Adaptive Control Protocol Research Articles

Cooperative control of mixed vehicle platoon based on pinning consensus of heterogeneous multi‐agent system

AbstractThis paper proposes a longitudinal controller for the mixed vehicle platoon in the presence of driver response time‐delay and communication time‐delay based on the pinning consensus of heterogeneous multi‐agent system. Firstly, an adaptive pinning consensus control protocol and derive sufficient conditions for the heterogeneous non‐linear multi‐agent system are designed to achieve pinning consistency. Then, the heterogeneous characteristics of the vehicle are described based on the car‐following model, then the mixed vehicle platoon system model is constructed and a mixed vehicle platoon controller based on heterogeneous multi‐agent pinning consensus is proposed. Besides, the driver response time‐delay and communication time‐delay are introduced into the model, and a controller based on time‐delay heterogeneous multi‐agent pinning consensus is designed. Finally, the effectiveness of the proposed controller is verified by numerical simulations, and the effect of number of connected autonomous vehicle, different types of vehicle order, driver response time‐delay, communication time‐delay and the parameter of the controller on stability of mixed vehicle platoon is also quantitatively demonstrated.

Optimization Algorithm of Network Node Layout of Fresh Agricultural Products’ Online Consumption Behavior in E-Commerce Environment

In order to improve the efficiency of online consumption and supply chain efficiency of fresh agricultural products in the e-commerce environment, a network node layout optimization algorithm was designed. In the e-commerce environment, a network node deployment model has been constructed for the online consumption behavior of fresh agricultural products. A network transmission supply chain detection model was established through the rotation scheduling method. By combining distributed transformation protocols, the spatial layout characteristics of network nodes have been reorganized. Further introduction of a multi-coverage scheduling model, combined with sensor information fusion tracking technology, accurately detects the layout characteristics of network nodes. Based on these detection data, forwarding and adaptive control protocols were developed. Real-time control using the node traversal method was developed. Under the optimal node supply chain transmission mechanism, the scheduling of the network node layout has been achieved. Meanwhile, convolutional neural networks were utilized to dynamically adjust layout control to ensure convergence and stability. The simulation results show that the node forwarding ability of the network node layout design for online consumption behavior of fresh agricultural products in the e-commerce environment is good, which improves the output balance of the network supply chain transmission of online consumption behavior of fresh agricultural products in the e-commerce environment. In addition, the optimized delivery cost decreased by 20% compared to before optimization, delivery efficiency increased by 30%, and inventory turnover rate increased by 25%, confirming that the proposed method has good optimization performance.

Fixed-time consensus and finite-time flocking of second-order nonlinear multi-agent systems under false data injection attacks

This paper focuses on addressing consensus and flocking issues in second-order nonlinear multi-agent systems (MASs) under the false data injection attacks. Novel adaptive control protocols are proposed to effectively mitigate the impact of these attacks by updating adaptive parameters. Based on algebraic graph theory, matrix theory and the Lyapunov approach, various sufficient conditions are established, which show the fixed-time consensus and finite-time flocking can be achieved for the MASs. Moreover, some upper bounds for the settling time are derived in terms of the parameters of the model. Finally, three simulation examples are presented to validate the efficacy of our proposed theoretical results.

Dynamic event-triggered quantized secure output consensus of heterogeneous multi-agent systems under DoS attacks.

This paper investigates secure output consensus problem of heterogeneous multi-agent systems (HMASs) under denial-of-service (DoS) attacks. First, an adaptive dynamic compensator depending on local measurement information is designed for tracking the signal of the virtual exosystem. Second, for mitigating network communication load, a novel adaptive control protocol is developed by introducing dynamic event-triggered control and quantized control strategies. Moreover, Zeno behavior can be eliminated under the proposed scheme. Third, the secure output consensus of HMASs under DoS attacks can be guaranteed by satisfying the designed sufficient conditions. Finally, simulation is shown to verify reliability of the proposed control protocol and theory.

Distributed adaptive tracking consensus control for a class of heterogeneous nonlinear multi-agent systems

The proposed approach differs from existing works in that it models the constraints of each follower as a nonlinear strict feedback system, rather than relying on a desired reference trajectory for accessible subsystems. To address the limitations caused by uncertain terms in systems, radial basis functions neural networks are utilized to compensate for these unknown nonlinear terms. This leads to a novel distributed adaptive consensus tracking control protocol for high-order nonlinear heterogeneous multi-agent systems, based on the backstepping technique. By introducing a non-zero parameter in the traditional radial basis functions neural network, a new universal approximation is constructed, which overcomes the limitation of the approximation’s finite domain. Additionally, the approximation precision can be adjusted online using provided laws, and the dimension explosion of virtual and real control gains can be avoided through the use of the designed control approach. Simulation results are provided to demonstrate the effectiveness of the proposed control scheme.

