Cooperative control of multiple surface vessels in the presence of ocean currents and parametric model uncertainty

This paper addresses the problem of cooperative path‐following of multiple autonomous vehicles. Stated briefly, the problem consists of steering a group of vehicles along specified paths while keeping a desired spatial formation. For a given class of autonomous surface vessels, it is shown how Lyapunov‐based techniques and graph theory can be brought together to design a decentralized control structure, where the vehicle dynamics and the constraints imposed by the topology of the inter‐vehicle communication network are explicitly taken into account. To achieve path‐following for each vehicle, a nonlinear adaptive controller is designed that yields convergence of the trajectories of the closed‐loop system to the path in the presence of constant unknown ocean currents and parametric model uncertainty. The controller derived implicitly compensates for the effect of the ocean current without the need for direct measurements of its velocity. Vehicle cooperation is achieved by adjusting the speed of each vehicle along its path according to information exchanged on the positions of a subset of the other vehicles, as determined by the communication topology adopted. Global stability and convergence of the closed‐loop system are guaranteed. Illustrative examples are presented and discussed. Copyright © 2009 John Wiley & Sons, Ltd.     

Cooperative control of multiple surface vessels with discrete‐time periodic communications

This paper addresses the problem of cooperative path‐following of networked autonomous surface vessels with discrete‐time periodic communications. The objective is to steer a group of autonomous vehicles along given spatial paths, while holding a desired inter‐vehicle formation pattern. For a given class of marine vessels, we show how Lyapunov‐based techniques, graph theory, and results from networked control systems can be brought together to yield a decentralized control structure where the dynamics of the cooperating vessels and the constraints imposed by the topology of the inter‐vehicle communication network are explicitly taken into account. Cooperation is achieved by adjusting the speed of each vessel along its path according to information exchanged periodically on the positions of a subset of the other vessels, as determined by the communications topology adopted. The closed‐loop system that is obtained by putting together the path‐following and cooperation strategies takes an interconnected feedback form where both systems are input‐to‐state stable with respect to the outputs of each other. Using a small‐gain theorem, stability and convergence of the overall system are guaranteed for adequate choices of the controller gains. Copyright © 2011 John Wiley & Sons, Ltd.     

联合通信资源分配的网联车协同自适应巡航 时滞反馈控制

考虑网联车辆队列在路段通信资源受限下的协同自适应巡航控制(CACC)问题,提出一种联合通信资源分配的网联车辆协同自适应巡航时滞反馈控制方法.首先,在头车-前车跟随的通信拓扑结构下,通过网联车辆队列中各车辆间的通信链路数量、该路段可使用的通信资源和当前时刻车辆间的间距误差建立二分图,根据车辆间的间距误差来调度有限的通信资源,将通信资源合理分配给有较大间距误差的跟随车辆;其次,利用非对称PD控制协议和网联车辆队列时滞纵向模型,应用线性矩阵不等式技术计算网联车CACC控制器,进一步得到车辆队列弦稳定性的充分条件;最后,通过Matlab/CarSim联合仿真验证该方法的有效性.     

Trajectory-Tracking and Path-Following of Underactuated Autonomous Vehicles With Parametric Modeling Uncertainty

We address the problem of position trajectory-tracking and path-following control design for underactuated autonomous vehicles in the presence of possibly large modeling parametric uncertainty. For a general class of vehicles moving in either 2- or 3-D space, we demonstrate how adaptive switching supervisory control can be combined with a nonlinear Lyapunov-based tracking control law to solve the problem of global boundedness and convergence of the position tracking error to a neighborhood of the origin that can be made arbitrarily small. The desired trajectory does not need to be of a particular type (e.g., trimming trajectories) and can be any sufficiently smooth bounded curve parameterized by time. We also show how these results can be applied to solve the path-following problem, in which the vehicle is required to converge to and follow a path, without a specific temporal specification. We illustrate our design procedures through two vehicle control applications: a hovercraft (moving on a planar surface) and an underwater vehicle (moving in 3-D space). Simulations results are presented and discussed.     

Formation control of multiple vehicles using dynamic surface control and hybrid systems

This paper deals with the formation control of multiple vehicles, using a combination of dynamic surface sliding control and hybrid systems. Each vehicle must perform several manoeuvres, either independently, or in a coordinated fashion as part of a vehicle formation. A dynamic surface controller is designed for each manoeuvre. Switches between manoeuvres and communication protocols between vehicles are represented using hybrid systems formalisms. Here, we present the design of both independent and coordinated dynamic positioning (DP) controllers for ocean vehicles using dynamic surface control. Independent and coordinated dynamic positioning are manoeuvres that the modules forming a floating runway at sea must perform. Experimental results using scaled modules are shown.     

