Unknown Leader Research Articles

Finite-time fuzzy adaptive consensus control for state-constrained MIMO nonlinear MASs with switched topologies

In this article, the adaptive fuzzy finite-time output feedback consensus control problem is investigated for multiple input and multiple output (MIMO) nonlinear multi-agent systems (MASs) with switched topologies and asymmetric state constraints. Fuzzy logic systems (FLSs) are utilised to approximate uncertain nonlinear dynamics, and a distributed observer and a state observer are established to estimate the unknown leader and system states, respectively. By constructing the barrier Lyapunov functions (BLFs), a finite-time output feedback consensus control scheme is presented via backstepping control technique. It is proved that the controlled MASs are stable, and the consensus errors converge in finite time. Moreover, the system states will not exceed the given bounds. Finally, the proposed finite-time consensus control approach is applied to control multiple unmanned surface vehicles (USVs), the simulation results check the feasibility of the developed finite-time consensus control methodology.

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.

A Modular Event-Triggered Containment Control Scheme for Nonlinear Heterogeneous Multiagent Systems With Unknown Leaders.

This article addresses the containment control problem in multiagent systems with nonlinear heterogeneous followers and multiple unknown leaders whose dynamics are exclusively known to their neighbors. The primary goal is to ensure the convergence of each follower to the dynamic convex hull spanned by the leaders under the constraints of limited communication resources. To achieve this, this article introduces a modular event-triggered containment control scheme with three modules. The first module, Module I-signal generator, is designed for each follower to generate a reference signal asymptotically entering the dynamic convex hull without relying on follower dynamics. The second module, Module II-event-triggered mechanism, is tailored to save communication resources effectively by determining when to broadcast information based on perturbed system stability and input-to-state stability theories. The third module, Module III-tracking controller, treats each follower as an independent agent and is crafted to track the reference signal generated by Module I using an output regulation approach. It is established that the system achieves containment control without Zeno behavior under the influence of these modules, and the theoretical results are validated through simulation examples, demonstrating the practical validity of the proposed approach.

Adaptive fixed-time containment control of uncertain underactuated underwater vehicles under dynamic event-driven mechanism

This paper presents a dynamic event-driven fixed-time design strategy for the three-dimensional containment control of underactuated underwater vehicles under a directed topology. Our main contribution is the development of a novel error transformation approach based on adaptive multi-leader estimation to address the fixed-time containment (FTC) control problem in the presence of underactuation input and unknown leaders’ velocity. An adaptive FTC control law using stabilizing auxiliary variables and nonlinear filters is constructed based on event-driven conditions. The dynamic thresholds, which depend on containment errors, are presented to efficiently reduce communication resources required for implementing the FTC controller. According to Lyapunov theory, it is shown that the trajectories of the followers converge to the convex hull spanned by multiple leader signals within a fixed time while ensuring the avoidance of the Zeno phenomenon. Finally, the effectiveness of the suggested control approach is verified through simulation results.

Leader–Follower Tracking for General Multiagent Systems With Unknown Leader Input and Limited Actuation

Leader–Follower Tracking for General Multiagent Systems With Unknown Leader Input and Limited Actuation

Resilient Event-Triggered Adaptive Cooperative Fault-Tolerant Tracking Control for Multiagent Systems Under Hybrid Actuator Faults and Communication Constraints

This paper investigates the cooperative fault-tolerant tracking problem for multiagent systems with directed topology that experience communication link faults and actuator faults under malicious attacks. Based on a resilient event-triggered mechanism, a novel distributed high-order sliding-mode observer and a robust adaptive cooperative fault-tolerant control method are proposed, which can achieve the desired formation shape tracking under communication limitations and hybrid actuator faults caused by malicious attacks. First, the designed distributed event-triggered observer can estimate the unknown leader. Second, the proposed event-triggered mechanism can be used to reduce the impact of malicious attacks on the information and physical layers of the multiagent system. Additionally, the utilization rate of network communication is further improved so that it can save communication resources by reducing the number of event triggers. Then, based on the information of the leader, the designed robust adaptive cooperative fault-tolerant controller can compensate for the influence of the hybrid actuator faults on the system under malicious attacks. Finally, the effectiveness of the method is verified by two sets of example simulations.

