Finite-time Consensus Tracking Research Articles

Adaptive finite-time consensus tracking for nonlinear second-order multi-agent systems based on integral sliding mode

This paper delves into the investigation of finite-time consensus for second-order nonlinear multi-agent systems (MASs) with external disturbances under directed topology. The MASs considered in this study consist of n followers and a leader, and the followers are subject to bounded disturbances. First, a continuous nonsingular integral terminal sliding mode is designed, which can effectively eliminate the singularity and chattering. Then, a finite-time disturbance observer is introduced to estimate and compensate for disturbances. Subsequently, an integral sliding mode adaptive controller is designed to enhance system’s robustness, improve response speed, and increase tracking accuracy. Furthermore, Lyapunov theory is utilized to demonstrate that the system achieves finite-time consensus under a directed connected topology. Finally, we apply a simulation to verify the efficacy of the proposed consensus control protocol.

Adaptive Finite-Time Consensus Tracking Control for Nonlinear Multi-Agent Systems: An Improved Tan-Type Nonlinear Mapping Function Method

Adaptive Finite-Time Consensus Tracking Control for Nonlinear Multi-Agent Systems: An Improved Tan-Type Nonlinear Mapping Function Method

Finite-time and Fixed-time Bipartite Consensus Tracking for Second-order Multi-agent Systems via an Integral Sliding-mode Approach

Finite-time and Fixed-time Bipartite Consensus Tracking for Second-order Multi-agent Systems via an Integral Sliding-mode Approach

Finite-Time and Fixed-Time Consensus Tracking of Multiple Euler–Lagrange Systems via Hierarchical Control Approach

Finite-Time and Fixed-Time Consensus Tracking of Multiple Euler–Lagrange Systems via Hierarchical Control Approach

Adaptive command-filtered finite-time consensus tracking control for single-link flexible-joint robotic multi-agent systems

This article presents a command-filtered finite-time consensus tracking control strategy for the considered single-link flexible-joint robotic multi-agent systems. First, each agent system considered in this article is a nonlinear nonstrict-feedback system with unknown nonlinearities, so the traditional backstepping method cannot be directly applied to the design controller. However, by applying the unique structure of the Gaussian function in radial basis function neural networks, the challenges in controller design caused by the aforementioned nonstrict-feedback system have been overcome. Second, the problem of unknown nonlinearities in the system is solved by the approximation property of radial basis function neural network technology. In addition, the traditional backstepping approach often leads to an “explosion of complexity” resulting from repeated derivation of virtual control signals. Our design addresses this issue by employing command filtering technology, which simplifies the controller design process. Meanwhile, new compensation signals are designed, which successfully eliminate the error influence posed by the filters. It is seen that the control strategy presented in this article can guarantee the tracking errors converge to a small neighborhood of origin in a finite time, and all signals in the closed-loop systems remain bounded. Eventually, the simulation results show the validity of the acquired control scheme.

Event-Based Finite-Time Control for Nonlinear Multiagent Systems With Asymptotic Tracking

In this paper, an adaptive neural finite-time event-triggered consensus tracking problem is studied for nonlinear multi-agent systems (MASs) under directed graphs. Firstly, the unknown nonlinear functions of MASs can be approximated by neural networks. Then, a distributed adaptive event-triggered control (ETC) scheme is proposed via command filter and backstepping technique. The newly designed control scheme can not only circumvent the problem of the explosion of complexity, but also remove the singularity issue typical of conventional backstepping technique. In the meanwhile, an event-triggered mechanism with a dynamic threshold is devised to reduce the waste of network resources. Moreover, by using a novel finite-time stability criterion, it can be proved that the closed-loop system is finite-time stable and the consensus tracking errors can reach zero as time approaches to infinity. Finally, a numerical example is given to validate the feasibility of the proposed scheme.