Globally Stable Adaptive Dynamic Surface Control for Cooperative Path Following of Multiple Underactuated Autonomous Underwater Vehicles

The cooperative path following problem of multiple underactuated autonomous underwater vehicles (AUVs) involves two tasks. The first one is to force each AUV to converge to the desired parameterized path. The second one is to satisfy the requirement of a cooperative behavior along the paths. In this paper, both of the tasks have been further studied. For the first one, a simplified path following controller is proposed by incorporating the dynamic surface control (DSC) technique to avoid the calculation of derivatives of virtual control signals. Besides, in order to handle the uncertain dynamics, a new type of neural network (NN) adaptive controller is derived, and then an NN based energy‐efficient path following controller is firstly proposed, which consists of an adaptive neural controller dominating in the neural active region and an extra robust controller working outside the neural active region. For the second one, in order to reduce the amount of communications between multiple AUVs, a distributed estimator for the reference common speed is firstly proposed as determined by the communications topology adopted, which means the global knowledge of the reference speed is relaxed for the problem of cooperative path following. The overall algorithm ensures that all the signals in the closed‐loop system are globally uniformly ultimately bounded (GUUB) and the output of the system converges to a small neighborhood of the reference trajectory by properly choosing the design parameters. Simulation results validate the performance and robustness of the proposed strategy.     

A highly scalable path-following controller for N-trailers with off-axle hitching

The paper presents a highly scalable nonlinear cascaded-like path-following feedback controller for N-trailer robotic vehicles equipped with arbitrary number of off-axle hitched trailers. In contrast to the other path-following control laws proposed in the literature for N-trailer robots, the presented control approach does not require determination of the shortest distance to a reference path. By introducing the so-called segment-platooning reference paths, and under the sign-homogeneity assumption for hitching offsets, the asymptotic following is guaranteed for both constant- and varying-curvature reference paths using either backward or forward vehicle motion strategy with a guidance point fixed on the last trailer. The paper contains experimental results obtained with a 3-trailer laboratory-scale vehicle.     

Event-triggered-based finite-time cooperative path following control for underactuated multiple marine surface vehicles

This paper develops an event-triggered-based finite-time cooperative path following (CPF) control scheme for underactuated marine surface vehicles (MSVs) with model parameter uncertainties and unknown ocean disturbances. First, a finite-time extended state observer (FTESO) is proposed, in which the FTESO can estimate the velocities and compound disturbances in finite time. Then, the finite-time LOS guidance law based on velocity estimation values is designed to obtain the desired surge velocity and the desired yaw rate. In order to realize the cooperative control of multiple paths in finite time, the cooperative control law for the path variable is designed. In addition, the relative threshold event-triggered control (ETC) mechanism is incorporated into the formation control algorithm, and an event-triggered-based finite-time CPF controller is designed, which not only effectively reduces the update frequency of controller and the mechanical loss of actuator but also improves the control performance of system. Furthermore, by using homogeneous method, Lyapunov theory, and finite-time stability theory, it is proved that under the proposed finite-time CPF control scheme, the formation errors can converge to a small neighborhood around origin in finite time. Finally, numerical simulation results illustrate the effectiveness of the proposed control scheme.     

Information flow and cooperative control of vehicle formations

We consider the problem of cooperation among a collection of vehicles performing a shared task using intervehicle communication to coordinate their actions. Tools from algebraic graph theory prove useful in modeling the communication network and relating its topology to formation stability. We prove a Nyquist criterion that uses the eigenvalues of the graph Laplacian matrix to determine the effect of the communication topology on formation stability. We also propose a method for decentralized information exchange between vehicles. This approach realizes a dynamical system that supplies each vehicle with a common reference to be used for cooperative motion. We prove a separation principle that decomposes formation stability into two components: Stability of this is achieved information flow for the given graph and stability of an individual vehicle for the given controller. The information flow can thus be rendered highly robust to changes in the graph, enabling tight formation control despite limitations in intervehicle communication capability.     

Predictor-based neural dynamic surface control for distributed formation tracking of multiple marine surface vehicles with improved transient performance基于预估器神经网络动态面的海洋航行器分布式队形跟踪

In this paper, we investigate the distributed formation tracking problem of multiple marine surface vehicles with model uncertainty and time-varying ocean disturbances induced by wind, waves, and ocean currents. The objective is to achieve a collective tracking with a time-varying trajectory, which can only be accessed by a fraction of follower vehicles. A novel predictor-based neural dynamic surface control design approach is proposed to develop the distributed adaptive formation controllers. We use prediction errors, rather than tracking errors, to construct the neural adaptive laws, which enable the fast identification of the vehicle dynamics without incurring high-frequency oscillations in control signals. We establish the stability properties of the closed-loop network via Lyapunov analysis, and quantify the transient performance by deriving the truncated L₂ norms of the derivatives of neural weights, which we demonstrate to be smaller than the classical neural dynamic surface control design approach. We also extend the above result to the distributed formation tracking using the relative position information of vehicles, and the advantage is that the velocity information of neighbors and leader are required. Finally, we give the comparative studies to illustrate the performance improvement of the proposed method.     

