Distributed Consensus Control Research Articles

Distributed Consensus Control of Vehicular Platooning Under Delay, Packet Dropout and Noise: Relative State and Relative Input-Output Control Strategies

In this article, we study the distributed control problem of vehicular platooning by taking into account network imperfections, namely the input delay and the packet dropout. The delay occurs within the inter network of each vehicle from its controller to its actuators and the packet dropout occurs within the intra network of vehicles when information is exchanged between vehicles. Relative state-feedback and relative input-output feedback control strategies are adopted for the vehicular platooning under network imperfection. To this end, and to avoid the requirement of relative state information, the relative state measurements are constructed for platoon systems based on a distributed observer via only relative input-output measurements and in the presence of delay, packet dropout and noise. Conditions for synchronization are provided in terms of the unique positive-definite solutions to some algebraic Riccati equations. Simulations validate the theoretical results.

Event-triggered adaptive sliding mode control for consensus of multiagent systems with unknown disturbances

In this paper, a novel robust distributed consensus control scheme based on event-triggered adaptive sliding mode control is proposed for multiagent systems with unknown disturbances in a leader-follower framework. First, an adaptive multivariate disturbance observer is utilized to compensate for the disturbance of each agent. Next, a distributed consensus control protocol is constructed via integral sliding mode control, in which a novel adaptive law is designed for the switching gain to overcome the unknown perturbations. An event-triggered strategy is designed to update the control input. Furthermore, the feasibility of the proposed scheme is rigorously analyzed by Lyapunov theory, and a lower bound expression for the inter-event time is derived to guarantee that Zeno behavior can be excluded. The proposed nonlinear consensus algorithm is remarkable in that it does not require any information about the bounds of the disturbances. Finally, compared with existing methods, the proposed algorithm is validated through detailed numerical simulations. In addition, the proposed algorithm is applied to a group of UAVs in this paper, and the results show that it has more application value.

Distributed consensus control of nonlinear multi‐agent systems with sensor uncertainty

AbstractThis article focuses on the distributed consensus control problem for nonlinear multi‐agent systems subject to sensor uncertainty. To be specific, we study nonlinear multi‐agent systems of lower or upper triangular structure with unknown growth rate and sensor uncertainty. A new time‐varying gain approach is proposed to construct observers as well as distributed output‐feedback controllers. By selecting suitable design parameters, the leader‐follower consensus of nonlinear multi‐agent systems is achieved. Different from the existing results, a time‐varying function in a logarithmic form is introduced to deal with unknown growth rate. Moreover, a monotonically increasing time‐varying function is constructed to cope with uncertain sensor sensitivity. Two simulation examples are provided to demonstrate the effectiveness of the proposed distributed consensus control algorithms.

Distributed event-triggered consensus control for multiple Euler–Lagrange systems with transmission delay under directed networks

This article addresses the distributed consensus control for multiple Euler–Lagrange systems under directed networks with time-varying transmission delays. Only some followers can access the information of the leader; communication is directed between agents. A distributed adaptive event-triggered control protocol is designed for the two cases where the generalized velocity of the leader is constant/time varying. When the generalized velocity of the leader is time varying, a distributed adaptive observer is designed to make followers obtain the time-varying information of the leader. Then, Lyapunov stability theory and the Linear matrix inequality algorithm prove the tracking errors can converge to zero in a completely distributed chattering-free manner. With the event-triggered mechanism, the number of communications can be decreased, and the system update frequency and the energy consumption can be reduced effectively. Meanwhile, the elimination of the Zeno behavior is also proved. Finally, the simulation results verify the effectiveness of the two controllers.

Distributed Consensus Based and Network Economic Control of Energy Internet Management

Energy internet (EI) was proposed to improve the utilization of multiple energy and meet the growing demand for energy. This paper proposes the distributed consensus control algorithm combined with a multi-agent system (MAS) which is applied to distributed generators in the energy internet. By selecting the incremental cost (IC) of each generation unit as the consensus variable, the algorithm is able to solve the conventional centralized economic dispatch (ED) problem in a distributed scheduling manner. The proposed algorithm is veriðed in the MAS layer and through a simulation model of the EI network in the MATLAB software. Simulation results conclude that incremental cost converges to its optimal value whether load demand is varying or generators plug-and-play. Distributed consensus control algorithm can provide better service for EI, it is immune to topological variations and accommodate desired plug-and-play features, and it enables real-time modeling and simulation of complex power systems.