Fixed-time consensus of second-order multi-agent systems with nonlinear dynamics

The authors mainly discuss finite-time tracking consensus and fixed-time tracking consensus of multi-agent systems for second-order with inherent nonlinear function and disturbance under a directed interaction graph in this work. By sliding mode control theory, consensus tracking controllers are proposed to ensure that sliding mode can be reached and maintain on it in finite time and fixed time. By using some theoretical knowledge of control, such as graph theory and Lyapunov theory, we make the system to reach consensus in finite time and fixed time by choosing the right parameters. In addition, the calculation leads to the conclusion that settling time of finite-time consensus is associated to initial state, while settling time of fixed-time consensus is interrelated to parameters but not to the initial state. The feasibility of the theory is proved by simulation experiments.

Finite-time group-bipartite consensus tracking for second-order nonlinear multi-agent systems

In this paper, the finite-time group-bipartite consensus problem for nonlinear second-order multi-agent systems (MASs) is studied. By designing the control protocol, based on the proof of the system reaching asymptotically group-bipartite consensus, the homogeneous dilation method is used to obtain sufficient conditions for all agents to reach the finite-time group-bipartite consensus. Moreover, nonlinear functions are constrained by the Lipschitz condition. In addition, two examples demonstrate the operability of the control protocol.

Sliding mode-based finite-time consensus tracking control for multi-agent systems under actuator attacks

Since it is inevitable for multi-agent systems (MASs) to encounter external malicious attack in the complex network environment, this paper studies the finite-time consensus tracking (FTCT) problem of MASs with unknown follower's states via sliding mode control (SMC) in the presence of actuator attacks. First, the states of each follower can be approximated by the designed appropriate observers. Then, the FTCT problem of MASs in two stages (i.e., reaching phase and sliding motion phase) of sliding mode dynamic is discussed by introducing partitioning strategy. Besides, the lower bound for the reaching phase is analyzed to ensure the feasibility of the designed SMC. The optimization problem is then formulated and is efficiently solved by the genetic algorithm (GA). Note that the attacks considered in this paper are false data injection attacks (FDIAs). Finally, simulation results are presented to illustrate the effectiveness and applicability of the proposed control method.

Distributed Finite-Time Consensus Tracking Control for Nonlinear Multi-Agent Systems With FDI Attacks and Application to Single-Link Robots

This brief considers the distributed finite-time consensus tracking control problem for nonlinear multi-agent systems with false data injection (FDI) attacks. Firstly, since instability is inevitable when false datas are injected into the researched system, a security control algorithm combining the modified coordinate transformation and the dynamic surface control (DSC) method is developed to eliminate the negative impact of FDI attacks and reduce the burden caused by iterative computations of virtual controls. Besides, there are unknown nonlinearities in the dynamics of each agent, which can not be directly handled by the traditional control design. Thus, the neural-network-based approximation technique is introduced to compensate the unknown nonlinearities. In summary, a novel controller is constructed for each agent, which guarantees the consensus of the outputs of all agents can be achieved and that all the signals of the studied system are bounded within a finite-time period. To prove the correctness of the designed security control algorithm, a simulation example of the multi-agent system composed of multiple single-link robots is presented.

Adaptive Fuzzy Output-Feedback Consensus Tracking Control of Nonlinear Multiagent Systems in Prescribed Performance.

This article addresses the finite-time consensus tracking control problem for nonlinear multiagent systems (MASs), in which state variables are unmeasured and nonlinear functions are totally unknown. An observer is designed to estimate state variables and fuzzy-logic systems are employed to approximate nonlinearities. Then, an observer-based adaptive fuzzy consensus tracking controller is developed by using the backstepping technique and constructing a novel barrier Lyapunov function with the consideration of the characteristics of MASs. The proposed control protocol can guarantee that: 1) all signals in the closed-loop system keep bounded and 2) the consensus tracking error converges to a prespecified region of the origin in the prescribed finite time. Compared with the existing observer-based finite/fixed-time control protocols, the settling time and the convergence region in our work can be both preassigned by the designer and not affected by the unknown positive constant, which lies in the Lyapunov derivative inequality. Finally, two comparison simulation examples, including a numerical example and a practical example, check the availability of the designed control scheme.