K-filter-based distributed adaptive bipartite tracking for nonlinear multi-agent systems with unknown control direction

This paper investigates K-filter-based distributed adaptive output-feedback bipartite tracking problem for multi-agent systems with unknown control direction. The agents are partitioned into two groups, where agents belonging to the same group are cooperative while agents belonging to the distinct group are competitive. Firstly, the unmeasurable state variables of the system under unknown control direction are estimated through K-filters. Then, a neighbourhood error is introduced to transform a structurally balanced network into a cooperative network. Based on K-filters, neighbourhood error, Nussbaum-type functions and dynamic surface control, a distributed adaptive output-feedback control protocol is designed to achieve the bipartite tracking. It is shown that all signals in the resulting closed-loop systems are semi-global bounded and the output of each agent can track the reference signal provided that the network is structurally balanced and contains a directed spanning tree. Finally, a numerical example is given to verify the effectiveness of the proposed method.

Distributed resilient adaptive consensus tracking control of nonlinear multi-agent systems dealing with deception attacks via K-filters approach

It poses technical difficulty to achieve distributed consensus tracking control with input quantizations and deception attacks for nonlinear multi-agent systems subject to mismatched parametric uncertainties via backstepping design. The underlying problem becomes even more complicated because i) the system contains mismatched uncertainties; ii) the output becomes unavailable after attacks, making the conventional recursive control design strategy using traditional error surfaces unsuitable; iii) since only the compromised output signal is available, the impacts of nonlinear items related to unknown attack weights become difficult to be explicitly addressed in the existing available output feedback control results. In this paper, we present a solution to circumvent these obstacles by constructing a set of new K-filters using compromised output only, which, together with a coordinate transformation involving the attacked output and filter variables, allow a new form of backstepping based distributed resilient adaptive control protocol to be developed. Meanwhile, an extra compensation term is incorporated into the real controller to handle the effect of quantization on the system stability. It is shown that, with proper choices of Lyapunov functions, the global uniform boundedness of all the closed-loop signals and the asymptotically output consensus tracking can be achieved. A practice example is provided to verify the benefits of our scheme.

Fully distributed adaptive consensus tracking for uncertain multi-agent systems

This work discusses the adaptive consensus tracking for first-order and second-order uncertain multi-agent systems (UMASs). The systems allow multiple uncertainties, including unknown control directions, parameterized unknown nonlinearities, and unknown external disturbances. To compensate for these uncertainties, two novel distributed adaptive control protocols with the dynamic compensation based on Nussbaum-type gain are proposed for first-order and second-order UMASs, respectively. Remarkably, the control protocol is devised in a fully distributed fashion, which is not dependent on the global information of communication graph. Then, under undirected connected graph, it is proved that the proposed control protocol can guarantee the boundedness of all signals in the closed-loop system and the achievement of the consensus tracking (CT). Finally, the theoretical results are validated by two simulation examples.

Adaptive fixed-time fuzzy containment control for uncertain nonlinear multiagent systems with unmeasurable states

This paper addresses the adaptive fixed-time fuzzy containment control for uncertain nonlinear multiagent systems, where the states and nonlinear functions are not feasible for the controller design. To address the issue of unmeasurable states, a state observer is developed, and fuzzy logic systems are utilized to approximate unknown nonlinear functions. Under the framework of fixed-time Lyapunov function theory and cooperative control, an adaptive fixed-time fuzzy containment control protocol is derived via the adaptive backstepping and adding one power integrator method. The derived fixed-time containment controller can confirm that the closed-loop systems are practical fixed-time stable, which implies that all signals in the systems are bounded and all follower agents can converge to the convex hull formed by the leader agents within fixed-time in the presence of unmeasurable states and unknown nonlinear functions . Simulation examples are conducted to test the validity of the present control algorithm.

Observer-based consensus control for a class of nonlinear singular multi-agent systems

This paper studies the bounded consensus control problem for nonlinear singular multi-intelligence systems (NSMASs) based on observers, where the structure of nonlinear dynamics is completely unknown. Firstly, the unknown nonlinear terms are estimated by the linear parameterization method. However, since the system state is not directly available, the observers are used for state estimations, which leads to a double estimation problem in the parameterization process. Moreover, the distributed adaptive control protocols and the adaptive laws of unknown parameter estimations are developed in the leader-following and leaderless frameworks. Furthermore, the proposed control protocols achieve bounded consensus for the NSMASs. And the proposed nonlinear estimation methods guarantee bounded estimation performance of the unknown nonlinear terms in the double estimation problem. Finally, two examples are given to illustrate the effectiveness of the proposed methods.