Distributed model-free adaptive control for multi-agent systems with external disturbances and DoS attacks

This paper presents a distributed consensus control algorithm for nonlinear multi-agent systems (MASs) with external disturbances and denial-of-service (DoS) attacks. Modified dynamic linearization is proposed for the linear transformation of the MASs, and an extended discrete state observer (EDSO) improves their robustness. An attack compensation scheme eliminates the effects of DoS attacks. Based on the EDSO and the attack compensation scheme, a distributed model-free adaptive control (DMFAC) algorithm is developed to achieve consensus control in a boundary, and simulations verify its superiority in tracking time and tracking accuracy over other control algorithms.

Consensus Control of Highway On-Ramp Merging With Communication Delays

In the environment of intelligent and connected vehicles, the information sharing level among vehicles and infrastructure get comprehensively improved. Aiming at the cooperative merging control at highway ramp, we present a two-stage hybrid cooperative control framework considering communication time delays including centralized decision-making for grouping with sequencing and distributed consensus control. The centralized controller is based on a grouping strategy and a cost function for minimizing total travel time and delays and determining the optimal vehicle passage order. Then we model the merging vehicles formation as a multi-agent system, which also could be viewed as a distributed controlling system. Combining with the multi-agent consensus method, it could achieve the desired inter-vehicle distance and speed. The proof tool is the Lyapunov-Krasovskii stability theorem in terms of convergence and formation stability. Finally, we design three simulation scenarios through varying the number of vehicles. Meanwhile, in order to verify the resistance of the algorithm to communication time delays, three conditions with respect to no time delays, heterogeneous time delays, and homogeneous time delays are considered. Simulation result verifies the advantage of the proposed method compared with the Hamilton control method. The efficiency of the proposed method is impervious in three different types of communication time delays and has approximately 30%, 25%, 15% improvement over that of the Hamiltonian method, respectively. Furthermore, the adaptation and effectiveness of the proposed method is demonstrated under different volumes of traffic flow and communication delays.

Consensus Control in Heterogeneous Nonlinear Multiagent Systems With Position Feedback and Switching Topologies

The primary challenge in designing a consensus algorithm under switching topologies is to deal with discontinuous interactive information. At present, most consensus control results are limited to either agents with mismatched uncertainties in a time-invariant interaction environment or integrator dynamics in a dynamically changing interaction environment. This work addresses consensus problems of heterogeneous nonlinear multiagent systems without these limitations. We propose a novel, simple, yet effective higher-order filter to yield differentiable control variables employing neighbor position information and discontinuous topology information. By applying this filter and defining a suitable auxiliary error, we develop distributed consensus controllers for second-order and uncertain higher-order systems. One of the salient attributes of the proposed methodology is to allow each agent to require minimal local feedback, i.e., only the position information of itself and its neighboring agents. Theoretical and simulation verifications of the scheme guaranteeing asymptotic convergence of consensus and the boundedness of each signal in the closed-loop system are carefully examined.

Udwadia-Kalaba approach based distributed consensus control for multi-mobile robot systems with communication delays

In this paper, a distributed consensus algorithm for multi-mobile robot systems (MMRSs) with communication delays is proposed based on the Udwadia-Kalaba (UK) approach. The key feature of the proposed algorithm is that the consensus requirement is configured as a second-order constraint, and then a concise and explicit equation of motion for the constrained mechanical systems is formulated. Furthermore, the necessary and sufficient conditions for achieving the consensus of MMRSs with or without communication delays are developed under the network topology possessing a directed spanning tree. Finally, some numerical simulations are performed to verify the validity of the proposed consensus algorithm.

An AFD-Based ILC Dynamics Adaptive Matching Method in Frequency Domain for Distributed Consensus Control of Unknown Multiagent Systems

This paper is concerned with distributed consensus control of unknown multiagent systems. As the system’s dynamics is unknown, an adaptive Fourier decomposition (AFD) based iterative learning control (ILC) dynamics adaptive matching method in frequency domain is put forward to deal with it. First, large amounts of input and output measurement data are used to estimate the frequency domain characteristics of the system by Takenaka-Malmquist functions. Second, convert the traditional time domain ILC to the frequency domain to establish a matching relationship with the estimated frequency domain features. Then, an adaptive iterative learning rate is constructed to achieve the optimal convergence at each sampling point. The feasibility of the proposed algorithm is guaranteed by the convergence of AFD in Hardy space <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H^{2}(\mathbb {D})$ </tex-math></inline-formula> under the maximum selection principle. Compared with the reinforcement learning data-driven control scheme, the method proposed in this paper has obvious advantages in the control accuracy and convergence efficiency. In addition, this paper takes two kinds of denoising algorithms based on unwinding AFD to deal with the multi-agent systems with channel noise. Finally, the feasibility and effectiveness of the developed method are verified by a series of simulations.

