基于虚拟群集中心的局部信息下多移动机器人编队控制研究

针对移动机器人感知能力有限,仅能根据周围邻居的行为对自身的运动进行调节的问题,在REYNOLDS提出的群集运动规则的指导下,设计了一种基于虚拟群集中心的多移动机器人编队控制算法。通过设计分布式虚拟群集中心估计器,使每个个体都向自身的虚拟群集中心靠拢,并通过理论分析证明了所设计的虚拟群集中心都能最终收敛到实际的群集中心。在此基础上,利用人工势场法和速度一致准则实现了多移动机器人的编队运行。实验结果表明:移动机器人群集在领航机器人的带领下最终会进入稳定运行状态,个体速度趋于一致,相互间的距离保持稳定。     

非完整约束大负重比六足机器人多机动态协同编队避障控制策略

在多机器人编队任务的现实环境中,不可避免会遇到队形变换的动态编队问题。为提高非结构环境多机器人编队的动态协同避障能力,以大负重比六足机器人的多机器人系统为例,利用非完整约束移动机器人轨迹跟踪的领航者-跟随者编队思想,提出多领航机器人分群一致性编队控制的动态队形变换避障策略。基于代数图论数学基础,设计大负重比六足机器人多机通信拓扑图与拓扑图分析矩阵,建立多领航者分群一致性编队系统的全局动态关系与一致性数学模型,提出多领航机器人分群一致性编队控制的动态队形变换避障策略,基于MATLAB软件实施仿真实验,仿真结果显示虚拟领航机器人发布控制指令使多机系统完成队形变换并顺利通过障碍物环境,验证多机动态协同编队避障控制策略的有效性和泛化能力。所提出的大负重比六足机器人多机动态协同编队避障控制策略,有助于提高非结构环境多机器人系统的地形通过能力。     

基于领航者的多机器人模糊队形控制

提出一种基于领航者的多机器人模糊队形控制方法,便于在恶劣的不确定环境下实现编队。跟随机器人依靠自身获取的信息跟随其领航机器人,保持与领航机器人期望的相对距离和相对方位角,并利用与领航机器人之间的距离偏差,采用比例控制器控制机器人速度大小。基于跟随机器人与领航机器人之间方位角的角度偏差及偏差变化率,模糊控制调整角度,得出输出量控制机器人方向。仿真结果表明该队形控制方法的有效性和可行性。     

多AUV编队控制

使用一致性算法l-φ和虚拟领航跟随结构法研究自主水下机器人的集群编队控制.基于一致性算法l-φ对各AUV所持有的参考信息进行一致性协商而达到状态一致.基于虚拟结构思想,将编队控制问题转化为跟随AUV对虚拟领航AUV的轨迹跟踪控制,使得各AUV相对于虚拟领航者的位置且在有限的时间内确保到达各自的期望位置.通过Java的GUI编程进行仿真实验来验证控制策略的有效性.     

多移动微小型机器人编队控制与协作避碰研究

针对多移动微小型机器人系统的协作避碰和队形保持,给出了一种分布式的编队控制方法。结合移动微小型机器人的运动控制模型,提出了一种路径规划方法,使其在运动中实时避免碰撞。在此基础上利用李雅普诺夫(Lyapunov)法设计了一种编队控制器。在有界误差范围内,该控制器能够保证多机器人的轨迹跟踪和协作避碰。通过将编队控制转化为跟踪整个队形质心的轨迹,降低了控制的复杂度,从而可以较好地应用到计算资源有限的多移动微小型机器人中。通过仿真、分析和对比,对以上控制方法的稳定性和可行性进行了验证,并进行了实际的编队和避碰控制实验。实验结果表明该方法可有效地应用于多移动微小型机器人的协作避碰和编队控制。     

