非完整轮试移动机器人的轨迹跟踪滑模控制

由于轮式移动机器人的非完整性质和运动受限性质,它的轨迹跟踪已经成为一类具有挑战性的控制问题.针对一个可以在医院环境中执行护理任务的室内移动机器人-护士助手机器人,提出一种轮式移动机器人的轨迹跟踪滑模控制方法.由移动机器人在极坐标系中的运动学方程出发设计一个滑模控制器,进而提出了一种新的滑模控制方法,解决了在极坐标系中关于运动学的跟踪问题.分析了此方法的稳定性和执行性能,并且通过仿真证明这个控制方法的实际应用的有效性.     

轮式移动机器人固定时间轨迹跟踪控制

针对存在外部干扰的轮式移动机器人轨迹跟踪控制问题,提出一种固定时间轨迹跟踪控制方案.首先,对于轮式移动机器人的运动学误差模型,基于一种新颖的积分滑模面设计固定时间运动学速度控制器,使跟踪误差在固定时间收敛到原点所在的邻域内;其次,对于轮式移动机器人的动力学模型,设计固定时间干扰观测器对外部干扰信息进行估计,提出一种固定时间轨迹跟踪控制器,以确保动力学系统的固定时间稳定性,实现轮式移动机器人的高精度轨迹跟踪控制;最后,通过仿真结果验证所设计的轨迹跟踪控制方案的有效性.     

滑动与打滑条件下的轮式移动机器人自抗扰跟踪控制

针对具有未知的滑动与打滑的轮式移动机器人(WMR),提出了一种基于自抗扰思想的跟踪控制策略.首先建立了滑动与打滑条件下的轮式移动机器人动力学模型.其次,由反步法设计运动学控制器,基于模型设计线性扩张观测器和动力学控制器,并给出了控制器稳定性分析.最后与积分滑模控制进行了仿真对比,结果表明该控制方法的误差收敛速度更快.观测器能够精确估计滑动与打滑及动力学不确定性对机器人的扰动,提高了轮式移动机器人轨迹跟踪的鲁棒性.     

采用惯性测量单元的移动机器人轨迹跟踪方法研究

对于非完整移动机器人的轨迹跟踪控制已有很多方法提出,但是这些方法或者是基于动力学模型或者是采用复杂的运动学模型,对于缺少强大计算设备且需要实时控制的工程应用是不适合的.本文针对非完整移动机器人提出了一种基于比例微分(proportional-differential,PD)控制器的实时轨迹跟踪控制方法.该方法运行在40 MHz的嵌入式控制器上的控制周期只有1～2 ms.通过将一个用于直流电机控制的非线性PID速度控制器与提出的轨迹控制器进行集成,实现了一个轮式移动机器人的运动控制.机器人轨迹跟踪实验系统中采用微机电系统(micro electro-mechanical system,MEMS)惯性测量单元检测轮式移动机器人的偏航角,实验结果验证了提出方法的有效性.     

基于Lyapunov稳定性理论的移动机器人轨迹跟踪控制

针对非完整轮式移动机器人的高度强耦合、欠驱动非线性动力学模型,设计了运动学控制器以及动力学力矩控制器,使得移动机器人轨迹能够跟踪理想轨迹。这种方法的实质是首先设计虚拟速度控制器,输出速度的期望值,然后设计基于模型的力矩控制器。最后通过simulink软件对所设计的系统进行仿真,结果表明对于非完整机器人的轨迹跟踪这种控制方法效果较好。     

非完整移动机器人轨迹跟踪自适应控制器设计

针对轮式移动机器人的非完整运动学模型,将自适应反演控制技术和李亚普诺夫稳定性理论应用于机器人轨迹跟踪控制,设计了具有全局渐近稳定性的自适应轨迹跟踪控制器,并在Matlab环境下实现了移动机器人对直线和椭圆2种轨迹追踪的仿真实验.实验表明:该控制方法在轨迹跟踪控制中有较好的航向跟踪效果,对机器人非完整系统模型的非线性特性...     

基于自适应反步法的轮式移动机器人跟踪控制

轮式移动机器人是一种典型的非完整约束系统.基于反步法提出一种自适应扩展控制器,对含有未知参数的非完整轮式移动机器人动力学系统进行轨迹跟踪控制并且Lyapunov稳定性理论保证跟踪误差渐近收敛到零.为了克服速度跳变产生滑动,加入了神经动力学模型对控制器进行改进.以两驱动轮移动机器人为例,利用运动学自适应控制器设计出转矩控制器,有效解决了不确定非完整轮式移动机器人动力学系统的轨迹跟踪问题.仿真结果证明该方法的正确性和有效性.     