Data-Based Optimal Consensus Control for Multiagent Systems With Policy Gradient Reinforcement Learning.

This article investigates the optimally distributed consensus control problem for discrete-time multiagent systems with completely unknown dynamics and computational ability differences. The problem can be viewed as solving nonzero-sum games with distributed reinforcement learning (RL), and each agent is a player in these games. First, to guarantee the real-time performance of learning algorithms, a data-based distributed control algorithm is proposed for multiagent systems using offline system interaction data sets. By utilizing the interactive data produced during the run of a real-time system, the proposed algorithm improves system performance based on distributed policy gradient RL. The convergence and stability are guaranteed based on functional analysis and the Lyapunov method. Second, to address asynchronous learning caused by computational ability differences in multiagent systems, the proposed algorithm is extended to an asynchronous version in which executing policy improvement or not of each agent is independent of its neighbors. Furthermore, an actor-critic structure, which contains two neural networks, is developed to implement the proposed algorithm in synchronous and asynchronous cases. Based on the method of weighted residuals, the convergence and optimality of the neural networks are guaranteed by proving the approximation errors converge to zero. Finally, simulations are conducted to show the effectiveness of the proposed algorithm.

Fuzzy Adaptive Optimal Consensus Fault-Tolerant Control for Stochastic Nonlinear Multiagent Systems

This article investigates the problem of adaptive fuzzy optimal distributed consensus control for stochastic multiagent systems (MASs) with full-state constraints and nonaffine nonlinear faults. Fuzzy logic systems are employed to identify the unknown nonlinearities. To solve the problem of optimal state constraint control, a barrier Lyapunov function based optimal cost function is designed. By introducing Butterworth low-pass filter into control design, the deleterious effects raised by nonlinear fault can be compensated. By utilizing adaptive dynamic programming algorithm in critic–actor construction, a fuzzy adaptive distributed optimal consensus fault-tolerant control method is proposed, which can ensure that all signals of the controlled system are semiglobally uniformly ultimately bounded in probability, and outputs of the follower agents keep consensus with the output of leader. In addition, system states are all not exceeded their constrained bound. Finally, simulation results are provided to illustrate the feasibility of the developed control method and theorem.

Distributed consensus control for networked Euler–Lagrange systems over directed graphs: A dynamic event‐triggered approach

AbstractThis paper considers the distributed dynamic event‐triggered consensus problem of multi‐agent systems with Euler–Lagrange dynamics over directed graphs in the presence of uncertain disturbances. To achieve consensus, a dynamic triggering law is designed such that consensus of reference model can be achieved. Different from the static triggering mechanism, an extra variable is involved in the proposed dynamic triggering law, which benefits the exclusion of the Zeno behavior. Then, an auxiliary variable is introduced to simplify agent dynamics, which benefits the controller design. Based on the auxiliary variable, a local controller is further proposed to guarantee the tracking ability of the auxiliary variable to the reference model. Owing to this treatment, consensus of agents can be reached in the presence of external disturbances. In addition, no continuous communication is needed in either controller updates or triggering detection. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed consensus protocol and its advantage in reducing the communication overhead compared with the relevant static triggering mechanism.

Distributed Control of Discrete-Time Linear Multi-Agent Systems With Optimal Energy Performance

This paper investigates the leader-based distributed optimal control problem of discrete-time linear multi-agent systems (MASs) on directed communication topologies. In particular, the communication topology under consideration consists of only one directed spanning tree. A distributed consensus control protocol depending on the information between agents and their neighbors is designed to guarantee the consensus of MASs. In addition, the optimization of energy cost performance can be obtained using the proposed protocol. Subsequently, a numerical example is provided to demonstrate the effectiveness of the presented protocol.

H∞ smooth switching distributed consensus controller for uncertain time-delay switched LPV multi-agent systems

This paper presents an approach to design [Formula: see text] smooth switching distributed linear parameter-varying (LPV) controller for consensus of LPV multi-agent systems (MASs) with a large range of parameter variations, uncertainty, input disturbance, and time-varying delay. By dividing the region of variable parameters into subregions with overlaps, a [Formula: see text] smooth switching distributed sliding mode LPV controller with a switched dynamic sliding surface is designed for each subregion and the controller in overlapping subregions is interpolated from two adjacent subregions. This control problem is formulated into parametric linear matrix inequality (LMI), which is solved by convex optimization algorithms. To illustrate the efficacy of the result, it is applied to consensus of practical vertical take-off and landing (VTOL) helicopter MAS.