多机器人系统的编队路径跟踪控制

介绍了一种多机器人系统的编队路径跟踪控制方法。首先将非完整约束机器人的动态方程转化为跟随者和领航员间相对运动模型,克服了非完整约束机器人结构奇异的缺点。随后将滑模控制方法应用于多机器人系统中,分别设计了领航员跟踪希望路径的滑模控制律和跟随者跟踪领航员的滑模控制律。算例仿真表明了应用本文介绍的编队路径跟踪控制律,各机器人能够较快地形成希望的编队,并按希望队形跟踪希望路径。仿真结果验证了此控制方法的有效性。     

一种足式移动机器人的混合视觉伺服控制方法

针对一种配有单目相机的足式移动机器人,提出一种基于图像单应性的混合视觉伺服方法,利用单应性矩阵中的元素构造状态变量估计估计机器人相对位姿,使机器人在缺乏深度信息的情况下可准确到达目标位姿。相较于轮式移动机器人,在足式机器人移动过程中,足式机构的间歇性运动直接影响机器人视觉反馈过程和伺服控制系统的准确性和稳定性。为解决这一问题,通过分析足式机构运动学并建立足式机器人移动速度与电机转速的映射关系,使控制器可以更准确地调整机器人运动速度。考虑到足式机构运动对视觉反馈环节的影响,提出一种改进型自适应中值滤波算法提高位姿估计精度。伺服环节设计了滑模控制器,并采用李雅普诺夫方法证明了控制系统的稳定性。最后,利用CoppeliaSim软件搭建足式移动机器人虚拟模型,通过仿真验证了所提出控制方案的可行性与有效性。     

全方位移动机器人编队控制研究

针对多机器人系统编队的控制问题,将编队行为分为了任务执行行为、队形保持行为、安全运行行为,并分别对各行为进行了研究,对各种传统编队方法进行了总结和比较,通过建立移动机器人的运动学模型,得到了车体运动的控制参数,提出了针对基于麦克纳姆轮的全方位移动机器人编队的基于行为的融合编队控制算法,利用Matlab软件对编队的各种行为进行了仿真。研究结果表明,该基于行为的融合编队控制算法能使全方位机器人完成编队行为,能够实现队形形成、队形保持、躲避静态障碍物、躲避机器人及驶向目标点等行为,编队基于该方法,实现迅速、可靠性高。     

非完整移动机器人的双自适应神经滑模控制

针对非完整移动机器人轨迹跟踪控制问题,提出一种基于Backstepping运动学控制器与双自适应神经滑模鲁棒动力学控制的混合鲁棒控制算法.利用两个带自适应调节算法的径向基神经网络(Radial basis function neural network,RBFNN)分别计算滑模的等效控制部分和调节滑模控制的增益,不但解决了移动机器人的参数与非参数不确定性问题,同时也消除了在滑模控制中的输入抖振现象.设计过程采用Lyapunov方法,保证了控制系统的稳定与收敛.仿真结果表明了该方法的有效性,且在多种不确定性存在的情况下,该方法能较好地消除非完整机器人的跟踪误差.     

一种改进的多机器人队形形成算法

针对多机器人系统编队控制中的队形形成问题,提出一种改进的基于行为分解的编队控制方法。此算法采用重心法获取机器人的动态目标点,依据有限状态机的原理,将动态目标点产生的运动需求分解为机器人不同子行为,通过对子行为归一化处理得到最终行为控制矢量,控制机器人运动。实验结果表明,该方法能快速有效的形成期望的圆形队形。     

基于领航跟随法的多AUV编队控制算法研究

针对已知路径下基于领航者的多自主水下机器人(AUV)编队队形控制问题,提出了一种AUV路径控制和编队协调控制相结合的新型编队控制器。其中,AUV的路径跟踪控制采用反步滑模控制器,将AUV位置、姿态和时变速度跟踪转化虚拟速度控制,使AUV能达到期望的位置、速度等,避免了反步控制中的奇异值问题,并能够很好实现不确定的模型的控制,同时又提高了跟随者协同定位精度;在路径跟踪控制基础上,编队协调控制器将领航者与跟随者的位置误差控制转化为跟随者的速度误差控制,使跟随者能快速达到期望位置,从而使所有AUV实现期望的队形并保持。仿真实验对该控制策略进行了可行性验证,结果表明,该算法提高了编队的响应速度、控制精度和稳定性;再应用3台AUV进行了湖上试验验证,证明了该控制策略的有效性,能有效应用到实际中。     

