一种新的AUV路径跟踪控制方法

研究了自主水下航行器(AUV)的路径跟踪问题,将跟踪控制问题分为导引和控制2部分.导引部分基于视线导引(Line of Sight)原理输出AUV的参考航向,针对AUV的参数不确定性及海流干扰等特点,航向控制器采用变结构控制律计算舵角控制输入,在此基础上,将航向控制器与路径跟踪控制器并行结合,构造了文中提出的混合型路径跟踪控制器.文章从理论上证明了控制律的稳定性,仿真结果表明,所设计的控制律可以保证AUV沿期望路径航行,路径跟踪误差快速收敛.     

AUV平面直线航迹跟踪控制算法

针对自主水下航行器（AUV）在平面直线航迹跟踪过程中的航迹超调问题,设计基于航向航速双闭环运动控制的航迹跟踪控制算法. 跟踪算法以视线导引法（LOS）为基础,设计时变前视距离提高AUV的机动性,并以一阶惯性滤波抑制因航向切换产生期望航向角的阶跃变化. 控制算法采用抗积分饱和PID控制及参数自适应,以增加算法的鲁棒性,并将航向航速控制设计成双闭环,使得 AUV航行时期望航迹段终点的距离偏差实时调整期望航速. 结果表明,此航迹跟踪控制算法根据距离偏差调节实时航速,可使AUV提前减速以低速转向,抗积分饱和可避免航速超调,参数自适应以适应多种航行工况. AUV能准确跟踪期望航迹,最大航迹偏差小于1.0 m,并且大角度转向时可有效减小航迹超调.     

高速无人驾驶车辆轨迹跟踪和稳定性控制

针对高速无人驾驶车辆运动控制过程中轨迹跟踪精度和稳定性难以同时保障的问题,提出综合前馈-反馈及自抗扰控制(ADRC)补偿相结合的横向控制算法. 通过车速和道路曲率信息计算前馈稳态前轮转向角,将质心侧偏角引入航向偏差,以车辆航向角偏差和侧向偏差作为参考量进行反馈控制,通过前馈-反馈控制提升瞬态轨迹跟踪性能. 设计自抗扰控制器,通过扩张状态观测器对未建模动态和内外界干扰进行估计,通过将后轮侧偏角控制在参考值附近来补偿前轮转角,提升无人驾驶车辆的转向稳定性和控制器的鲁棒性. 不同工况下的仿真结果表明,利用该方法可以保证高速无人驾驶车辆稳定地跟踪期望路径行驶,轨迹跟踪偏差较小,对车辆参数变化和外界干扰具有较强的鲁棒性.     

AUV的精确航迹跟踪系统的鲁棒控制

为了解决外界海洋环境干扰下水下无人航行器(AUV)的精确航迹跟踪控制问题,针对欠驱动AUV动力学运动模型不确定性,将三维航迹跟踪控制分解为水平面和垂直面跟踪控制问题,分别建立了AUV水平面和垂直面动力学模型,在设计模型时考虑了线性近似产生的误差、不确定性和外界干扰的影响,根据鲁棒H∞控制理论设计了航向控制器和纵倾控制器.仿真结果表明,系统存在外界海流情况下,AUV能够克服外界干扰海流的影响运动到设定航迹上,跟踪误差收敛于0,控制效果良好.文中所设计的鲁棒H∞控制器能够有效克服外界干扰的影响,较精确的实现了航迹跟踪.     

基于改进PSO-GWO算法的无人艇路径跟踪控制系统研究

随着海洋经济的迅猛发展,水面无人艇(Unmanned Surface Vehicle,USV)的重要性更加显著。由于无人艇本身具有非线性不确定性和欠驱动的特点,在航行过程中易受到风、浪等环境因素的干扰,使得未知扰动下USV的路径跟踪控制问题非常困难。将无人艇路径跟踪控制分解为对USV航向的控制和导引策略的设计两个问题。首先采用由粒子群算法改进的灰狼算法(PSO-GWO)对自抗扰航向控制器的相关参数进行在线整定,降低了传统自抗扰控制器参数调整的复杂度;再设计LOS导引策略计算期望航向角,实现对USV的路径跟踪控制。经Matlab仿真实验验证,所设计的系统能实现对航向角的快速稳定跟踪,具有很强抗干扰能力;USV在给定航行速度下能以较短路径到达期望的直线路径和曲线路径,跟踪精度高。     

