Distributed Formation Control Research Articles

Neuro-adaptive distributed formation tracking control of under-actuated unmanned surface vehicles with input quantization

This paper addresses distributed formation control of multiple under-actuated unmanned surface vehicles (USVs) subject to input quantization, in addition to the unknown dynamics caused by external sea disturbances and internal model uncertainties. A two-level distributed guidance and neuro-adaptive quantized control architecture is presented to achieve a time-varying formation regardless of the input quantization. Specifically, at the kinematic level, an extended state observer (ESO)-based distributed guidance law is developed to track a time-varying trajectory where the ESO is adopted to estimate the unavailable linear velocity and rate of turn (ROT) of neighboring USVs. At the dynamic level, by using a linear time-varying model to deal with the difficulty caused by quantization and the radial basis function neural networks (RBFNNs) to identify the unknown dynamics, a neuro-adaptive quantized control law is developed where no information on the parameters of quantizers is required. The stability of the proposed two-level formation control architecture is proven on the basis of input-to-state stability, and all signals in the closed-loop system are uniformly ultimately bounded. Simulation results demonstrate the effectiveness of the proposed neuro-adaptive quantized control method for USVs.

Finite time fault tolerant tracking control for multiple unmanned aerial vehicles with actuator faults

SummaryAn adaptive fast nonsingular integral terminal sliding mode control scheme is proposed for the distributed formation control problem of multiple unmanned aerial vehicles (UAVs) affected by actuator faults and external disturbances. In order to achieve a good cooperative tracking performance of UAVs during mission execution, the adverse effect of the lumped disturbances composed of actuator failures, wind and vortex disturbances is estimated by the cerebellar model articulation neural network, meanwhile the tangent function is introduced to eliminate the chattering of the sliding mode. Then the analysis of superior convergence performance of the fast nonsingular integral terminal sliding manifold is implemented, and the finite time stability of the closed‐loop formation flight control system is proved. Finally, the simulation experiments verify that the proposed approach is superior to the nonsingular integral terminal sliding mode control for the formation control system of faulty multiple UAVs.

Path Planning and Formation Control for UAV-Enabled Mobile Edge Computing Network.

Recent developments in unmanned aerial vehicles (UAVs) have led to the introduction of a wide variety of innovative applications, especially in the Mobile Edge Computing (MEC) field. UAV swarms are suggested as a promising solution to cope with the issues that may arise when connecting Internet of Things (IoT) applications to a fog platform. We are interested in a crucial aspect of designing a swarm of UAVs in this work, which is the coordination of swarm agents in complicated and unknown environments. Centralized leader–follower formations are one of the most prevalent architectural designs in the literature. In the event of a failed leader, however, the entire mission is canceled. This paper proposes a framework to enable the use of UAVs under different MEC architectures, overcomes the drawbacks of centralized architectures, and improves their overall performance. The most significant contribution of this research is the combination of distributed formation control, online leader election, and collaborative obstacle avoidance. For the initial phase, the optimal path between departure and arrival points is generated, avoiding obstacles and agent collisions. Next, a quaternion-based sliding mode controller is designed for formation control and trajectory tracking. Moreover, in the event of a failed leader, the leader election phase allows agents to select the most qualified leader for the formation. Multiple possible scenarios simulating real-time applications are used to evaluate the framework. The obtained results demonstrate the capability of UAVs to adapt to different MEC architectures under different constraints. Lastly, a comparison is made with existing structures to demonstrate the effectiveness, safety, and durability of the designed framework.

Fully distributed prescribed performance formation control for UAVs with unknown maneuver of leader

This paper focuses on the formation control for multiple quadrotor unmanned aerial vehicles (UAVs) in a leader-follower structure. Taking account of the unknown maneuver of the leader and external disturbances, a novel fully distributed prescribed performance formation controller is proposed. Firstly, to obtain a quick convergence rate of errors and desired control precision, a performance function is introduced into a time-varying barrier Lyapunov function (TV-BLF). Then, a distributed adaptive extended state observer (AESO) is constructed to estimate the maneuver of the leader and external disturbances simultaneously. A distributed formation controller is established further based on the TV-BLF and estimations of the AESO. It is proved rigorously that by using the proposed formation controller, the desired formation pattern can be formed while the prescribed performance is guaranteed. Moreover, no global topology information is required in the proposed AESO and controller, which means that the formation can be realized in a fully distributed way. Last, simulations are performed to validate the effectiveness and the superiority of the presented scheme.

