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.     

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.     

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.     

Adaptive neural control for cooperative path following of marine surface vehicles: state and output feedback

This paper addresses the cooperative path-following problem of multiple marine surface vehicles subject to dynamical uncertainties and ocean disturbances induced by unknown wind, wave and ocean current. The control design falls neatly into two parts. One is to steer individual marine surface vehicle to track a predefined path and the other is to synchronise the along-path speed and path variables under the constraints of an underlying communication network. Within these two formulations, a robust adaptive path-following controller is first designed for individual vehicles based on backstepping and neural network techniques. Then, a decentralised synchronisation control law is derived by means of consensus on along-path speed and path variables based on graph theory. The distinct feature of this design lies in that synchronised path following can be reached for any undirected connected communication graphs without accurate knowledge of the model. This result is further extended to the output feedback case, where an observer-based cooperative path-following controller is developed without measuring the velocity of each vehicle. For both designs, rigorous theoretical analysis demonstrate that all signals in the closed-loop system are semi-global uniformly ultimately bounded. Simulation results validate the performance and robustness improvement of the proposed strategy.     

Target point‐based path‐following controller for a car‐type vehicle using bounded controls

In this paper, we have studied the control problem of target point‐based path following for car‐type vehicles. This special path‐following task arises from the needs of vision‐based guidance systems, where a given target point located ahead of the vehicle, in the visual range of the camera, must follow a specified path. A solution to this problem is developed through a nonlinear transformation of the path‐following problem into a reference trajectory tracking problem, by modeling the target point as a virtual vehicle. The use of target point complicates the control problem, as the development produces a first‐order nonlinear nonglobally Lipschitz differential equation with finite escape time. This problem is solved by using small control signals. Bounded feedback laws are designed to control the real vehicle's angular acceleration and the virtual vehicle's velocity, to achieve stability. The resulting controller is globally asymptotically stable with respect to the origin, the proof of which is derived from Lyapunov‐based arguments and a bootstrap argument. It is also shown that the use of exponentially convergent observers/differentiators does not affect the stability of the closed‐loop system. The effectiveness of this controller has been illustrated through simulations. Copyright © 2014 John Wiley & Sons, Ltd.     

Nonlinear control with integral sliding properties for circular aerial robot trajectory tracking: Real‐time validation

A nonlinear control algorithm for tracking dynamic trajectories using an aerial vehicle is developed in this work. The control structure is designed using a sliding mode methodology, which contains integral sliding properties. The stability analysis of the closed‐loop system is proved using the Lyapunov formalism, ensuring convergence in a desired finite time and robustness toward unknown and external perturbations from the first time instant, even for high frequency disturbances. In addition, a dynamic trajectory is constructed with the translational dynamics of an aerial robot for autonomous take‐off, surveillance missions, and landing. This trajectory respects the constraints imposed by the vehicle characteristics, allowing free initial trajectory conditions. Simulation results demonstrate the good performance of the controller in closed‐loop system when a quadrotor follows the designed trajectory. In addition, flight tests are developed to validate the trajectory and the controller behavior in real time.     

Centralized and decentralized distributed control of longitudinal vehicular platoons with non‐uniform communication topology

In this paper, the distributed control of a longitudinal platoon of vehicles with non‐uniform communication topology is studied. In the case of non‐uniform communication topology, some eigenvalues of the network's matrix may be complex which complicates the stability analysis of the platoon. Most previous studies on vehicular platooning focus mainly on uniform topologies such as uni‐directional, bi‐directional, and multi predecessors following. Since all eigenvalues of these topologies are real, the stability analysis can be performed in a straightforward manner. A third‐order linear differential model is employed to describe the upper‐level dynamics of each vehicle. The 3 N‐order closed‐loop dynamics of the platoon are decoupled to individual third‐order dynamics by presenting a new approach. Two new centralized and decentralized control protocols are introduced to perform the stability analysis of the closed‐loop dynamics. A constant time headway strategy is employed to adjust the inter‐vehicle spacing. Simulation results with different scenarios are presented to illustrate the effectiveness of the proposed approaches.     

A curve extension design for coordinated path following control of unicycles along given convex loops

This article utilises a dynamic model of unicycles to address the convergence of vehicle formation about closed convex curves. A novel curve extension method, extending the target loop along the vector from the loop centre to the point on the loop, is proposed to construct a family of level curves and the existence of a loop function on a tubular-like neighbourhood is proved by referring to the tubular neighbourhood theorem. Path following control is derived based on the loop function which incorporated into the arc-length function to propose the solution to coordinated formation control. We show how backstepping technique, Lyapunov-based theory and graph theory can be combined together to construct the coordinated path following controller under the bidirectional commutation topology. It is proved that the designed cooperative control system is asymptotically stable if the graph is connected. The proposed method is effective for a skewed superellipse, which is a type of curve that includes circles, ellipses and rounded parallelograms.     