一类非线性系统的加速度规划输出跟踪动态控制

针对一类严格反馈形式的非线性二阶多输入多输出系统,提出一种带有加速度规划的输出跟踪动态控制策略.引入一个代替时间变量的路径参数用以规划路径跟踪时的加速度,回避了设计内环加速度控制回路的常规方法,简化了控制器的设计过程.对二阶系统的控制项求导进行系统扩维,基于新的增广系统,设计了使系统输出收敛于期望路径的反馈线性化动态控制律.再对加速度跟踪误差基于梯度法设计更新律使其渐近收敛于零,最后通过调节期望加速度实现定常速度控制.理论分析表明,误差闭环系统一致渐近稳定,速度误差有界.动力定位船舶循迹控制仿真结果表明了所提出控制器的有效性.     

多自主船协同路径跟踪的自适应动态面控制

为实现多自主船含模型不确定与未知风浪流干扰下的协同路径跟踪控制,提出了一种基于神经网络自适应动态面控制的协同路径跟踪算法.该算法采用单隐层(SHL)神经网络逼近模型不确定性以及海洋环境干扰,所引入的动态面设计技术显著降低了控制算法的复杂性.同时将网络通信约束考虑在内,通过设计分散式协同控制律有效地降低了信息通讯量.Lyapunov稳定性分析证明了闭环系统所有的状态和信号是有界的,并且通过选择合适的设计参数可使跟踪误差为任意小.对比仿真结果验证了所提方法的有效性.     

Robust adaptive path-following control of underactuated marine vessel with off-track error constraint

In this paper, a new robust adaptive controller is investigated to force an underactuated surface marine vessel to follow a predefined parameterised path at a desired speed, despite actuator saturation and the presence of model uncertainties as well as environmental disturbances induced by waves, wind and sea-currents. To ensure robustness of the path-following controller, time-varying constraint on the off-track error (i.e. the maximal distance from the ship to the reference path) is considered. To address the off-track error constraint the tan-barrier Lyapunov function is incorporated with the control scheme, where the idea of auxiliary design system introduced in Chen, Sam, and Ren (2011) is adopted and its states are used in combination with backstepping and Lyapunov synthesis to adaptive tracking control design with guaranteed stability. Furthermore, the command filters are adopted to implement physical constraints on the virtual control laws so that analytic differentiation of the virtual control laws is avoided. We show that the proposed robust adaptive control law is able to guarantee semi-global uniform ultimate bounded stability of the closed-loop system. Numerical simulations and experimental results are carried out to demonstrate the effectiveness of the proposed algorithm.     

无人艇全分布式动态事件触发编队控制

针对通信资源受限的多无人艇(USV)编队控制问题, 本文提出了一种动态事件触发数据传输机制以降低通信频率, 减少控制算法对系统带宽的占用. 首先, 基于滑模和自适应控制算法设计一种全分布式编队控制器, 使得所有编队成员在保持预设队形的同时能够完成对期望轨迹的跟踪. 与现有编队控制器相比, 该控制器不需要通信网络的全局信息. 然后, 基于Lyapunov稳定性理论证明了编队跟踪误差以及所有闭环信号都能达到稳定状态. 此外,该算法能够保证触发时间序列不表现出Zeno行为. 最后, 通过数值仿真验证了全分布式编队控制器的有效性     

Cooperative path following of constrained autonomous vehicles with model predictive control and event‐triggered communications

We present a solution to the problem of multiple vehicle cooperative path following (CPF) that takes explicitly into account vehicle input constraints, the topology of the intervehicle communication network, and time‐varying communication delays. The objective is to steer a group of vehicles along given spatial paths, at speeds that may be path dependent, while holding a feasible geometric formation. The solution involves decoupling the original CPF problem into two subproblems: (i) single path following of input‐constrained vehicles and (ii) coordination of an input‐constrained multiagent system. The first is solved by adopting a sampled‐data model predictive control scheme, whereas the latter is tackled using a novel distributed control law with an event‐triggered communication (ETC) mechanism. The proposed strategy yields a closed‐loop CPF system that is input‐to‐state‐stable with respect to the system's state (consisting of the path following error of all vehicles and their coordination errors) and the system's input, which includes triggering thresholds for ETC communications and communication delays. Furthermore, with the proposed ETC mechanism, the number of communications among the vehicles are significantly reduced. Simulation examples of multiple autonomous vehicles executing CPF maneuvers in 2D under different communication scenarios illustrate the efficacy of the CPF strategy proposed.     