Performance-Based Distributed Control of Multiagent Systems: A Dual Phase Approach.

In this article, we investigate the distributed tracking control problem for networked uncertain nonlinear strict-feedback systems with unknown time-varying gains under a directed interaction topology. A dual phase performance-guaranteed approach is established. In the first phase, a fully distributed robust filter is constructed for each agent to estimate the desired trajectory with prescribed performance such that the control directions of all agents are allowed to be nonidentical. In the second phase, by establishing a novel lemma regarding Nussbaum function, a new adaptive control protocol is developed for each agent based on backstepping technique, which not only steers the output to track the corresponding estimated signal asymptotically with arbitrarily prescribed transient response but also extends the application scope of the proposed control scheme largely since the unknown control gains are allowed to be time-varying and even state-dependent. In such a way, the underlying problem is tackled with the output tracking error converging into an arbitrarily preassigned residual set exhibiting an arbitrarily predefined convergence rate. Besides, all the internal signals are ensured to be semi-globally ultimately uniformly bounded (SGUUB). Finally, two examples are provided to illustrate the effectiveness of the co-designed scheme.

Data-driven leader-following consensus for nonlinear multi-agent systems against composite attacks: A twins layer approach

This paper studies the leader-following consensuses of uncertain and nonlinear multi-agent systems against composite attacks (CAs), including denial of service (DoS) attacks and actuation attacks (AAs). A double-layer control framework is formulated, where a digital twin layer (TL) is added beside the traditional cyber–physical layer (CPL), inspired by the recent Digital Twin technology. Consequently, the resilient control task against CAs can be divided into two parts: One is distributed estimation against DoS attacks on the TL, and the other is resilient decentralized tracking control against actuation attacks on the CPL. First, a distributed observer based on switching estimation law against DoS is designed on TL. Second, a distributed model-free adaptive control (DMFAC) protocol based on attack compensation against AAs is designed on CPL. Moreover, the uniformly ultimately bounded convergence of consensus error of the proposed double-layer DMFAC algorithm is strictly proved. Finally, the simulation verifies the effectiveness of the resilient double-layer control scheme.

Designing adaptive continuous event-triggered consensus protocol for nonlinear multi-agent systems with a nonautonomous leader

This article investigates the leader-follower consensus (LFC) issue for a class of Lipschitz-type nonlinear multi-agent systems (NMASs) that include one leader and multiple followers. To enable the leader to denote a flexible noncooperative reference trajectory, it is considered that the leader's control input (LCI) exists and cannot be obtained by other followers. A novel robust distributed adaptive continuous event-triggered control protocol is developed. Through rigorous analysis, it is shown that under this control protocol, the NMASs can reach LFC and the Zeno behavior is not exhibited. Compared to existing research works, the main merits of this control protocol are as follows: 1) It is chattering-free while can completely eliminate the adverse effects brought by the LCI; 2) The communication traffic between agents is lower; 3) It can be executed in a fully distributed way (i.e., no global information is required for the design process of this control protocol). Finally, the effectiveness of the developed control protocol is validated through an example.

Adaptive containment control for heterogeneous MASs with unknown leaders and actuator failures

This paper investigates the containment control problem for heterogeneous multi-agent systems with unknown leaders and actuator failures. The dynamics of the leaders are unavailable to all followers and the measurable information of leaders is available to some followers. A model-free adaptive observer for each follower is proposed to estimate the convex hull of the leaders states and the dynamic knowledge of the unknown leaders. The followers may be affected by the actuator failures. Based on the adaptive observer and the adaptive solution of the output regulation equation, an adaptive fault-tolerant control protocol is designed to mitigate the impact of actuator failure on containment performance such that the output containment errors are ultimately uniformly bounded. Two simulation examples are provided to demonstrate the feasibility of the presented control scheme.

Adaptive consensus control of uncertain nonlinear multi-agent systems with communication delays and relative output information

This paper explores the challenges of distributed adaptive consensus control problems in nonlinear multi-agent systems with unknown parameters and communication delays. To address these issues, a novel backstepping-based adaptive state feedback control protocol is proposed by utilizing a reference dynamic system. Furthermore, an output-feedback consensus control algorithm incorporating a state observer is introduced. Through the application of Laplace transformation, matrix properties, and graph theory, it is demonstrated that the closed-loop multi-agent system ensures the boundedness of all signals and achieves output consensus, even in the presence of nonuniform communication delays. Numerical simulations on a group of inverted pendulums illustrate the effectiveness of these algorithms.