An internal model approach to autonomous leader/follower trailing for non‐holonomic vehicles

The focus of this paper is on the design of a control architecture of decentralized type for controlling a leader/follower pair of autonomous non‐holonomic vehicles. A fundamental constraint in this trailing control requires that each agent employs local sensor information to process data on the relative position and velocity between its neighbouring vehicles, without relying on global communication with mission control. This constraint poses a challenge in the design of the control system because the reference trajectory to be tracked, which in the case considered in this paper is related to the motion of the leader, is not known a priori. It is shown in the paper that this specific control problem can be approached from the point of view of the internal model paradigm. In particular, once models of the autonomous dynamics of the leader are embedded in a decentralized dynamic controller, the design of the controller can be completed with a robust stabilizer, obtained by using ISS‐gain‐assignment techniques. It is shown that asymptotic convergence of the follower to an arbitrarily small neighbourhood of the desired steady‐state configuration is achieved, despite the presence of possibly large parameter uncertainties, while the motion of each agent remains confined into specified ‘sectors’ to avoid possible collision between neighbouring vehicles during transients. Simulation results are presented to illustrate the design methodology. Copyright © 2006 John Wiley & Sons, Ltd.     

Control of multivehicle systems in the presence of uncertain dynamics

In this paper, we present a cooperative control architecture for high-order multivehicle systems having non-identical nonlinear uncertain dynamics. The proposed methodology consists of a local cooperative controller and a vehicle-level controller for each vehicle. The former controller receives the relative output measurements of the neighbouring vehicles in order to solve a containment problem formulated on a leader–follower framework. Specifically, the leaders generate trajectories in which the vehicles (followers) converge to the convex hull formed by those of the leaders. For a special case with one leader, this controller synchronises the output of the vehicles with the output of the leader. The latter controller receives the internal-state measurements for suppressing the nonlinear uncertain dynamics of the vehicle by using a decentralised adaptive control approach. The interaction topology between vehicles is described by undirected graphs and extensions to directed graphs are further discussed. The stability and convergence properties of the proposed cooperative control architecture are analysed by using the results from linear algebra and the Lyapunov theory. Several numerical examples are provided to demonstrate the efficacy of the proposed cooperative control architecture.     

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.     

Path following of car-like vehicles using dynamic inversion

This paper focuses on a special path following task arising from the needs of vision-based autonomous guidance: a given front point of a car-like vehicle that is within the look-ahead range of a stereo vision system must follow a prespecified Cartesian path. A solution to this path following problem is provided by a new feedforward/feedback control strategy where the feedforward is determined by a dynamic generator based on exact dynamic inversion over the nominal vehicle model and the feedback is mainly issued by correcting terms proportional to the tangential and normal errors determined with respect to the vehicle’s ideal trajectory. A convergence analysis of the resulting dynamic inversion based controller is established versus a vehicle’s uncertain model defined via equation errors. Simulation examples highlighting the controller’s performances are included.     

A path following algorithm for mobile robots

This paper considers path following control for a robotic platform. The vehicle used for the experiments is a specially designed robotic platform for performing autonomous weed control. The platform is four-wheel steered and four-wheel driven. A diesel engine powers the wheels via a hydraulic transmission. The robot uses a Real Time Kinematic Differential Global Positioning System to determine both position and orientation relative to the path. The deviation of the robot to the desired path is supplied to two high level controllers minimizing the orthogonal distance and orientation to the path. Wheel angle setpoints are determined from inversion of the kinematic model. At low level each wheel angle is controlled by a proportional controller combined with a Smith predictor. Results show the controller performance following different paths shapes including a step, a ramp, and a typical headland path. A refined tuning method calculates controller settings that let the robot drive as much as possible along the same path to its setpoint, but also limit the gains at higher speeds to prevent the closed loop system to become unstable due to the time delay in the system. Mean, minimum and maximum orthogonal distance errors while following a straight path on a paving at a speed of 0.5 m/s are 0.0, −2.4 and 3.0 cm respectively and the standard deviation is 1.2 cm. The control method for four wheel steered vehicles presented in this paper has the unique feature that it enables control of a user definable position relative to the robot frame and can deal with limitations on the wheel angles. The method is very well practical applicable for a manufacturer: all parameters needed are known by the manufacturer or can be determined easily, user settings have an easy interpretation and the only complex part can be supplied as a generic software module.     

Inverse optimal self-tuning PID control design for an autonomous underwater vehicle

This paper presents a new approach to path following control design for an autonomous underwater vehicle (AUV). A NARMAX model of the AUV is derived first and then its parameters are adapted online using the recursive extended least square algorithm. An adaptive Propotional-Integral-Derivative (PID) controller is developed using the derived parameters to accomplish the path following task of an AUV. The gain parameters of the PID controller are tuned using an inverse optimal control technique, which alleviates the problem of solving Hamilton–Jacobian equation and also satisfies an error cost function. Simulation studies were pursued to verify the efficacy of the proposed control algorithm. From the obtained results, it is envisaged that the proposed NARMAX model-based self-tuning adaptive PID control provides good path following performance even in the presence of uncertainty arising due to ocean current or hydrodynamic parameter.     