Bipartite Tracking Consensus for High-Order Heterogeneous Uncertain Nonlinear Multi-Agent Systems With Unknown Leader Dynamics via Adaptive Fully-Distributed PID Control

This article tackles the problem of bipartite tracking consensus for high-order heterogeneous nonlinear and uncertain Multi-Agent Systems (MASs) interacting over directed signed graphs, where the agent nonlinear dynamics, including the leader ones, are general and unknown. A novel fully-distributed adaptive PID-like protocol, that does not require any prior knowledge about the global information of the network structure and/or any distributed observer for leader dynamics estimation, is proposed to solve the problem. Based on the Lyapunov theory, we derive adaptive mechanisms able to guarantee the robust asymptotic convergence of the overall networked system and the boundedness of the time-varying control signals. To achieve these control objectives, the computation of the adaptive control actions leverages only a limited amount of time-varying information, thus preserving the communication channel bandwidth and reducing the computational burden required at the single agent level. A numerical analysis supports the theoretical derivation.

Vortex Formation Control for Linear Multiagent Systems With Unknown Leader Input and External Disturbances

This brief investigates vortex formation control problem for linear multiagent systems with unknown leader input and external disturbances. This brief proposes a distributed control protocol with antisymmetric matrix which can adjust the interaction between agents to realize the vortex formation of multiagent system. Each agent only communicates with their neighbor agents through the communication topology without requiring the whole system to be fully connected, which makes the control protocol more suitable for large-scale systems. The unknown bounded external disturbance and the input information of leader that may be encountered in practical application are considered in the protocol design. A control term related to the symbolic function is introduced to deal with bounded external disturbances and unknown leader input signal, which can deal with more complex external environment and uncooperative leader in practical applications. Finally, a numerical example is presented to verify the proposed protocol.

Guest Editorial: Learning, optimisation and control of cyber‐physical systems

Guest Editorial: Learning, optimisation and control of cyber‐physical systems

The Spectre of Populist Leadership: QAnon, Emergent Formations, and Digital Community

QAnon is an online conspiracy movement centred on cryptic posts published by an unknown figure referred to as “Q.” Its anti-hierarchical framework and deployment of an unknown leader can be understood as a substantial departure from other 21st-century populisms that are sustained by the celebrity relationship between a leader (often aspiring to or gaining political office) and its followers (constituted in community through consumption of the leaders’ social media posts). Reflecting on contemporary debates and insights within cultural studies and digital communication literature, this article investigates some of the ways in which the spectral leadership of Q presents challenges for understanding and apprehending populist movements. In light of QAnon, there is an emerging need to make sense of populisms that are built on mythical or anonymous characters rather than on identifiable human actors in leadership roles. We begin by discussing the role of key practices of contemporary populist leadership and contrast these with justice-based populisms that are community-led without the figure of an identifiable leader. We argue that, as a populist movement, QAnon fits neither of these frameworks and, instead, has drawn on the affordances of digital media and its intersections with postmodern hyperreality to produce a new formation of populist movement today. Arguing that Q is the simulacra of a leader, we theorise the ways in which QAnon fosters affiliation and action from its adherents who, themselves, take on the role of saviour-leader.

Dynamic Event-Triggered Platooning Control of Automated Vehicles Under Random Communication Topologies and Various Spacing Policies.

This article addresses the problem of dynamic event-triggered platooning control of automated vehicles over a vehicular ad-hoc network (VANET) subject to random vehicle-to-vehicle communication topologies. First, a novel dynamic event-triggered mechanism is developed to determine whether or not the sampled data packets of each vehicle should be released into the VANET for intervehicle cooperation. More specifically, the threshold parameter in the triggering condition is dynamically adjusted over time according to the vehicular data variations, the dynamic threshold updating laws, and the bandwidth occupancy indication. Second, a unified platooning control framework is established to account for various spacing policies, randomly switching communication topologies, unknown leader control input, and external disturbances. Then, a new scheduling and platooning control co-design approach is presented such that the controlled vehicular platoon can successfully track the leader vehicle under random communication topologies and different spacing policies, including constant spacing, constant time headway spacing, and variable time headway spacing, meanwhile maintaining efficient bandwidth-aware resource management. Finally, comparative studies are provided to substantiate the effectiveness and merits of the proposed co-design approach.