Distributed formation control of underactuated ships with connectivity preservation and collision avoidance

Formation control of ship has distinct advantages in ocean exploration, environment monitoring, patrol surveillance, and maritime rescue with efficiency and flexibility. In this paper, the distributed formation control of underactuated ships, the connectivity preservation, the collision avoidance among formation members, and the collision avoidance with external obstacles are achieved for the first time under the consideration of control input constraints. Taking advantage of nonlinear model predictive control (NMPC), the problem of distributed formation control of underactuated ships with connectivity preservation and collision avoidance is formulated as the quadratic optimization problem with input and output constraints. The periodic event-triggered mechanism is included to solve the optimization problem efficiently. The Floyd method is employed to obtain the optimal communication topology. Multiple studies are conducted to illustrate the advantages of presented methodology.

Path-Guided Finite-Time Formation Control of Nonholonomic Mobile Robots Based on an Extended State Observer

In this paper, we study the finite-time formation control problem of uncertain nonholonomic mobile robots following a parameterized path. A path-guided formation control scheme based on an extended state observer is proposed. To compensate for unmeasured velocities and disturbances simultaneously, a third-order fast finite-time extended state observer (FFTESO) is proposed. Then, a distributed formation control solution is developed to achieve the kinematic and dynamic system coordination control of the nonholonomic mobile robots. For the kinematic system control, a path-parameter-updating law is developed for a virtual leader, and the desired linear velocity and heading angle are developed for the mobile robots. For the kinetic control, an anti-disturbance control protocol is designed based on the estimated signals. The salient features of the proposed algorithms lie in that the estimations of disturbances and unmeasured velocities are achieved against the system’s nonholonomic constraints, and the path following the control and cooperative control is synthesized together for path-guided formation, which reduces the complexity of the controller design. Finally, simulation studies are conducted to demonstrate the effectiveness of the proposed algorithm.

Distributed dynamic edge-based event-triggered formation control for multiple underactuated unmanned surface vessels

This paper investigates the distributed formation control problem for underactuated unmanned surface vessels (USVs) under communication resources constraints and unknown external disturbances. Based on the adaptive algorithm and the minimal learning parameter (MLP) algorithm, a distributed dynamic edge-based event-triggered controller is proposed to achieve the desired formation maneuver. Different from the node-based event-triggered strategy, the edge-based event-triggered mechanism in this paper is developed depends on the information of every edge. Besides, the internal dynamic variable is embedded in the triggering function to obtain larger triggered time interval. Only the triggered condition of every edge is reached can the communication happen, such that the communication burden will be effectively reduced. The theoretical result exhibits that the tracking errors will converge into a tiny region under this control scheme. Finally, numerical simulations are presented to demonstrate the validity of the proposed controller.

Functions of the Laplacian Matrix With Application to Distributed Formation Control

In this article, we study a class of matrix functions of the combinatorial Laplacian that preserve its structure, i.e., that define matrices, which are positive semidefinite and which have zero row-sum and nonpositive off-diagonal entries. This formulation has the merit of presenting different incarnations of the Laplacian matrix that have appeared in recent literature in a unified framework. For the first time, we apply this family of Laplacian functions to consensus theory, and we show that they leave the agreement value unchanged and offer distinctive advantages in terms of performance and design flexibility. The theory is illustrated via worked examples and numerical experiments featuring four representative Laplacian functions in a shape-based distributed formation control strategy for single-integrator robots.

Distributed Stochastic Model Predictive Control for Human-Leading Heavy-Duty Truck Platoon

Human-leading truck platooning systems have been proposed to leverage the benefits of both human supervision and vehicle autonomy. Equipped with human guidance and autonomous technology, human-leading truck platooning systems are more versatile to handle uncertain traffic conditions than fully automated platooning systems. This paper presents a novel distributed stochastic model predictive control (DSMPC) design for a human-leading heavy-duty truck platoon. The proposed DSMPC design integrates the stochastic driver behavior model of the human-driven leader truck with a distributed formation control design for the following automated trucks in the platoon. The driver behavior of the human-driven leader truck is learned by a stochastic inverse reinforcement learning (SIRL) approach. The proposed stochastic driver behavior model aims to learn a distribution of cost function, which represents the richness and uniqueness of human driver behaviors, with a given set of driver-specific demonstrations. The distributed formation control includes a serial DSMPC with guaranteed recursive feasibility, closed-loop chance constraint satisfaction, and string stability. Simulation studies are conducted to investigate the efficacy of the proposed design under several realistic traffic scenarios. Compared to the baseline platoon control strategy (deterministic distributed model predictive control), the proposed DSMPC achieves superior controller performance in constraint violations and spacing errors.