Adaptive PID formation control of nonholonomic robots without leader's velocity information

This paper proposes an adaptive proportional integral derivative (PID) algorithm to solve a formation control problem in the leader–follower framework where the leader robot's velocities are unknown for the follower robots. The main idea is first to design some proper ideal control law for the formation system to obtain a required performance, and then to propose the adaptive PID methodology to approach the ideal controller. As a result, the formation is achieved with much more enhanced robust formation performance. The stability of the closed-loop system is theoretically proved by Lyapunov method. Both numerical simulations and physical vehicle experiments are presented to verify the effectiveness of the proposed adaptive PID algorithm.     

Distributed coordinated attitude tracking control for spacecraft formation with communication delays

This paper investigates the distributed coordinated attitude tracking control problem for spacecraft formation with time-varying communication delays under the condition that the dynamic leader spacecraft is a neighbor of only a subset of follower spacecrafts. We consider two cases for the leader spacecraft: i) the attitude derivative is constant, and ii) the attitude derivative is time-varying. In the first case, a distributed estimator is proposed for each follower spacecraft by using its neighbors’ information with communication delays. In the second case, to express the dynamic leader’s attitude, an improved distributed observer is developed to estimate the leader’s information. Based on the estimated values, adaptive coordinated attitude tracking control laws are designed to compensate for parametric uncertainties and unknown disturbances. By employing the Lyapunov–Krasovskii functional approach, the attitude tracking errors and estimation errors are proven to converge to zero asymptotically. Numerical simulations are presented to illustrate the effectiveness of theoretical results.     

A switching formation strategy for obstacle avoidance of a multi-robot system based on robot priority model

This paper describes a switching formation strategy for multi-robots with velocity constraints to avoid and cross obstacles. In the strategy, a leader robot plans a safe path using the geometric obstacle avoidance control method (GOACM). By calculating new desired distances and bearing angles with the leader robot, the follower robots switch into a safe formation. With considering collision avoidance, a novel robot priority model, based on the desired distance and bearing angle between the leader and follower robots, is designed during the obstacle avoidance process. The adaptive tracking control algorithm guarantees that the trajectory and velocity tracking errors converge to zero. To demonstrate the validity of the proposed methods, simulation and experiment results present that multi-robots effectively form and switch formation avoiding obstacles without collisions.     

Distributed ESO based cooperative tracking control for high-order nonlinear multiagent systems with lumped disturbance and application in multi flight simulators systems

Based on extended state observer, a novel and practical design method is developed to solve the distributed cooperative tracking problem of higher-order nonlinear multiagent systems with lumped disturbance in a fixed communication topology directed graph. The proposed method is designed to guarantee all the follower nodes ultimately and uniformly converge to the leader node with bounded residual errors. The leader node, modeled as a higher-order non-autonomous nonlinear system, acts as a command generator giving commands only to a small portion of the networked follower nodes. Extended state observer is used to estimate the local states and lumped disturbance of each follower node. Moreover, each distributed controller can work independently only requiring the relative states and/or the estimated relative states information between itself and its neighbors. Finally an engineering application of multi flight simulators systems is demonstrated to test and verify the effectiveness of the proposed algorithm.     