Learning‐based distributed adaptive control of heterogeneous multi‐agent systems with unknown leader dynamics

Learning‐based distributed adaptive control of heterogeneous multi‐agent systems with unknown leader dynamics

Resource-Efficient Platooning Control of Connected Automated Vehicles Over VANETs

This paper is concerned with distributed cooperative longitudinal platooning control of connected automated vehicles over resource-constrained vehicular ad-hoc networks. First, a general platoon-based control framework is constructed, which simultaneously accounts for unknown leader control input, external disturbances, intermittent data samplings and transmissions, various spacing policies, and different vehicle-to-vehicle communication topologies. To alleviate excessive occupancy of the limited communication resources, an adaptive Zeno-free event-triggered communication mechanism is developed to determine when the sampling and transmission actions of vehicular data should be performed among interacting vehicles. Then, a scalable co-design approach for the desired adaptive platoon controller as well as event triggering condition is developed. One promising feature of the proposed platooning control strategy is that it is independent on the platoon scale or any global knowledge of the associated communication topology, and thus implementable on each vehicle in a scalable manner. Finally, several numerical case studies are conducted to verify the efficacy of the derived approach.

Adaptive leader–follower control for nonlinear uncertain multi-agent systems with an uncertain leader and unknown tracking paths

With unknown leader parameters and false or immeasurable tracking paths, the leader–follower tracking problem via adaptive control becomes more complex and challenging. Different from the existing work in the literature and in line with real-world applications, this challenging issue is solved in this paper for multi-agent networks with different kinds of unknown uncertainties in the followers such as partially known parameters, nonlinearities, external disturbances, communication weights, and sensor faults. The solution of this challenging issue is obtained in three steps. Firstly, the tracking path is estimated by designing distributed adaptive observers at all agents that have direct communication edges with the leader. Next, by designing local adaptive observers for all followers, the estimates of all followers’ states can be obtained. Then, distributed adaptive controllers for all followers are designed using the estimated states of both followers and their neighbors in addition to the estimated tracking path. The tracking performances are provided via sufficient conditions for both the adaptive observers and the adaptive controllers. The proposed methods are evaluated through two examples that are commonly used in the literature. The obtained results prove the efficacy of the recommended adaptive approaches.

H∞-based control of multi-agent systems: Time-delayed signals, unknown leader states and switching graph topologies

The paper investigates a leader-following scheme for nonlinear multi-agent systems (MASs). The network of agents involves time-delay, unknown leader's states, external perturbations, and switching graph topologies. Two distributed protocols including a consensus protocol and an observer are utilized to reconstruct the unavailable states of the leader in a network of agents. The H∞-based stability conditions for estimation and consensus problems are obtained in the framework of linear-matrix inequalities (LMIs) and the Lyapunov-Krasovskii approach. It is ensured that each agent achieves the leader-following agreement asymptotically. Moreover, the robustness of the control policy concerning a gain perturbation is guaranteed. Simulation results are performed to assess the suggested schemes. It is shown that the suggested approach gives a remarkable accuracy in the consensus problem and leader's states estimation in the presence of time-varying gain perturbations, time-delay, switching topology and disturbances. The H∞ and LMIs conditions are well satisfied and the error trajectories are well converged to the origin.

Scalable and Resilient Platooning Control of Cooperative Automated Vehicles

This paper addresses the problem of distributed cooperative longitudinal control of automated vehicle platoons subject to a variety of uncertainties, including unknown engine time lags, external disturbances, measurement noises, and actuator anomaly in follower vehicles as well as unknown leader control. First, a unified framework is proposed for accomplishing resilient vehicle platooning, which empowers longitudinal vehicle state estimation, anomaly signal estimation and compensation, and adaptive platoon controller design to be addressed in a comprehensive way. Second, a novel scalable platooning control design approach is developed to guarantee desired platoon stability and resilience over generic communication topologies and various spacing policies. A salient feature of the approach is that the design procedure does not depend on any global information of the associated topology, and thus preserves essential scalability for large and/or size-varying platoons. Third, it is shown that the proposed longitudinal platooning control approach is promising for performing flexible cooperative maneuvers such as platoon splitting and merging that are beyond the capacity of most existing longitudinal platooning strategies. Finally, simulation results for different platoon maneuvers are elaborated to substantiate the efficacy of the proposed approach.