基于惯性测量单元的轮式机器人轨迹跟踪仿真

针对轮式机器人轨迹跟踪质量下降问题,提出基于惯性测量单元(IMU)的轮式移动机器人轨迹跟踪控制方法.通过两个惯性测量单元(IMU)来建立轮式机器人的速度、角速度计算模型,针对轮式移动机器人执行中的差动命令对轮式机器人实施闭环控制;设计轮式机器人工作轨迹参考量,结合动力学模型提出轮式机器人轨迹跟踪控制器,使轮式机器人可以在指定的轨迹上进行跟踪.实验结果表明,提出的方法能够使轮式移动机器人的轨迹跟踪误差更小,跟踪结果更精准.     

基于视觉图像的全向移动机器人轨迹跟踪控制研究

机器人轨迹节点跟踪比较难,导致机器人实际轨迹偏离期望轨迹,所以设计基于视觉图像的全向移动机器人轨迹跟踪控制方法。以滑模变结构控制闭环为基础,求解运动学模型、动力学模型表达式,实现对机器人移动轨迹数学模型的构建。按照视觉图像划分标准,完成对全向移动机器人运动图像的分割,通过分离目标节点的方式提取运动学特征参量,完成机器人轨迹节点跟踪处理。设置前馈控制器与扰动观测器,根据运动学不等式条件计算误差向量指标的取值范围,根据该值对主机元件的控制作用能力进行调节,实现全向移动机器人轨迹跟踪控制。对比实验结果表明,所设计的方法应用后,全向移动机器人角速度曲线、线速度曲线与期望运动轨迹曲线之间的贴合程度均超过90%,满足全向移动机器人轨迹跟踪控制要求。     

基于预测控制的非连续路段下移动机器人的轨迹跟踪

针对非连续路段下的轨迹跟踪问题,设计了基于观测型的预测控制器。首先建立了移动机器人的运动学模型,根据机器人的运动学模型得出了其位姿误差微分方程;然后在轨迹跟踪问题的基础上,设计了系统的观测模型,通过将预测控制器与系统的观测模型结合,设计了观测型预测控制器;最后再MATLAB环境下,利用本文所设计的控制器对移动机器人在非连续路段下的轨迹跟踪问题进行仿真,并将仿真结果与PID控制器控制的仿真结果进行对比,由仿真结果可以看出,本文所设计的控制器具有很好的鲁棒性、快速性及稳定性,可适用于移动机器人的轨迹跟踪的研究。     

Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots

In this work a neural indirect sliding mode control method for mobile robots is proposed. Due to the nonholonomic property and restricted mobility, the trajectory tracking of this system has been one of the research topics for the last ten years. The proposed control structure combines a feedback linearization model, based on a kinematics nominal model, and a practical design that combines an indirect neural adaptation technique with sliding mode control to compensate the dynamics of the robot. Using an online adaptation scheme, a neural sliding mode controller is used to approximate the equivalent control in the neighbourhood of the sliding manifold. A sliding control is appended to ensure that the neural sliding mode control can achieve a stable closed-loop system for the trajectory-tracking control of a mobile robot with unknown nonlinear dynamics. The proposed design simultaneously guarantees the stability of the adaptation of the neural nets and obtains suitable equivalent control when the parameters of the robot model are unknown in advance. The robust adaptive scheme is applied to a mobile robot and shown to be able to guarantee that the output tracking error will converge to zero.     

带有未知参数和有界干扰的移动机器人轨迹跟踪控

针对模型参数未知和存在有界干扰的非完整移动机器人的轨迹跟踪控制问题,本文提出了一种鲁棒自适应轨迹跟踪控制器方法.非完整移动机器人的控制难点在于它的运动学系统是欠驱动的.针对这一难点,本文利用横截函数的思想,引入新的辅助控制器,使得非完整移动机器人系统不再是一个欠驱动系统,缩减了控制器设计的难度,进而利用非线性自适应算法和参数映射方法构造李雅谱诺夫函数.通过李雅普诺夫方法设计控制器和参数自适应器,从而使得非完整移动机器人的跟随误差任意小,即可以任意小的误差来跟随任意给定的参考轨迹.仿真结果证明了方法的有效性.     

Sliding mode control for trajectory tracking of mobile robot in the RFID sensor space

This paper presents a sliding mode control method for wheeled mobile robots. Because of the nonlinear and nonholonomic properties, it is difficult to establish an appropriate model of the mobile robot system for trajectory tracking. A robust control law which is called sliding mode control is proposed for asymptotically stabilizing the mobile robot to a desired trajectory. The posture of the mobile robot (including the position and heading direction) is presented and the kinematics equations are established in the two-dimensional coordinates. According to the kinematics equations, the controller is designed to find an acceptable control law so that the tracking error will approximate 0 as the time approaches infinity with an initial error. The RFID sensor space is used to estimate the real posture of the mobile robot. Simulation and experiment demonstrate the efficacy of the proposed system for robust tracking of mobile robots. Recommended by Sooyong Lee under the direction of Editor Jae-Bok Song. This work was supported by the Korea Science and Engineering (KOSEF) grant funded by the Korea government (MOST) (No. R01-2007-000-10171-0). Jun Ho Lee received the M.S degree in Mechanical Engineering from Pusan National University. His research interests include factory automation and sliding mode control. Cong Lin received the B.S. degree in Electrical Engineering from Jilin University and the M.S degree in Electrical Engineering from Pusan National University. His research interests include neural network and sliding mode control. Hoon Lim is currently a M.S student in Electrical Engineering of Pusan National University. His research interests include mobile manipulator and sliding mode control. Jang Myung Lee received the B.S. and M.S degrees in Electronics Engineering from Seoul National University, Korea. He received the Ph.D. degree in Computer from the University of Southern California, Los Angeles. Now, he is a Professor in Pusan National University. His research interests include integrated manufacturing systems and intelligent control.     