Distributed finite-time neural network observer-based consensus tracking control of heterogeneous underwater vehicles

This note scrutinizes the distributed finite-time tracking problem of heterogeneous multi-agent systems with uncertain dynamics and environmental disturbances. To estimate the exogenous disturbances, an adaptive neural network-based disturbance observer is developed in which the approximation error of the neural network is compensated using adaptation laws. Based on finite-time stability theory, a distributed finite-time observer is proposed for each follower in order to estimate the leader's position. Moreover, an adaptive dynamic sliding mode-based controller is also developed for each follower, which ensures finite-time convergence of the tracking error between the leader and the follower. Incorporating adaptive control into the developed composite control structure leads to reducing the chattering, as well as enhancing the robustness and accuracy. Stability analysis and finite-time convergence of the tracking error are performed using the Lyapunov theory and multiple time scale principle, respectively. Finally, simulations and comparisons are performed in order to verify the effectiveness of the developed control algorithm for a group of autonomous underwater vehicles (AUVs).

Adaptive Fuzzy Finite-Time Fault-Tolerant Consensus Tracking Control for High-Order Multiagent Systems With Directed Graphs.

This article investigates the distributed adaptive fuzzy finite-time fault-tolerant consensus tracking control for a class of unknown nonlinear high-order multiagent systems (MASs) with actuator faults and high powers (ratio of positive odd rational numbers). The fault models include both loss of effectiveness and bias fault. Compared with existing similar results, the MASs considered here are more general and complex, which include the special case when the powers are equal to 1. Besides, the functions in this article are completely unknown and do not need to satisfy any growth conditions. In the backstepping framework, an adaptive fuzzy fault-tolerant consensus tracking controller is designed via adding one power integrator technique and directed graph theory so that the controlled systems are semiglobal practical finite-time stability (SGPFTS). Finally, numerical simulation results further verify the effectiveness of the developed control scheme.

Adaptive Fuzzy Command Filtered Finite-Time Tracking Control for Uncertain Nonlinear Multi-Agent Systems with Unknown Input Saturation and Unknown Control Directions

This paper investigates the finite-time consensus tracking control problem of uncertain nonlinear multi-agent systems with unknown input saturation and unknown control directions. An adaptive fuzzy finite-time consensus control law is proposed by combining the fuzzy logic system, command filter, and finite-time control theory. Using the fuzzy logic systems, the uncertain nonlinear dynamics are approximated. Considering the command filter and backstepping control technique, the problem of the so-called “explosion of complexity” in the design of virtual control laws and adaptive updating laws is avoided. Meanwhile, the Nussbaum gain function method is applied to handle the unknown control directions and unknown input saturation problems. Based on the finite-time control theory and Lyapunov stability theory, it was found that all signals in the closed-loop system remained semi-global practical finite-time stable, and the tracking error could converge to a sufficiently small neighborhood of the origin in the finite time. In the end, simulation results were provided to verify the validity of the designed control law.

Adaptive Fuzzy Finite-Time Consensus Tracking for High-Order Stochastic Multi-agent Systems with Input Saturation

Adaptive Fuzzy Finite-Time Consensus Tracking for High-Order Stochastic Multi-agent Systems with Input Saturation

Nonlinear finite-time and fixed-time bipartite consensus tracking of multi-agent systems

ABSTRACT This paper deals with the finite-time and fixed-time bipartite consensus tracking (FFBCT) problems for multi-agent systems (MASs) , in which both cooperative and competition exist. Using Lyapunov stability methods, distributed nonlinear protocols are provided to ensure all agents reach agreement. Its absolute value is the same but it might be different in direction. Besides, the second protocol can make the system reach bipartite consensus in fixed time regardless of the initial state of agents. Moreover, boundaries for settling times are estimated. Some numerical examples are finally presented to prove the validity of our designs.