Distributed Disturbance-and-Leader Estimation for Controlling Networks of Nonholonomic Mobile Robots

This work studies the formation control problem for mobile robots. The distinguishing feature of this work is considering the leader and the followers dynamics to be non-ideal, i.e. subject to disturbances/unmodelled terms. Distributed joint disturbance-and-leader estimators are designed to solve the problem, allowing to reconstruct the leader’s signals in a distributed way. The estimates of the leader and the follower disturbances provided by the estimators are embedded in the control law to reject such disturbances and achieve the formation asymptotically. Lyapunov technique is employed to analyze stability of the overall distributed formation control algorithm. Simulations are conducted to illustrate the theoretical results.

Fully Distributed Formation Control of General Linear Multiagent Systems Using a Novel Mixed Self- and Event-Triggered Strategy

In this study, the state formation control issue of general linear networked multi-agent systems (MASs) is considered. Combining self-triggered strategy with general event-triggered strategy, a novel fully distributed asynchronous mixed self- and event-triggered control strategy is proposed, which can make the MASs achieve the prescribed state formation structure. The control strategy proposed in this study does not depend on any global network information. Therefore, no matter how large scale of the network is, the control strategy is feasible. Meanwhile, the control strategy uses the sampled state information at triggering instants instead of the real-time state information, which efficiently eliminates continuous communication among agents. Different from the existing studies, the event-triggered detector starts to work if and only if the next self-triggering instant comes in the control strategy proposed in this article. Thus, the control strategy can save more communication resources between sensor and event-triggered detector within the same inter-event interval compared with the previous event-triggered strategies. In addition, the control strategy designs a exponential decay term in the triggering function to rule out the unexpected Zeno behavior and reduce the triggering number. Finally, the numerical simulation result of multi-robot formation is given, which demonstrates the feasibility and performance of the proposed control strategy.

Distributed non‐ideal leader estimation and formation control for multiple non‐holonomic mobile robots

This paper studies a distributed formation problem for non-holonomic mobile robots. Consideration of the leader dynamics of the robots as non-ideal, that is, subject to disturbances/unmodelled variables, is the distinguishing feature of this work. The issue is resolved by a distributed combined disturbance-and-leader estimator, allowing for the distributed reconstruction of the leader's signals. The estimator needs to detect the leader's information and disturbance. In order to reject such disturbance and achieve the formation asymptotically, the control law incorporates the smooth estimator's estimate of the leader disturbance. Furthermore, the stability of the total distributed formation control algorithm is also examined using the Lyapunov technique. Finally, to show the viability of the proposed theoretical results, simulations and actual experiments are carried out.

Bearing-Based Distributed Formation Control of Unmanned Aerial Vehicle Swarm by Quaternion-Based Attitude Synchronization in Three-Dimensional Space

Most of the recent research on distributed formation control of unmanned aerial vehicle (UAV) swarms is founded on position, distance, and displacement-based approaches; however, a very promising approach, i.e., bearing-based formation control, is still in its infancy and needs extensive research effort. In formation control problems of UAVs, Euler angles are mostly used for orientation calculation, but Euler angles are susceptible to singularities, limiting their use in practical applications. This paper proposed an effective method for time-varying velocity and orientation leader agents for distributed bearing-based formation control of quadcopter UAVs in three-dimensional space. It combines bearing-based formation control and quaternion-based attitude control using undirected graph topology between agents without the knowledge of global position and orientation. The performance validation of the control scheme was done with numerical simulations, which depicted that UAV formation achieved the desired geometric pattern, translation, scaling, and rotation in 3D space dynamically.

Adaptive distributed fault-tolerant control for underactuated surface vehicles with bridge-to-bridge event-triggered mechanism

This paper investigates an adaptive distributed fault-tolerant formation control scheme for multiple underactuated surface vehicles (USVs) with the bridge-to-bridge event-triggered communication mechanism. In particular, under the directed topology, information from each USV is broadcast to the adjacent vehicles only if the event-triggered condition is satisfied. The benefit of the proposed event-triggered communication mechanism eliminates the requirement of either the continuous monitoring of adjacent vehicles’ states or global graph information, which can address the problem of the limited communication bandwidth in the marine practice. Based on the event-triggered communication, backstepping and directed topology, an adaptive distributed formation controller is developed for each USV. Besides, the unknown structure uncertainty and external disturbances are compressed together to compensate by introducing the neural network (NN) approximator and the neural damping technique. And the derived adaptive law can also compensate the adverse effect of unknown actuator faults and gain uncertainty. Through the Lyapunov theory, all signals in the closed-loop system are proved to be with the semi-global uniform ultimate bounded (SGUUB) stability. Finally, the numerical simulation is illustrated to verify the effectiveness of the control algorithm.

