欠驱动自主水面船的非线性路径跟踪控制

基于级联方法提出一种欠驱动自主水面船的全局K指数稳定路径跟踪控制算法.采用以自由路径参考点为原点的Serret-Frenet坐标系建立路径跟踪误差的动态模型,以路径参数的变化率为附加控制输入,克服了以正交投影点为坐标原点时的奇异值问题.设计路径跟踪航向角指令,将路径跟踪模型分解为位置跟踪子系统和航向角、前向速度跟踪子系统两个子系统级联的形式,设计航向角和前向速度的全局指数稳定跟踪控制器,应用级联系统理论证明了路径跟踪误差的全局K指数稳定性.数学仿真和自主水面船湖上实验结果验证了该路径跟踪控制算法的有效性.     

Constrained Moving Path Following Control for UAV With Robust Control Barrier Function

This paper studies the moving path following(MPF)problem for fixed-wing unmanned aerial vehicle(UAV) under output constraints and wind disturbances. The vehicle is required to converge to a reference path moving with respect to the inertial frame, while the path following error is not expected to violate the predefined boundaries. Differently from existing moving path following guidance laws, the proposed method removes complex geometric transformation by formulating the moving path following pr...     

基于自适应神经网络的AUVs路径跟踪控制

为解决由于随时间变化水动力阻尼引起的参数变化和不确定性的问题,提出了基于径向基函数神经网络的未知评估算法,引入自适应算法以保证神经网络权值的最优评估.基于Lyapunov稳定性理论,设计一种自适应神经网络控制器以保证路径跟踪系统中所有误差状态都趋于稳定.为了验证该控制器的可行性,对系统施加如位置误差、方向误差等虚拟干扰,证明该控制器可将误差消减为零.另一方面,机器人在以恒定的速度行驶时,每个航点被指定一个适合半径的圆弧可以保证其有较高的精度.为了评估路径跟踪控制器的性能,提出直线型和直线加圆弧型路径方案.仿真结果表明,该控制器可以有效地消除机器人非线性和模型不确定性造成的干扰.     

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.     

基于非线性迭代滑模的欠驱动UUV三维航迹跟踪控制

为实现欠驱动无人水下航行器(Unmanned underwater vehicle, UUV)在未知海流干扰作用下的三维航迹跟踪控制, 提出一种基于工程解耦思想设计的非线性迭代滑模航迹跟踪控制器. 基于虚拟向导的方法,建立UUV空间航迹跟踪误差方程;采用迭代方法设计非线性滑模控制器, 无需对UUV模型参数不确定部分和海流干扰进行估计,避免了舵的抖振现象以及减小了稳态误差与超调问题. 仿真实验表明,设计的控制器对欠驱动UUV系统的模型参数摄动及海流干扰变化不敏感、 且设计参数易于调节,可以实现三维航迹的精确跟踪.     

A Second Order Sliding Mode Path Following Control for Autonomous Surface Vessels

This paper presents a path following control design for an autonomous surface vessel. The boat considered presents three degrees of freedom being driven by two independent propellers placed at its stern and is represented by a highly nonlinear underactuated dynamic model. The control objective is to reach and closely follow a pre‐specified trajectory, operating in an environment perturbed by currents and waves. This objective is achieved through a control scheme based on the interaction of guidance laws synthesized by Lyapunov techniques and a high order sliding mode control approach based on the Super Twisting Algorithm. This methodology allows designing robust and simple controllers that avoid chattering effects on sliding surfaces, producing continuous control actions and presenting a reduced computational burden. The control performance is analyzed through representative simulations.     

Finite-Time Sideslip Differentiator-Based LOS Guidance for Robust Path Following of Snake Robots

This paper presents a finite-time sideslip differentiator-based line-of-sight(LOS) guidance method for robust path following of snake robots. Firstly, finite-time stable sideslip differentiator and adaptive LOS guidance method are proposed to counteract sideslip drift caused by cross-track velocity. The proposed differentiator can accurately observe the cross-track error and sideslip angle for snake robots to avoid errors caused by calculating sideslip angle approximately. In our method, the des...     

Robust Position Stabilization of Underactuated Surface Vessels With Unknown Modeling Parameters Via Simple P/D‐Like Feedback: The Center Manifold Approach

In this work, two smooth time‐invariant control laws are proposed to achieve asymptotic position stabilization of underactuated surface vessels despite modeling parameter uncertainties. The proposed control laws take a strikingly simple linear proportional derivative (PD)‐like feedback form or just a simplest proportional (P)‐like one, where the former relies on measuring the relative position error and surge/yaw velocity and the latter relies on measuring only the relative position error, decreasing or minimizing the sensing cost. The stabilities of the closed‐loop systems for the both control laws are strictly proved via the center manifold approach despite the unknown model parameters. The effectiveness of the proposed control laws is verified by simulation examples.     

离轴式带拖车移动机器人的路径跟踪控制

研究了离轴式拖车移动机器人系统任意一节车体的几何路径跟踪问题. 首先推导出系统的时间--状态线性化模型并证明了系统的能控性; 然后应用内模原理设计了线性动态反馈控制律, 该控制律可以保证路径跟踪误差有界和最终一致有界, 且最终一致界正比于期望路径函数变化率的立方. 仿真结果证实了控制律的有效性.     

非线性系统的神经网络鲁棒自适应跟踪控制

针对一类具有未知非线性函数和未知虚拟系数非线性函数的二阶非线性系统,提出了一种神经网络鲁棒自适应输出跟踪控制方法.用李雅普诺夫稳定性分析方法证明了本文的神经网络自适应控制器能够使受控系统内的所有信号均为有界.选择的神经网络权值调整规律可以防止自适应控制中的参数漂移.     

