A position control differential drive wheeled mobile robot

For more accurate path tracking of a four-wheeled two-degrees-of-freedom mobile robot (WMR), a position control algorithm is proposed with two separated feedback loops, a velocity feedback loop and a position feedback loop. In the most conventional position control system of a WMR, internal error is mainly considered, while external error has, as yet, hardly been treated, although it plays an important role in accurate position control. This external error is caused by unexpected environmental situations. The proposed control algorithm is designed to compensate for both internal error and external error. This algorithm makes it possible to accurately follow the designed trajectory     

中型组机器人运动控制系统的FPGA设计

以RoboCup中型组足球机器人为实验平台,提出一种基于FPGA的全方位移动足球机器人运动控制系统的实现方法。首先分析和研究三轮全方位移动机器人的运动学特性,建立其运动控制模型,然后以FPGA为主要处理器,设计了PID速度闭环控制算法,实现了对机器人的精确控制。实验发现,该设计方法具有很好的实时性,能够对全方位移动机器人进行快速、准确的控制。     

Model identification and adaptive control of lower limb exoskeleton based on neighborhood field optimization

In lower limb exoskeletons, control performance and system stability of human–robot coordinated movement are often hampered by some model parametric uncertainties. To address this problem, Neighborhood Field Optimization (NFO) is proposed to identify the unknown model parameters of an exoskeleton for the model-based controller design. The excitation trajectory is designed by the NFO algorithm with motion constraints to improve the model identification accuracy. Meanwhile, the Huber fitness function is adopted to suppress the influence of the disturbance points in sampled dataset. Then an adaptive backstepping control scheme is constructed to improve the dynamic tracking performance of human–robot training mode in the presence of the identification error. Via Lyapunov technique and backstepping iteration, all the system state errors of the exoskeleton are bound and converge to zero neighborhood based on the assumption of bounded identified parameter error. Finally, the model identification results and comparative tracking performance of the proposed scheme are verified by an experimental platform of Two-degrees of freedom (DOF) lower limb exoskeleton with human–robot cooperative motion.     

基于ADT850的移动机器人运动控制系统设计

主要介绍了一种移动机器人的运动控制系统硬、软件结构。控制系统是由工业PC,ADT850运动控制卡及相关传感器组成;操作系统采用Windows98系统,采用VisualC 6.0开发,并应用模块化及Windows线程的多任务处理机制实现控制程序设计;根据状态反馈控制理论,设计了移动机器人路径跟踪控制算法。实验论证了此控制系统及控制算法的有效性。     

移动机器人路径跟踪模糊控制系统设计及仿真

本文的主要研究内容是模糊逻辑在移动机器人已知全局路径的情况下通过对局部路径的分析进行轨迹跟踪运动中的应用。利用模糊逻辑在移动机器人运动控制中的优越性,结合驾驶员的丰富经验设计了移动机器人的模糊控制器,包括一个预瞄距离确定器和一个运动模糊控制器。设计出移动机器人运动控制进行仿真的方法及程序流程,对其进行计算机仿真验证控制...     

Orientation control of a differential mobile robot through wheel synchronization

This paper presents the orientation control of a differential mobile robot through the synchronization of the motions of two driving wheels, using an adaptive coupling control algorithm. The orientation error is usually caused by the synchronization error between two driving wheels and has the largest impact on the motion accuracy. The proposed controller incorporates the cross-coupling technology into an adaptive control architecture and guarantees asymptotic convergence to zero of the position tracking errors of two wheels as well as the synchronization error between them. Experiments demonstrate that the proposed control method exhibits better motion performance than traditional control methods especially in the orientation control.     

轮式机器人滑模轨迹跟踪控制器设计

轮式机器人是一个典型的非完整性系统。由于非线性和非完整特性,很难为移动机器人系统的轨迹跟踪建立一个合适的模型。介绍了一种轮式机器人滑模轨迹跟踪控制方法。滑模控制是一个鲁棒的控制方法,能渐近的按一条所期望的轨迹稳定移动机器人。以之为基础,描述了轮式机器人的动力学模型并在二维坐标下建立了运动学方程,根据运动学方程设计滑模控制器,该控制器使得机器人的位置误差收敛到零。     