打滑状态下的多机器人编队控制

讨论打滑状态下的多机器人编队控制器设计问题。打滑现象会使机器人偏离正常的运动轨迹,导致基于理想环境设计的控制器控制效果变差,甚至发生机器人失控的现象。考虑打滑因素的控制算法能使机器人适应更一般的环境,增强机器人的实际可用性。采用领导者-跟随者策略来协调各机器人的运动。领导者机器人的运动规律根据任务需要事先设定,随后控制跟随者机器人以一定距离和角度跟随领导者机器人运动。根据机器人的运动特性导出单机器人在打滑情况下的运动规律,并据此导出两机器人以距离-角度模型形成编队的方程。采用二阶滑模控制法来为跟随者机器人设计控制器,使得两机器人在运动过程中能够形成期望的队形。以Matlab仿真来验证算法的有效性。理论推导及仿真结果说明,导出的编队模型能够准确描述机器人在有打滑情况时的运动规律,二阶滑模编队算法具有较好的抗干扰能力,适用性强。     

Integrated control strategy for CVT powertrains with consideration of vehicle drivability

During shift,power flow is not interrupted in powertrains equipped with continuously variable transmission(CVT).When hard acceleration is commanded,engine speed will flare and corresponding torque will be consumed,which leads to a drop in vehicle drive torque and also the vehicle acceleration.This is the reason why CVT vehicles have poor drivability during hard acceleration maneuver.Conventional method such as torque compensation doesn’t always work due to the limited backup torque of engine.According to this,means to evaluate the drivability of CVT vehicles are studied,affect factors of drivability are analyzed in detail.Hard acceleration process of CVT vehicle is studied by theoretical analysis,based on which engine torque and ratio change rate of CVT are identified as two key control parameters that decide the drivability of CVT vehicles during hard acceleration maneuver.Therefore,a control strategy based on restricting the change rate of CVT ratio together with torque compensation is proposed,and two different algorithms to establish the limitation of ratio change rate are proposed.These two algorithms are simulated and compared with each other,results indicate that drop of vehicle acceleration is eliminated evidently by limit the change rate of CVT ratio,but small ratio change rate also results in a longer time to finish the accelerate process,an algorithm to decide a proper ratio change rate is needed in order to tune these different characteristics.In order to get better control effects,a new fuzzy logic based algorithm is proposed to decide a proper ratio change rate during kick down conditions,simulation and experiment results indicate that,the amount of vehicle acceleration decrease is reduced from about 1 m/s2 to almost 0,in the mean time the accelerate process only delayed for about 0.3 s.The proposed control strategy and algorithm can effectively tune the characteristics of CVT equipped vehicle during kick down conditions.     

基于遗传优化的无人车横向模糊控制

以视觉导航式无人车DLUIV-1为控制对象,对其进行横向运动控制研究。建立视觉导航式无人车横向运动控制系统模型,对无人车的横向运动行为进行描述。在此基础上,分析预瞄距离对横向控制系统动态性能的影响,并建立考虑速度因素的预瞄距离计算公式。针对无人车具有非完整运动约束、高度非线性动态特性以及参数的不确定性等特点,提出基于遗传算法的无人车横向模糊控制策略,通过遗传算法对横向模糊控制器的隶属度函数参数和控制规则的自动优化,从而有效地确定出横向模糊控制器的隶属度函数和控制规则。最后通过仿真和实车试验对该横向模糊控制器进行验证和评价,仿真和试验结果表明,该横向控制器可保证无人车稳定准确地跟踪参考路径,且具有较强的鲁棒性。     

Decentralized control of quadrotors in a leader–follower formation

A problem of control of quadrotors in a leader–follower formation is considered. A method is proposed, which allows control actions for the follower robot to be formed only on the basis of information about the follower motion parameters and the relative positions of the leader and follower.     

Surrounding control of nonlinear multi-agent systems with non-identical agents

In this paper, the surrounding control problem of a group of non-identical agents is considered, where a team of followers achieves an equidistant distributed formation to surround a team of moving leaders. An adaptive design method is presented for multi-agent systems where the dynamics of agents are supposed to be nonlinear with unknown parameters. First, an estimator for the center of the leaders is introduced. Then, two distributed adaptive controllers based on the estimated center are proposed for each follower. The stability and parameter convergence of the proposed protocols are shown by using algebraic graph theory and Lyapunov theory. Finally, a numerical example is provided to validate the theoretical results.