考虑未知死区非线性的自适应模糊神经UUV航迹跟踪控制

针对无人水下航行器(unmanned underwater vehicles, UUV)在航迹跟踪控制中存在未知死区非线性和工作环境不确定性的问题,提出一种鲁棒自适应自组织模糊神经控制策略,采用滑模趋近律控制框架和自组织模糊神经网络逼近器在线估计系统未知状态和进行参数的自适应,并采用有限增益鲁棒控制器补偿重构误差。根据李雅普诺夫稳定性理论分析证明所有参数和跟踪状态均有界,并且当时间趋向于无穷大时,跟踪误差及其导数都趋向于零且闭环系统的信号有界。通过与已有控制策略对比仿真表明,该控制策略具有先进性和有效性,对无人水下航行器设计具有指导意义。     

考虑未知死区非线性的自适应模糊神经UUV航迹跟踪控制

针对无人水下航行器(unmanned underwater vehicles, UUV)在航迹跟踪控制中存在未知死区非线性和工作环境不确定性的问题,提出一种鲁棒自适应自组织模糊神经控制策略,采用滑模趋近律控制框架和自组织模糊神经网络逼近器在线估计系统未知状态和进行参数的自适应,并采用有限增益鲁棒控制器补偿重构误差。根据李雅普诺夫稳定性理论分析证明所有参数和跟踪状态均有界,并且当时间趋向于无穷大时,跟踪误差及其导数都趋向于零且闭环系统的信号有界。通过与已有控制策略对比仿真表明,该控制策略具有先进性和有效性,对无人水下航行器设计具有指导意义。     

融合侧倾稳定性的智能客车轨迹跟踪增益调度控制策略

基于三自由度智能客车简化模型,考虑了智能客车易发生侧翻稳定性问题,采用轨迹跟踪与侧倾稳定性相结合的方式,利用多点预瞄的LQR(Linear quadratic regulator)最优控制算法,提出了智能客车轨迹跟踪控制策略.本策略采用增益调度方法,以实现变化车速工况的客车轨迹跟踪控制,搭建了Matlab/Simulink软件与Trucksim软件联合仿真平台,进行智能客车轨迹跟踪控制策略软件在环仿真实验.结果表明:所提控制策略适应了智能客车轨迹跟踪过程中的车速动态变化,实现了轨迹位移和航向角平滑稳定良好地跟踪,最大侧向位移误差率和最大航向角峰值误差率分别为1.56％和2.14％,保证了轨迹跟踪过程中智能客车横摆侧倾稳定性.     

无人水下航行器PID神经网络解耦控制

通过无人水下航行器动力学分析和运动建模,将系统解耦为航向、横滚、纵向三通道控制系统。为了消除解耦过程中存在的问题,采用PID神经网络控制算法来实现三自由度的独立控制。仿真结果表明,该控制方法不仅减少了计算时间,提高了响应速度,而且具有超调量小、稳态精度高等控制品质,对无人水下航行器的实际应用具有一定意义。     

机器人系统鲁棒轨迹跟踪控制器设计

针对机器人系统的轨迹跟踪控制问题,考虑实际系统中存在的不确定性,基于动态系统终值有界性引理,采用连续状态反馈的方法,设计出一种鲁棒轨迹跟踪控制器。仿真结果表明,此法设计的控制器对机器人系统的参数不确定性具有较好的鲁棒性,可保证不确定性存在情况下跟踪误差的终值有界性。     

基于动态反馈的AUV水平面路径跟踪控制

针对离散自治水下机器人水平面的路径跟踪控制问题,利用水下机器人的位置和姿态角量测信息,提出神经网络自适应输出反馈控制器.所设计的控制器包括3部分,镇定水下机器人动态系统线性部分的动态反馈控制器;神经网络控制器,用来补偿水下机器人受到环境干扰引起的水动力系数变化的不确定非线性结构;补偿环境扰动和神经网络带来的重构误差的鲁棒控制器.基于离散非线性系统理论,对水下机器人水平面跟踪误差系统进行分析,得到系统的跟踪误差最终一致有界.所提出的控制方法具有对模型精确度要求低的优点,利用INFANTE水下机器人模型进行仿真分析验证了提出的控制算法的有效性.     