固定时间预测器下的欠驱动无人艇路径跟踪控制

无人艇是一类在水面自主移动的智能船艇, 具有无人自主, 航速高, 欠驱动的特点, 能应用到民用和军事的诸多领域. 针对欠驱动无人艇的路径跟踪问题, 本文在传统视线法制导律的基础上, 首次提出了一种新的固定时间收敛的预测器, 用于预测位置误差, 实现对干扰的估计和补偿. 与基于有限时间收敛的预测器的制导律相比, 固定时间预测器收敛时间不依赖于初始状态, 可以更快收敛. 此外, 为了保证跟踪控制器的有效收敛, 还设计了固定时间控制器, 将无人艇尾部的方向舵力矩作为控制器, 使无人艇航向角在固定时间收敛到期望艏向角. 最后通过仿真实验证明本文所提出的制导律和控制器能精确跟踪给定路径.     

不确定性系统的局部模型跟踪控制

针对线性失配不确定性系统，提出了局部模型跟踪、复合参考模型和控制系统匹配度等概念，研究了局部模型跟踪控制系统的设计方法和复合参考模型的特定结构，证明了系统的最大匹配度。本研究突破了完全模型跟踪条件的苛刻限制，能确保被控对象的输出等关键状态稳态无误差地跟踪参考模型，复现系统的指今输入。     

人工神经网络在伺服最优鲁棒控制中的应用

提出了一种基于神经网络的伺服最优鲁棒控制，介绍了利用神经网络的学习特性对被控对象的模型不确定性进行补偿和控制。仿真结果表明，所控制器优于一般伺服控制的性能，并有较强的鲁棒性。     

基于神经网络的鲁棒自适应控制

考虑摩擦及外界干扰的情况下，针对具有不确定性参数的机器人系统，提出一种基于神经网络动态补偿的鲁棒自适应控制策略，采用神经网络在线补偿控制器以克服系统的外部扰动，未建模动力学部分等非参数不定性带来的影响，从而提高了系统的动态性能和稳态精度，并对闭环系统稳定性进行了证明，仿真结果表明，所提方法具有良好的跟踪性能和较强的鲁棒性。     

变结构神经网络自适应鲁棒控制

针对一类不确定非线性系统, 提出一种变结构神经网络自适应鲁棒控制(Variable structure neural network adaptive robust control, VSNNARC)方法. 其中变结构神经网络用于在线辨识系统未知非线性函数, 该网络利用节点激活与催眠技术进行动态调节, 减小网络规模与计算量; 自适应鲁棒控制用于网络权值学习与系统建模误差及外部扰动补偿. 采用Lyapunov稳定性分析法, 给出网络权值自适应律的形式以及鲁棒控制项的设计方法. 该方法不仅能保证系统的稳定性, 也能保证系统具有很好的瞬态性能. 将该方法应用到转台伺服系统的位置跟踪控制中, 实际运行结果表明, 该方法使系统具有很强的鲁棒性及良好的跟踪效果.     

Dynamic Parameterization for Path Following Control

Path following is a basic skill for robots in industrial use. Since the objective of path following is to make a robot follow the reference path, the velocity of the robot or the timing of the motion does not need to be strictly controlled. In this paper, the reference path is defined as a function of the parameter that has dynamics. Using this parameter, we can define the contour error, which is the error that enables us to measure the distance from the reference path to the configuration of the robot. Although the contour error is suitable for use in path following, the dynamics of the parameter contain singular points at which the dynamics cannot be defined. In order to overcome this difficulty, globally defined dynamics are introduced, and two dynamics are integrated with a switching scheme. In this paper, the asymptotic stability of the whole system is proved theoretically. Computer simulation results also show the effectiveness of the method.     

非线性系统的强实用鲁棒控制

分析输出具有给定时域性能的一类微分包含系统的控制问题。     

含时变不确定性线性系统的鲁棒跟踪控制

本文就含时变不确定性的线性系统,研究了鲁棒跟踪控制器的设计问题。文中利用Ｒｉｃ－ｃａｔｉ方程,给出了使系统输出鲁棒跟踪某一动态输入的线性控制律,对于匹配系统,跟踪误差可以任意小,从而得到实际跟踪;对于不满足匹配条件的系统,若另一些条件成立,则跟踪误差有界。     

不确定广义系统的鲁棒脉冲耗散控制

本文在状态空间下, 基于线性矩阵不等式(LMI)的方法, 研究了一类不确定广义系统在允许的不确定性下的脉冲耗散控制问题, 并且通过解线性矩阵不等式得到了此类不确定广义系统对于允许的不确定性的鲁棒脉冲耗散状态反馈控制器和输出反馈控制器, 最后通过数值算例验证了定理的可行性.     

考虑扰动及模型不确定的无人船路径跟踪控制

针对外界扰动与模型不确定因素影响下的无人船路径跟踪控制问题,引入Serret-Frenet坐标系对无人船的路径跟踪问题进行数学描述,根据给定的期望跟踪路线与当前无人船的位置信息,利用李雅普诺夫直接法设计无人船航行速度与航向角度的期望值作为路径跟踪的虚拟控制律,通过设计滑模控制器实现对虚拟控制量的误差跟踪控制,通过设计切换函数避免无人船的控制量出现饱和或抖振现象,进而降低模型不确定及干扰对路径跟踪控制的影响。仿真实验表明,设计的控制器可在外界时变扰动与模型不确定的前提下完成对给定路线的理想跟踪。