately. The proposed scheme ensures that the tracking error can asymptoticall...     

Cooperative Neuro Adaptive Control of Leader Following Uncertain Multi-Agent Systems with Unknown Hysteresis and Dead-Zone

In this paper, a cooperative adaptive control of leader-following uncertain nonlinear multiagent systems is proposed. The communication network is weighted undirected graph with fixed topology. The uncertain nonlinear model for each agent is a higher-order integrator with unknown nonlinear functions, unknown disturbances and unknown input actuators. Meanwhile, the gains of input actuators are unknown nonlinear functions with unknown sign. Two most common behaviors of input actuators in practical applications are hysteresis and dead-zone. In this paper, backlash-like hysteresis and dead-zone are used to model the input actuators. Using universal approximation theorem proved for neural networks, the unknown nonlinear functions are tackled. The unknown weights of neural networks are derived by proposing appropriate adaptive laws. To cope with modeling errors and disturbances an adaptive robust structure is proposed. Considering Lyapunov synthesis approach not only all the adaptive laws are derived but also it is proved that the closed-loop network is cooperatively semi-globally uniformly ultimately bounded(CSUUB). In order to investigate the effectiveness of the proposed method, it is applied to agents modeled with highly nonlinear mathematical equations and inverted pendulums. Simulation results demonstrate the effectiveness and applicability of the proposed method in dealing with both numerical and practical multi-agent systems.     

Generalized Consensus of Discrete-Time Multi-Agent Systems with Directed Topology and Communication Delay

Journal of Systems Science and Complexity - Compared with traditional consensus, this paper studies the generalized consensus problem for discrete-time multi-agent systems with directed topology...     

Stability Analysis and Group Consensus Tracking Predictive Control of Multi-Agent Systems

The issue of stability and group consensus tracking is investigated for the discrete-time heterogeneous networked multi-agent systems with communication constraints(e.g., time delays and data loss) in this paper. Firstly, the couple-group consensus tracking control is analyzed theoretically,the communication constraints are compensated by the prediction method, and the factor of leaders is introduced to make the system not lose generality. Secondly, the necessary and sufficient condition is give...     

Consensus for Heterogeneous Multi-Agent Systems with Directed Network Topologies

In this paper, the consensus problem for heterogeneous multi-agent systems composed of first-order and second-order agents is investigated with directed network topologies. Based on a system transformation method, this consensus problem is turned into a consensus problem for homogeneous multi-agent systems. With certain assumption on the control parameters, firstly, necessary and sufficient condition for consensus is proposed with fixed topology. Secondly, sufficient condition is proposed for heterogeneous multi-agent systems to achieve consensus with switching topologies. Finally, simulation examples are presented to verify the effectiveness of the theoretical results.     

离散异构多自主体系统时变输出编队跟踪控制

针对维数和参数都不同的离散异构多自主体系统,利用输出调节方法研究了系统的时变输出编队跟踪控制问题.假设多自主体系统由多个follower自主体和多个leader自主体组成,并且ollowe自主体不能得到leade自主体的状态信息,利用邻接信息针对每个ollowe自主体设计了分布式观测器.基于观测器的状态,利用状态反馈,...     

Global Output-Feedback Tracking for Nonlinear Cascade Systems with Unknown Growth Rate and Control Coefficients

This paper deals with the global practical tracking problem by output-feedback for a class of uncertain cascade systems with zero-dynamics and unmeasured states dependent growth.The systems investigated are substantially different from the closely related works,and have zero-dynamics,unknown growth rate,and unknown time-varying control coefficients.This makes the problem much more difficult to solve.Motivated by the authors' recent works,this paper proposes a new adaptive control scheme to achieve the global practical tracking.It is shown that the designed controller guarantees that the state of the resulting closed-loop system is globally bounded and the tracking error converges to a prescribed arbitrarily small neighborhood of the origin after a finite time.This is achieved by combining the methods of universal control and dead zone with backstepping technique,and using the framework of performance analysis in the closely related works.A numerical example demonstrates the effectiveness of the theoretical results.     

Predictive Event-Triggered Control for Disturbanced Wireless Networked Control Systems

The control and scheduling for wireless networked control system with packet dropout and disturbance are investigated. A prediction based event triggered control is proposed to reduce data transmissions while preserving the robustness against external disturbance. First, a trigger threshold is especially designed to maintain the difference of the estimated and actual states below a proper boundary when system suffers from packet dropout. Then a predictive controller is designed to compensate for packet dropouts by utilizing the packet-based control approach. The sufficient conditions to ensure the closed-loop system being uniformly ultimately bounded are derived, with consequently the controller gain method. Numerical examples illustrate the effectiveness of the proposed approach.     

未知非线性系统的神经网络跟踪控制与仿真研究

应用输入／输出反馈线性化方法和李亚普诺夫方法,研究了一类具有未知非线性函数的非线性动态系统的自适应鲁棒输出跟踪控制问题。首先通过坐标变换和输入变换,将非线性系统变换为部分线性可控系统。接着采用多层前向神经网络来逼近未知非线性函数,网络的权值根据李亚普诺夫原则来在线修正,这样就克服了多神经网络控制系统中存在的稳定性问题。同时,为了减少权值学习时间,应用遗传算法预先离线训练网络权值。最后提出了一个基于神经网络建模的自适应鲁棒控制律,给出了李亚普诺夫意义下的稳定性证明。所提出的控制律可确保相应闭环系统的状态及跟踪误差一致最终有界。所给的Van der pol系统的例子说明了所提控制方案的有效性与鲁棒性。     

非线性多智能体网络的分布式包容控制

针对具有本质非线性动态的多智能体网络,研究分布式包容控制问题.假设只有部分个体已知领航者信息,依据相对位置和速度信息设计分布式控制律.基于代数图论、矩阵理论和Lyapunov稳定性分析方法,得出非线性网络实现渐近包容控制的充分条件.当跟随者之间有向强连通且每个跟随者都至少存在一个领航者与其通信,可选取合适的控制增益使得跟随者渐近收敛到由多个领航者所围成的静态凸包中.仿真实例验证了理论分析的正确性和有效性.