Time-varying formation tracking for noisy multi-agent systems with unknown leader trajectory

In this article, time-varying formation tracking problem for multi-agent systems is investigated. It is assumed the number of agents is changing and obstacles should be avoided along the trajectory. In addition, the tracking formation should be reached while the leader trajectory is unknown and communication data are noisy. To reach the desired formation tracking, first, a virtual leader is constructed using the local neighbouring data. Second, the reference signal is created based on the virtual leader and the leader data (which is available for some agents). The data fusion at this stage is done based on Kalman filtering to reduce the effect of communication noise. Third, an integral state feedback controller as a new consensus formation controller based on the relative position and velocity vectors of the agents and the estimated (virtual) leader are proposed to achieve the time-varying formation tracking. Next, closed-loop stability of the system under the proposed control law is investigated using the Lyapunov stability theorem. In order to implement the proposed control strategy, an extended state observer is designed to estimate the required velocity and accelerations. Finally, an obstacle avoidance strategy would be embedded to the controller via a repelling strategy. That is, once the leader identifies the obstacle and enters a repulsion region, its reference trajectory is modified to keep a safe distance from the obstacle. The agents modify their reference trajectory according to the new leader trajectory while trying to keep their formation. As an illustrative example, various simulations are performed for formation tracking of a unmanned aerial vehicle multi-agent system to evaluate its performance.

Adaptation to Unknown Leader Velocity in Vector-Field UAV Formation

This article presents a new adaptive method for formation control of unmanned aerial vehicles (UAVs) with limited leader information and communication. We study a formation control protocol in the framework of vector-field guidance where the leader can communicate its position and orientation but not its velocity. A practical motivation for this scenario is the so-called congestion-aware control, in which tradeoffs between the density of unmanned vehicles and communication interference caused by many communicating vehicles arise: these tradeoffs may require to reduce the communication load to avoid interference. To compensate for the lack of knowledge of the leader velocity, each UAV makes use of a local estimation mechanism. The resulting method is an adaptive control method, whose stability can be established using Lyapunov stability. We show that the method can be extended to a distributed communication setting with a few neighboring UAVs in place of the leader. Extensive simulations with different formation shapes (Y, V, and T formation) show that the proposed adaptation mechanism effectively achieves the formation despite the unknown leader velocity. The proposed mechanism has a very similar performance to the ideal case when the leader velocity is perfectly known, and outperforms all the nonadaptive cases in which the followers have an incorrect knowledge of the leader velocity.

Robust Adaptive Consensus of Decentralized Large-Scale Bi-Directional Vehicular Platoons With Only Relative Position Measurement

This paper presents a new approach to solve the problem of internal and string stability of decentralized large-scale bi-directional vehicular platoons (DLBVPs) under uncertain dynamics with constant spacing strategy. It is assumed that each following vehicle can only measure the relative position with respect to its predecessor and subsequent vehicles. To estimate the uncertain dynamics of each following vehicle and unknown leader acceleration, a new decentralized robust adaptive consensus protocol is introduced which by using only relative position measurement, guarantees internal and string stability. It will be shown that the control gains are tuned without requiring any knowledge about the platoon size (number of following vehicles) and consequently, the controller is robust against size changing due to common maneuvers. By using Lyapunov theorem, we will prove that under this approach, the position and velocity tracking errors of each vehicle converge to zero asymptotically. Furthermore, it is shown that the adaptation laws have the main role in assuring string stability of DLBVPs with constant spacing strategy. Several simulation and practical results will depict the merits of this algorithm.

Fuzzy Integral Sliding Mode Observer-Based Formation Control of Mobile Robots With Kinematic Disturbance and Unknown Leader and Follower Velocities

Fuzzy integral sliding mode observer (FISMO) based leader-follower formation control with the use of ceiling-mounted camera information is proposed for mobile robots with kinematic disturbance and no information of the velocities of leader and follower robots. Using only the posture information of both the leader and follower robots obtained from the camera sensor, the follower robot is made to follow the trajectory of a target robot that is introduced to render the leader-follower formation control more efficient. As a result, a kinematic tracking error model is proposed in terms of both the posture error between the target and follower robots and the posture error between the origin of the inertial reference frame and follower robot. Because the kinematic disturbance and the velocities of the leader and follower robots are not available, an FISMO is designed to simultaneously estimate the kinematic disturbance as well as the linear and angular velocities of the leader and follower robots. FISMO-based leader-follower output feedback formation control is then proposed based on the estimates of the kinematic disturbance and velocities and the backstepping-like feedback linearization tracking control. The experimental results comparing the proposed FISMO-based method with the robust distance-based tracking control method and integral sliding mode observer (ISMO)-based method are provided to verify the effectiveness of the proposed method.