Symbol Reference Model of Desired Yaw Angle for Automated Lane Changing Behavior of Vehicle

In this paper, it studies the problem of trajectory planning and tracking for lane changing behavior of vehicle in automatic highway systems. Based on the model of yaw angle acceleration with positive and negative trapezoid constraint, by analyzing the variation laws of yaw motion of vehicle during a lane changing maneuver, the reference model of desired yaw angle and yaw rate for lane changing is generated. According to the yaw angle model, the vertical and horizontal coordinates of trajectory for vehicle lane change are calculated. Assuming that the road curvature is a constant, the difference and associations between two scenarios are analyzed, the lane changing maneuvers occurred on curve road and straight road, respectively. On this basis, it deduces the calculation method of desired yaw angle for lane changing on circular road. Simulation result shows that, it is different from traditional lateral acceleration planning method with the trapezoid constraint, by applying the trapezoidal yaw acceleration reference model proposed in this paper, the resulting expected yaw angular acceleration is continuous, and the step tracking for steering angle is not needed to implement. Due to the desired yaw model is direct designed based on the variation laws of raw movement of vehicle during a lane changing maneuver, rather than indirectly calculated from the trajectory model for lane changing, the calculation steps are simplified.     

Reference Model of Desired Yaw Angle for Automated Lane Changing Behavior of Vehicle

In this paper,it studies the problem of trajectory planning and tracking for lane changing behavior of vehicle in automatic highway systems. Based on the model of yaw angle acceleration with positive and negative trapezoid constraint,by analyzing the variation laws of yaw motion of vehicle during a lane changing maneuver,the reference model of desired yaw angle and yaw rate for lane changing is generated. According to the yaw angle model,the vertical and horizontal coordinates of trajectory for vehicle lane change are calculated. Assuming that the road curvature is a constant,the difference and associations between two scenarios are analyzed,the lane changing maneuvers occurred on curve road and straight road,respectively. On this basis,it deduces the calculation method of desired yaw angle for lane changing on circular road. Simulation result shows that,it is different from traditional lateral acceleration planning method with the trapezoid constraint,by applying the trapezoidal yaw acceleration reference model proposed in this paper, the resulting expected yaw angular acceleration is continuous,and the step tracking for steering angle is not needed to implement. Due to the desired yaw model is direct designed based on the variation laws of raw movement of vehicle during a lane changing maneuver, rather than indirectly calculated from the trajectory model for lane changing, the calculation steps are simplified.     

Intelligent PID guidance control for AUV path tracking

Based on rational behavior model of three layers, a tracking control system is designed for straight line tracking which is commonly used in underwater survey missions. An intelligent PID control law implemented as planning level during the control system using transverse deviation is came up with. Continuous tracking of path expressed by a point sequence can be realized by the law. Firstly, a path tracking control system based on rational behavior model of three layers is designed, mainly satisfying the needs of underactuated AUV. Since there is no need to perform spatially coupled maneuvers, the 3D path tracking control is decoupled into planar 2D path tracking and depth or height tracking separately. Secondly, planar path tracking controller is introduced. For the reason that more attention is paid to comparing with vertical position control, transverse deviation in analytical form is derived. According to the Lyapunov direct theory, control law is designed using discrete PID algorithm whose parameters obey adaptive fuzzy adjustment. Reference heading angle is given as an output of the guidance controller conducted by lateral deviation together with its derivative. For the purpose of improving control quality and facilitating parameter modifying, data normalize modules based on Sigmoid function are applied to input-output data manipulation. Lastly, a sequence of experiments was carried out successfully, including tests in Longfeng lake and at the Yellow sea. In most challenging sea conditions, tracking errors of straight line are below 2 m in general. The results show that AUV is able to compensate the disturbance brought by sea current. The provided test results demonstrate that the designed guidance controller guarantees stably and accurately straight route tracking. Besides, the proposed control system is accessible for continuous comb-shaped path tracking in region searching.     