一种新型的移动机器人轨迹跟踪控制方法

主要是对非完整约束下移动机器人的轨迹跟踪控制进行了研究,提出了一种新型的基于移动机器人运动模型、具有全局渐近稳定性的跟踪控制方法。这种非线性控制方法主要分为前馈和反馈两个部分：前馈部分是一种滑模控制器,它是基于反演设计的思想设计了切换函数,采用指数趋近律,减少了滑模变结构控制的抖动,并使用Lyapunov第一法对控制系统进行了稳定性分析,证明了滑模跟踪控制器是稳定的;反馈部分是基于Lyapunov函数的方法设计的反馈控制器。通过前馈部分和反馈部分的相互作用,提高了移动机器人轨迹跟踪控制的精度。实验结果表明与一般的跟踪控制方法相比,控制效果明显改善,跟踪误差能在较短时间内收敛,具有很好的抗干扰性能。     

移动机器人轨迹跟踪快速终端滑模自抗扰控制

针对移动机器人动力学模型难以精确建立、运动过程中各种干扰对高精度轨迹跟踪造成偏航等问题,构造出一种快速终端滑模自抗扰控制器,实现了高速高精度轨迹跟踪控制目标.首先建立非完整移动机器人的干扰控制模型;然后运用扩张状态观测器实时监测系统未建模动态与各种干扰;同时将扩张状态量和系统反馈量作为快速终端滑模算法的系统变量;最后设...     

Robust Adaptive Terminal Sliding Mode Control of an Omnidirectional Mobile Robot for Aircraft Skin Inspection

In this paper, an adaptive terminal sliding mode control scheme for an omnidirectional mobile robot is proposed as a robust solution to the trajectory tracking control problem. The omnidirectional mobile robot has a double-frame structure, which adsorbes on the aircraft surface by suction cups. The major difficulties lie in the existence of nonholonomic constraints, system uncertainty and external disturbance. To overcome these difficulties, the kinematic model is established, the dynamic model is derived by using Lagrange method. Then, a robust adaptive terminal sliding mode (RATSM) control scheme is proposed to solve the problem of state stabilization and trajectory tracking. In order to enhance the robustness of the system, an adaptive online estimation law is designed to overcome the total uncertainty. Subsequently, the asymptotic stability of the system without total uncertainty is proved with basis on Lyapunov theory, and the system considering total uncertainty can converge to the domain containing the origin. Simulation results are given to show the verification and validation of the proposed control scheme.

     

Adaptive sliding mode dynamic controller with integrator in the loop for nonholonomic wheeled mobile robot trajectory tracking

In this paper, novel adaptive sliding mode dynamic controller with integrator in the loop is proposed for nonholonomic wheeled mobile robot (WMR). The modified kinematics controller is used to generate kinematics velocities of WMR which are subsequently used as the input to adaptive dynamic controller. Actuator dynamics are also derived to generate actuator voltage of WMR through torque and velocity vectors. Stability of both kinematics and dynamic controller is presented using Lyapunov stability analysis. The proposed scheme is verified and validated using computer simulations for tracking the desired trajectory of WMR. The performance of proposed scheme is compared with standard backstepping kinematics controller and classical sliding mode control. In addition, the performance is further compared with standard backstepping kinematics controller with adaptive sliding mode controller without integrator. It is shown that the proposed scheme exhibits zero steady state error, fast error convergence and robustness in the presence of continuous disturbances and uncertainties.     

时滞的非完整动力学系统滑模抗干扰跟踪控制

针对具有外部扰动和时滞的非完整轮式移动机器人系统,本文阐述了一种基于非线性扰动观测器的时滞滑模控制方法.首先,利用扰动观测器估计系统的外部扰动;然后,用极坐标转化移动机器人的姿态,并用计算转矩法对机器人的动力学方程进行反馈线性化.设计带时滞控制的滑模,目的是使移动机器人渐近稳定在期望轨迹上,并有效地减小控制增益的过高估计.最后,利用李雅普诺夫函数建立闭环系统的稳定性.仿真结果表明,该方案具有良好的跟踪精度和鲁棒性.