Passivity-based designs for synchronized path-following

We consider a formation control system where individual systems are controlled by a path-following design and the path variables are to be synchronized. We first show a passivity property for the path-following system, and next, combine this with a passivity-based synchronization algorithm developed in Arcak [2007. Passivity as a design tool for group coordination. IEEE Transactions on Automatic Control, in press]. The passivity approach expands the classes of synchronization schemes available to the designer. This generality offers the possibility to optimize controllers to, e.g., improve robustness and performance. Two designs are developed in the proposed passivity framework: the first employs the path error information in the synchronization loop, while the second only uses synchronization errors. A sampled-data design, where the path variables are updated in discrete-time and the path-following controllers are updated in continuous time, is also developed.     

基于CAN总线的底盘综合控制系统设计

设计了基于CAN总线的底盘综合控制系统,主要包括对整车、四轮驱动、转向系统和制动系统的控制器设计。采用CAN总线实现电动汽车各控制器间的通信,并完成了CAN网络应用层协议的制订。在综合考虑相关影响因素基础上,设计了各控制器的硬件,建立伪逆控制分配算法实现常规的控制量分配,以及必要时实现控制再分配,保证车辆的操纵稳定性。系统的仿真结果表明,该系统可有效地完成常规和再分配控制量,兼顾电动汽车的灵活与稳定。     

Using improved particle swarm optimization to tune PID controllers in cooperative collision avoidance systems

The introduction of proportional-integral-derivative (PID) controllers into cooperative collision avoidance systems (CCASs) has been hindered by difficulties in their optimization and by a lack of study of their effects on vehicle driving stability, comfort, and fuel economy. In this paper, we propose a method to optimize PID controllers using an improved particle swarm optimization (PSO) algorithm, and to better manipulate cooperative collision avoidance with other vehicles. First, we use PRESCAN and MATLAB/Simulink to conduct a united simulation, which constructs a CCAS composed of a PID controller, maneuver strategy judging modules, and a path planning module. Then we apply the improved PSO algorithm to optimize the PID controller based on the dynamic vehicle data obtained. Finally, we perform a simulation test of performance before and after the optimization of the PID controller, in which vehicles equipped with a CCAS undertake deceleration driving and steering under the two states of low speed (≤50 km/h) and high speed (≥100 km/h) cruising. The results show that the PID controller optimized using the proposed method can achieve not only the basic functions of a CCAS, but also improvements in vehicle dynamic stability, riding comfort, and fuel economy.     

Yaw stability control of articulated frame off-highway vehicles via displacement controlled steer-by-wire

Off-highway vehicles have not received the same level of scrutiny that their on-highway counterparts did relative to safety, comfort, fuel economy, and automation. Over the past few decades, various active chassis safety control systems, architectures, and schemes have been researched and developed to improve the stability and handling of on-highway vehicles, including articulated vehicles such as tractor–trailer applications. In this paper, the authors investigate a yaw stability control system for articulated frame steering off-highway vehicles via novel steer-by-wire technology that they have recently developed. A high-fidelity vehicle dynamics model is derived while keeping the yaw rate decoupled from the lateral acceleration, in order to separate the primary path-following task (driver) from the secondary disturbance–attenuation task (controller). The control algorithm is then designed such that the two tasks do not hamper one another, and that the automatic controller is quickly activated for a short period of time to counteract instabilities, and then smoothly relinquishes control back to the human operator. Simulation and experimental testing results are obtained to validate the vehicle dynamics model, the control algorithm design, and the new system's efficacy in counteracting yaw instabilities on low-friction surfaces using standard vehicle dynamic maneuvers.     

一种多向链路感知的车载Ad Hoc网络传播协议

为了提高车辆自组织网络（Vehicular Ad Hoc Network,VANET）的数据传输效率,并使车辆间的数据通信能够持续进行,提出一种多向链路感知的车载Ad Hoc网络传播协议。为了保证车辆节点在执行通信任务的过程中实现数据的持续传输,防止通信链路频繁断连影响传输质量,提出了车辆网络的时间关联模型来讨论车辆间的速度差与通信持续时间的关系。为了缩短VANET中用于数据传输任务的总时间,协议基于改进蚁群的方法进行了多向链路感知,从而寻找在保证通信需求时间下的最短传输路径。实验结果分析表明,相比基于改进地理信息路由和基于优化链路状态路由的VANET数据传输算法,该算法的数据传输任务完工时间分别缩短了38.4%和27.3%,平均传输延迟分别降低了25.5%和12.1%。