Nonsingular path following control of a unicycle in the presence of parametric modelling uncertainties

A new type of control law is derived to steer the dynamic model of a wheeled robot of unicycle type along a desired path. The methodology adopted for path following control deals explicitly with vehicle dynamics and plant parameter uncertainty. Furthermore, it overcomes stringent initial condition constraints that are present in a number of path following control strategies described in the literature. This is done by controlling explicitly the rate of progression of a ‘virtual target’ to be tracked along the path, thus bypassing the problems that arise when the position of the virtual target is simply defined by the projection of the actual vehicle on that path. In the paper, a nonlinear adaptive control law is derived that yields convergence of the (closed‐loop system) path following error trajectories to zero. Controller design relies on Lyapunov theory and backstepping techniques. Simulation results illustrate the performance of the control system proposed. Copyright © 2006 John Wiley & Sons, Ltd.     

Guidance and nonlinear control system for autonomous flight of minirotorcraft unmanned aerial vehicles

Small unmanned aerial vehicles (UAVs) are becoming popular among researchers and vital platforms for several autonomous mission systems. In this paper, we present the design and development of a miniature autonomous rotorcraft weighing less than 700 g and capable of waypoint navigation, trajectory tracking, visual navigation, precise hovering, and automatic takeoff and landing. In an effort to make advanced autonomous behaviors available to mini‐ and microrotorcraft, an embedded and inexpensive autopilot was developed. To compensate for the weaknesses of the low‐cost equipment, we put our efforts into designing a reliable model‐based nonlinear controller that uses an inner‐loop outer‐loop control scheme. The developed flight controller considers the system's nonlinearities, guarantees the stability of the closed‐loop system, and results in a practical controller that is easy to implement and to tune. In addition to controller design and stability analysis, the paper provides information about the overall control architecture and the UAV system integration, including guidance laws, navigation algorithms, control system implementation, and autopilot hardware. The guidance, navigation, and control (GN&C) algorithms were implemented on a miniature quadrotor UAV that has undergone an extensive program of flight tests, resulting in various flight behaviors under autonomous control from takeoff to landing. Experimental results that demonstrate the operation of the GN&C algorithms and the capabilities of our autonomous micro air vehicle are presented. © 2009 Wiley Periodicals, Inc.     

Finite‐Time Sliding Mode Trajectory Tracking Control of Uncertain Mechanical Systems

The problem of finite‐time tracking control is studied for uncertain nonlinear mechanical systems. To achieve finite‐time convergence of tracking errors, a simple linear sliding surface based on polynomial reference trajectory is proposed to enable the trajectory tracking errors to converge to zero in a finite time, which is assigned arbitrarily in advance. The sliding mode control technique is employed in the development of the finite‐time controller to guarantee the excellent robustness of the closed‐loop system. The proposed sliding mode scheme eliminates the reaching phase problem, so that the closed‐loop system always holds the invariance property to parametric uncertainties and external disturbances. Lyapunov stability analysis is performed to show the global finite‐time convergence of the tracking errors. A numerical example of a rigid spacecraft attitude tracking problem demonstrates the effectiveness of the proposed controller.     

Collision avoidance command governor for multi‐vehicle unmanned systems

In this paper, we consider the problem of coordinating a collection of autonomous unmanned vehicles while guaranteeing collision avoidance. Each vehicle is regulated by a local controller that ensures stability and provides desired path tracking performance in the absence of constraints. The fulfillment of coordination tasks (e.g., collision avoidance) and local constraints (e.g., input saturation constraints) is achieved through a command governor (CG) strategy that, whenever necessary, modifies the nominal paths of the vehicles. First, a centralized CG approach is proposed and fully analyzed. Then, a more interesting distributed implementation requiring low communication rates is discussed. Both approaches make use of a receding horizon strategy and require the on‐line solution of mixed‐integer optimization programs. Finally, an example is given for illustration purposes. Copyright © 2013 John Wiley & Sons, Ltd.     

智能海洋机器人技术进展

智能海洋机器人是可以在复杂海洋环境中执行各种任务的智能化无人平台, 包括智能水下机器人和智能水面机器人. 基于实践和在相关技术难题上的经验, 提出了一些关键技术问题的解决方案. 在智能水下机器人方面, 探讨了体系结构、运动控制、智能规划与决策和系统仿真等关键技术. 在智能水面机器人方面, 探讨了快速性和智能化问题. 我国在智能海洋机器人技术研究方面已经取得了较大的进步, 但距离全面应用还有很大差距.     

基于模糊混合控制的自治水下机器人路径跟踪控制

基于模糊混合控制策略,本文提出了一种用于非线性欠驱动自治水下机器人的鲁棒路径跟踪控制方法.利用Sugeno型模糊推理系统,将PD滑模控制器与非奇异终端滑模控制器光滑连接,构造了模糊混合控制器.它能充分融合这两类控制器的优势,无论系统远离平衡点还是在其附近,都能取得快速收敛的效果.如果,借助于非时间参考量,将该混合控制器用于自治水下机器人路径跟踪控制,将有利于提高它在不确定环境中的跟踪能力.最后,通过仿真计算结果验证了该控制策略的有效性.