Finite-Time Consensus Tracking Control for Speed Sensorless Multi-Motor Systems

Considering the unknown compound interference in manufacturing systems, the finite-time tracking and synchronization performance of the multi-motor system significantly affects the production safety, reliability, and quality, which can be considered a multi-agent system with unmeasured speed and uncertainty. In recent years, the synchronous control schemes of the multi-motor system have grown to maturity, but the research on the speed sensorless finite-time consensus tracking control remains to be extended. This paper proposes an observer-based leader–follower consensus tracking control for the synchronous coordination control of the multi-motor system. The speed and position of all motors can be tracked by consensus in a finite time when only some motors realize partial interaction. First, a finite-time observer is designed to estimate the unknown composite disturbance and unmeasurable speed variable of each motor. Second, the distributed finite-time consensus tracking control protocol is designed using the observed value and local information interaction. The stability of the overall closed-loop system is theoretically analyzed based on Lyapunov theory and graph theory, which shows that the consensus tracking error converges to an arbitrary small neighborhood of zero, and all signals are globally bounded in finite time. Finally, simulation results are provided to illustrate the effectiveness of the proposed control method.

Finite-time adaptive neural command filtered control for non-strict feedback uncertain multi-agent systems including prescribed performance and input nonlinearities

In this paper, the issue of finite-time consensus tracking control (CTC) is discussed for uncertain nonlinear multi-agent systems (MASs) with prescribed performance and input saturation. By constructing a finite-time performance function (FTPF), the tracking errors converge to a predefined attenuation range within finite-time. By using tanh(·) function and mathematical transformation, the effect of input saturation is solved. The unmodeled dynamics and dynamic disturbances of the system are solved by means of measurable dynamic signals. Through the Young’s inequality and the properties of Gaussian function, the coupling problem between multi-agents and the system controller design problem in non-strict feedback form are successfully dealt with. Furthermore, a finite-time adaptive neural controller is designed based on command filter, which not only guarantees the finite-time stability of the system, but also makes the tracking errors reach a predefined bound in a finite-time. Stability analysis proves that the proposed method is feasible, and simulation verifies its effectiveness.

Finite-time observer based tracking control of uncertain heterogeneous underwater vehicles using adaptive sliding mode approach

In this study, a finite-time consensus tracking problem is investigated for a group of autonomous underwater vehicles (AUVs) with heterogeneous uncertain dynamics. We firstly propose a two-layer distributed control strategy, which consists of an upper-layer distributed observer and a lower-layer controller, without using any global information. Based on Hölder’s inequality and the theory of finite-time stability, a distributed finite-time observer is developed for each follower to estimate the position information of a leader (i.e., an exosystem). Based on the sliding mode control method, a consensus tracking control scheme is designed for each AUV, by which all follower AUVs can track the leader in finite time. Secondly, when the parameters in the AUV dynamics are uncertain, a parameter-adaptive sliding mode control algorithm is introduced to improve the control performance. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control algorithms.

Adaptive Finite-Time Consensus Tracking Control for Coopetition Flexible Joint Multi-Manipulators With Full-State Constraints

In this paper, the adaptive full-state constraints bipartite consensus tracking problem for coopetition flexible joint multi-manipulator systems with finite-time convergence is investigated. Based on the finite-time convergent method, the command filtered backstepping technique is introduced to ensure the excellent convergence performance without the influence of the repeated differential problem which is called explosion of complexity, and the error compensation mechanism is proposed to reduce the error caused by the filtering progress. Furthermore, by using the barrier Lyapunov functions, the state of the system and error compensation signals are proved to be constrained in their respective expected ranges. It is worth mentioning that the flexible joint multi manipulator system is in the mode of coopetition. Finally, the practicability of the proposed algorithm is exhibited in the simulation.