Attack reconstruction‐based resilient consensus tracking for multi‐agent systems with distributed adaptive control protocol

AbstractThis article considers the distributed secure consensus tracking control problem for multi‐agent systems (MASs) with relative output information. To tackle the potential false‐data‐injection (FDI) attacks on both the communication between physical components and the control center at the agent level, as well as the message transmission between connected agents, local sliding mode observers (SMO) and distributed observers are proposed for each agent. By introducing reconstructed signals for attacks and smooth terms to compensate the unknown input in the leader agent's dynamics, a distributed adaptive consensus protocol with relative output information is proposed. The closed‐loop stability is analyzed by introducing a novel Lyapunov function. It is shown that all closed‐loop signals are globally uniformly bounded and asymptotically consensus tracking can be achieved. Simulation results are provided to validate the theoretical findings.

Interleaved Periodic Event-Triggered Communications-Based Distributed Formation Control for Cooperative Unmanned Surface Vessels.

This article addresses the distributed formation control issue of cooperative unmanned surface vessels (USVs) under interleaved periodic event-triggered communications. First, an adaptive event-based control protocol is designed, where the event-based neural network (NN) scheme is developed to compensate for uncertain model dynamics. Upon the designed control protocol, an interleaved periodic event-triggered mechanism (IPETM) is subsequently proposed to achieve the communication objective. Unlike the common continuous event-triggered methods and periodic event-triggered methods, in which multiple nodes are allowed to trigger their events at the same time, the proposed IPETM ensures that USVs detect their events at different times to avoid the simultaneous event triggering of different nodes. By this virtue, traffic jamming in common wireless environments can be prevented, such that potential communication delays and faults are naturally avoided. In addition, the event detecting instants of the presented IPETM are also discrete and periodic, such that it can be performed under low-computational frequencies. Through Lyapunov-based analysis, it is verified that all closed-loop signals can converge to an arbitrary small compact set with exponential convergence rates. Simulation results demonstrate the effectiveness and superiority of the proposed control scheme.

A New Event-Triggered Adaptive Fixed-Time Control Design for Uncertain Nonlinear Systems.

This article investigates the problem of dynamic memory event-triggered (DMET) fixed-time tracking control within time-varying asymmetric constraints for nonaffine nonstrict-feedback uncertain nonlinear systems with unmodeled dynamics and unknown disturbances. The existing dynamic event-triggered control methods cannot handle the nonlinear systems with unmodeled dynamics and nonaffine inputs, which greatly limits the applicability of the strategy. To this end, a novel DMET adaptive fuzzy fixed-time control protocol is constructed based on the idea of command filtered backstepping, in which a new dynamic signal function is established to deal with the unmodeled dynamics and an improved DMET mechanism (DMETM) is designed to solve the problem of nonaffine inputs. It is proved that the newly DMET control strategy ensures the tracking error converges to an arbitrarily small compact set in a fixed time and all the signals of the closed-loop systems are bounded. The effectiveness of the proposed approach is demonstrated by two simulation examples.

Fuzzy tracking control of singular multi-agent systems under switching topology

<p>The consensus tracking problem of leader-follower multi-agent systems (MASs) with singular structures on jointly connected topology is studied in this paper. To achieve the objective of consensus tracking, a distributed adaptive control protocol is formulated to adjust the coupling weights among the agents using the adaptive rate, where the adaptive protocol can be implemented by each agent in a fully distributed manner without using any global information. A fuzzy logic system method is used to deal with the nonlinear terms in response to the limitations of nonlinear system analysis. The consensus tracking problem is transformed into an error system stability analysis, and two sufficient conditions are provided to guarantee the control objective based on Lyapunov stability theory and singular system theory. Finally, the effectiveness of this method is verified through a simulation example.</p>

Robust [formula omitted] synchronization for parabolic complex networks with coupling time-varying delays

This paper delves into the robust H∞ synchronization for diffusion-type parabolic complex networks (PCNs) characterized by second-order nonlinear partial differential equations (PDEs). Given that the potential deterioration of network performance or the loss of network synchronization caused by external disturbances and time delays, the analysis and synthesis results for the robust H∞ synchronization of the PCNs with coupling time-varying delays are derived with and without the utilization of the distributed adaptive state feedback control protocol. A numerical example is employed to validate the effectiveness of the acquired H∞ synchronization results and the adaptive protocol.