Adaptive Formation for Multiagent Systems Subject to Denial-of-Service Attacks

The vulnerabilities of multi-agent-system (MAS) become a critical issue for cybersecurity. The article investigates the formation control problem for MASs under multi-channel denial-of-service (DoS) attacks. In this article, the attacks on each channel are independent, while most of the existing results show that DoS attacks are the same on all channels. Without loss of generality, we consider multi-channel DoS attacks are imposed on a leader-follower MAS. Firstly, we propose a distributed formation control protocol to achieve the desired formation in the presence of DoS attacks. A translation-adaptive method is considered to adjust the interaction weights among neighboring agents online. Furthermore, a performance guarantee is derived based on the state information, and hereafter state errors among all agents can be regulated. Moreover, we derive the sufficient conditions for system stability w.r.t the controller gain and the allowable attack duration in the form of linear matrix inequalities (LMIs). Finally, simulation results are given to illustrate the effectiveness of the proposed method.

Stability Analysis of Gradient-Based Distributed Formation Control With Heterogeneous Sensing Mechanism: The Three Robot Case

This article focuses on the stability analysis of a formation shape displayed by a team of mobile robots that uses a heterogeneous sensing mechanism. For the setups consisting of three robots, we show that the use of heterogeneous gradient-based control laws can give rise to undesired invariant sets where a distorted formation shape is possibly moving at a constant velocity. We guarantee local asymptotic stability for the correct and desired formation shape. For the setup with one distance and two bearing robots, we identify the conditions such that an incorrect moving formation is locally attractive.

Leaderless maneuver guidance and event-triggered formation control for distributed multi-space-robot systems

In this paper, the distributed displacement-based formation and leaderless maneuver guidance control problems of multi-space-robot systems are investigated by introducing event-triggered control update mechanism. A distributed formation and leaderless maneuver guidance control framework is first constructed, which includes two parallel controllers, namely an improved linear quadratic regulator and a distributed consensus-based formation controller. By applying this control framework, the desired formation configuration of multi-space-robot systems can be achieved and the center of leaderless formation can converge to the target point globally. Second, a pull-based event triggering mechanism is introduced to the distributed formation controller, which makes the control update independent of the events of neighboring robots, avoids unnecessary control updates, and saves the extremely limited energy of space robots. Furthermore, the potential Zeno behaviors have been excluded by proving a positive lower bound for the inter-event times. Finally, numerical simulation verifies the effectiveness of the theoretical results.

Distributed Formation Control Algorithm for Improved String Stability in Heterogenic Vehicle Platoons

Achieving speed, safety and energy optimization in vehicle platoons is among the important topics of recent years. In this context, this work focuses on improving the string stability (SS) of heterogeneous platoons. Better SS allows for smaller gap between vehicles, which means shorter time headway for Cooperative Adaptive Cruise Control (CACC) or inter-vehicle following-distance for platooning. Shorter time headway or inter-vehicle distance results in better road use and less fuel consumption. Rather than compensating for dynamic differences by means of low level control schemes by implementing pre-compensators at vehicle level, this work takes a different approach, where a higher level of control is preferred to improve SS: The platoon formation. To achieve this, it is important to ensure that each vehicle is in its optimum position in the platoon based on its dynamics for highest string stability. This generally leads to the vehicle with highest inertia to lead the platoon and the lowest one as the last follower. In this study, a platoon formation algorithm is proposed to run on each vehicle, leading to an optimum overall string structure. The efficiency of the algorithm is demonstrated by simulations in Matlab(R) for a four-vehicle platoon.

Sampled-data-based dynamic event-triggered formation control for nonlinear multi-agent systems

This paper studies the distributed formation control of multi-agent systems with nonlinear dynamics. In view of practical digital microprocessor and limited network resources, the sampled-data-based dynamic event-triggered control strategy is developed. First, each agent synchronously samples its states and monitors the event-triggered function periodically. Each agent broadcasts its states to neighbors only when the function is triggered which can greatly reduce communication times. Meanwhile, the Zeno behavior is excluded due to periodic sampling. Moreover, the dynamic parameter in event-triggered function updates in accordance with a dynamic rule which helps achieve a trade-off between communication frequency and formation performance. The formation problem is transformed into the stability analysis of a time-delay system. Finally, numerical simulations are shown to illustrate the effectiveness of the proposed strategy.

Formation control of unmanned aerial vehicle swarms: A comprehensive review

AbstractThe unmanned aerial vehicle formation plays a crucial role in numerous applications, such as reconnaissance, agricultural plant protection, and electric power inspection. This paper provides a comprehensive review and analysis of the unmanned aerial vehicle swarm communication networks and formation control strategies. First, the most commonly used unmanned aerial vehicles are introduced and compared. Next, the entire process of the formation task, from the formation assignment to the formation transformation, is detailed described. At last, the widely adopted communication networks are analyzed, and the existing formation control strategies of the UAV swarm are compared, which shows that the distributed formation control is superior to the centralized method and is the future development trend.