Fully Distributed Consensus Control for Linear Multiagent Systems With Dynamic Double-Event-Triggered Mechanism

This brief studies the fully distributed consensus control problem for linear multiagent systems (MASs) with a novel dynamic double-event-triggered mechanism (DDETM). The proposed DDETM can not only reduce the resource consumption of communication, but also reduce the frequency of controller update. Meanwhile, larger triggering time intervals are obtained by introducing two sets of dynamic variables in DDETM compared with the static double-event-triggered mechanism (SDETM). Then a fully distributed DDETM-based control protocol is designed, which is independent of any global information. Next, rigorous proofs are given to assure the realization of consensus control and the exclusion of Zeno behavior. Finally, an illustrative example is presented to verify the proposed protocol.

A New Method to Design Distributed Consensus Controller for Linear Multi-Agent Systems With Directed Graphs

The consensus control of second-order linear multi-agent systems with velocity constraint under directed graphs is investigated. In this brief, a new distributed sliding mode control scheme is proposed. The novelty of this scheme is that we integrate the logarithmic barrier function with the sliding surface, then the consensus is achieved by showing the convergence of the sliding variable to zero, meanwhile, the boundedness of the sliding variable indicates the velocity constraint is satisfied. With the proposed method, the semi-global consensus control of second-order linear multi-agent systems with velocity constraints can be easily achieved under directed graph. The effectiveness of the results is illustrated through a numerical example.

Distributed Dynamic Event-triggered Consensus Control for Multiple Euler-Lagrange Systems under Digraphs

In this paper, the distributed consensus control of multiple Euler-Lagrange dynamics under digraphs via the dynamic event-triggering mechanism is studied. By designing the upper-level reference model and introducing an auxiliary variable, a novel distributed dynamic event-triggered consensus control protocol is proposed, which allows to separate neighboring information interaction from local dynamics control and thus simplifies the design process. Owing to this treatment, consensus of agents can be reached without continuous state transmission and Zeno behavior. Finally, numerical simulation is given to illustrate the effectiveness of theoretical results.

Resilient Distributed Multiagent Control for AC Microgrid Networks Subject to Disturbances

In actual microgrids (MGs) networks, the information exchange between distributed energy resources (DERs) agents may be subject to various types of measurement noises and effected by communication time delays. This article proposes a resilient distributed multiagent control scheme for ac MG networks subject to additive noise and time-delay disturbances. The proposed multiagent control scheme is composed of three distributed consensus protocols, which is able to synchronize the output voltages and frequencies of inverter-based DERs to their reference values and achieve the optimal active power-sharing property by a low bandwidth communication network with noise and time-delay disturbances in almost sure convergence. By means of the stochastic analysis tools and algebraic graph theory, distributed consensus control protocols are designed to be employed for the secondary control level of MGs. On this basis, we deduce the stability criteria of the closed-loop MG system under noise and time-delay disturbances. As a result, the proposed consensus protocols can well restore the voltage and frequency’s derivation produced at the primary control level, meanwhile, can well achieve the optimal power sharing even though there exist communication disturbances. Several simulation scenarios on an islanded MG network are provided to verify the proposed control protocols’ performance.

Distributed Consensus Control of Networked Robotic Systems With Dynamic Leader Under Time-Varying Delays and Denial-of-Service Attacks

Consensus of multi-agent systems has a wide range of applications, such as coordination, cooperative transportation, and synchronization. This study investigates consensus control in the task space of multi-robotic systems modeled using Euler-Lagrange equations with a moving leading under time-varying delays and denial-of-service (DoS) attacks, respectively. Two control algorithms are studied when networked robotic systems are interconnected over directed spanning trees with a constant-velocity leader as the root. First, we use the Lyapunov-Razumikhin theorem to address a condition of the maximum time delay for nonuniform time-delay communication, thereby ensuring asymptotic tracking of the network. Second, we propose a novel resilient control framework to deal with DoS attacks. Note that designing the control algorithm for DoS attacks is difficult because the attacks cause signal discontinuity. The proposed resilient controller can release the DoS duration condition, which is a common requirement in many related works. It is verified that the consensus errors converge to the origin under the proposed control frameworks. We present experimental results to demonstrate the effectiveness of the proposed controllers.