基于横摆角速度反馈的电动助力转向车辆操纵稳定性分析

提出一种基于横摆角速度反馈的车辆横向稳定性控制方法,以横摆角速度为控制目标,利用前馈补偿控制产生横摆力矩和附加的前轮转角,通过对车辆转向角的修正,使车辆转向行驶时的横摆角速度很好地跟踪参考模型.对车辆转向系统不加入反馈、加入正反馈和加入负反馈3种工况分别进行试验分析,试验表明该方法能有效地控制车辆横摆角速度,同时减轻驾驶员操纵负担.     

海流干扰下的欠驱动AUV三维路径跟踪控制

为解决存在海流干扰和模型不确定性情况下欠驱动自主水下航行器(AUV)的三维路径跟踪控制问题,首先在Serret-Frenet坐标系下,基于虚拟向导建立了跟踪误差模型.然后,在运动学控制器中基于李雅普诺夫(Lyapunov)理论和反步法设计具有自适应律的虚拟向导和一种改进的积分视线法(ILOS)导引律,克服了海流的干扰并减少了超调.应用反步自适应滑模控制(BASMC)理论设计动力学控制器,保证了系统的稳定性和鲁棒性.最后,应用非线性级联理论证明了整个控制系统的闭环稳定性.仿真结果表明:基于AUV与流体的相对速度来实现的控制律,便于工程应用.该控制器能够有效克服海流和模型不确定的影响,实现对三维路径的跟踪.     

基于微分平滑的欠驱动船舶航迹控制

对于欠驱动船舶水平面运动的直接航迹控制问题,由于其具有欠驱动和非线性的特点,不能采用静态反馈线性化的方法来处理．首先证明了欠驱动船舶航迹控制系统属于微分平滑系统,基于微分平滑系统中所有状态量均可表示为平滑输出及其导数的函数这一特点,在进行船舶航迹控制器设计时,采用直接动态反馈线性化的方法,建立模型的等价表达式,并将其解耦成为2个可控的线性系统,设计反馈控制律,使欠驱动水面船舶在外界干扰的情况下相对于预先设定的航迹,跟踪误差全局渐近镇定．该方法解除了以往轨迹跟踪控制律中要求角速度持续激励的假设条件．通过仿真试验验证了该方法的有效性。     

潜艇近水面舵减横摇的改进变结构控制

为了提高横摇控制性能,依据潜艇舵减横摇的原理和变结构控制理论,在潜艇非线性模型基础上提出了航向控制器和横摇控制器的设计方法.该方法以航向角和横摇角各自的偏差及其导数建立变结构控制切换面,选取相应的指数趋近律,分别计算了航向和横摇的变结构控制律,最后利用加权方法得到了总的方向舵控制规律.针对变结构控制的抖振现象,利用自适应双神经元对趋近率进行在线修正.仿真研究表明,改进变结构控制提高了近水面航行潜艇水平面操纵控制的性能.     

Direct adaptive control for lane keeping in intelligent vehicle systems

In this paper, with parametric uncertainties such as the mass of vehicle, the inertia of vehicle about vertical axis, and the tire cornering stiffness, we deal with the vehicle lateral control problem in intelligent vehicle systems. Based on the dynamical model of vehicle, by applying Lyapunov function method, the control problem for lane keeping in the presence of parametric uncertainty is studied, the direct adaptive algorithm to compensate for parametric variations is proposed and the terminal sliding mode variable structure control laws are designed with look-ahead references systems. The stability of the system is investigated from the zero dynamics analysis. Simulation results show that convergence rates of the lateral displacement error, yaw angle error and slip angle are fast.