非线性反馈线性化方法在轮式移动机器人的应用

给出一种轮式移动机器人系统的受非完整约束的动态模型。基于此模型应用了非线性反馈精确线性化方法进行了机器人路径跟踪控制系统设计。经过输入输出反馈线性化后,系统实现了解耦和线性化,然后用配置极点的方法对变换后的线性系统进行了设计。仿真结果表明,用反馈线性化设计的机器人系统具有良好的性能。实验结果证明了上述方法的有效性。     

移动机器人全局轨迹跟踪的自适应滑模控制

讨论了两驱动后轮角速度为控制输入的移动机器人轨迹跟踪问题，针对含有未知参数的非完整移动机器人运动学模型．基于反演（backstepping）控制算法的思想设计了变结构控制的切换函数，并由此构造了具有全局渐近稳定的白适应滑模轨迹跟踪控制器。该方法设计过程简单并具有直观的稳定性分析，适用于移动机器人的全局轨迹跟踪控制。仿真结果表明了该方法的有效性和正确性。     

参数不确定移动机器人全局轨迹跟踪的自适应滑模控制

通过对一类质心和几何中心不重合情况下移动机器人轨迹跟踪问题的研究,得到了两独立驱动轮角速度为控制输入的机器人运动学模型.对于车轮半径和两驱动轮之间距离参数已知的情况,基于反演控制的思想设计了变结构控制的切换函数,构造了具有全局渐近稳定的滑模轨迹跟踪控制律,并针对这两个参数未知时,通过自适应方法对其进行参数估计,给出了自适应滑模轨迹跟踪控制律的设计方法.该方法设计过程简单且具有直观的稳定性分析,适用于移动机器人的全局轨迹跟踪控制.仿真算例验证了所提控制律的有效性和正确性.     

Trajectory tracking of redundantly actuated mobile robot by MPC velocity control under steering strategy constraint

Four-wheel independent-steering redundantly-actuated omnidirectional mobile robot (FIR-OMR) has attracted wide attention for its excellent motion performance such as multi-mode steering and flexible attitude adjustment. However, for the 8-drive redundant and strong nonlinear system of FIR-OMR, the complexity and time-consuming of model solutions make it hard for the embedded system to achieve fast and efficient trajectory tracking. To copy with that, an optimal velocity model predictive control under steering strategy constraint (USSC-MPC) is presented, which is combined with pose correction by local micro error (LME-PC) for independent wheel angle feedback control. Specifically, the steering modes of FIR-OMR are divided into fixed independent wheel steering (IWS), zero-angle pure differential steering (DS), and Ackerman steering (AS), which is ultimately selected by steering fuzzy selector (SFS). Then a steer-based model prediction controller is designed to optimize the wheel velocity and the micro-error feedback wheel angle of pose correction pointing to the desired point is calculated by FIR-OMR in real-time. As a result, by controlling the wheel velocity and wheel angle, a satisfactory path tracking control effect can be obtained. In our proposed method, the USSC-MPC ensures the optimality of wheel velocity, and the LME-PC can achieve efficient trajectory tracking with a faster error convergence rate. Through simulations and experiments, complex motions such as multi-section paths and side parking can be realized, which verifies the feasibility and superiority of our method.     

Robust learning control of a high precision planar parallel manipulator

End-point positioning accuracy and fast settling time are essential in the motion system aimed at semiconductor packaging applications. In this paper, a novel robust learning control method for a direct-drive planar parallel manipulator is presented. A frequency-domain system identification approach is used to identify the high frequency dynamic of the manipulator. A robust control design method is employed to design a stable, fast tracking response feedback controller with less sensitivity to high frequency disturbance and the control parameters are determined using genetic algorithm. A Fourier-series-based iterative learning controller is designed and used on the feedforward path of the controller to further improve the settling time by reducing the dynamic tracking error of the manipulator. Experimental results demonstrate that the planar parallel manipulator has significant improvements on motion performance in terms of positioning accuracy, settling time and stability when compared with traditional XY-stages. This shows that the proposed manipulator provides a superior alternative to XY-motion stages for high precision positioning.     

两轮差速机器人运动学分析和控制研究

对两轮差速机器人的运动控制进行分析,建立了输入/输出量之间的函数隶属关系,在建立轮式机器人的运动学模型和动力学模型基础上,为实际研究提供可行性指导和理论依据。同时为博创平台的差速机器人运动控制提出新的思路,即基于模糊控制的机器人路径跟踪。将增量式PID控制算法及模糊控制策略结合起来,应用于两轮差速机器人的运动控制模型中,并运用Matlab进行仿真,得到了控制系统的响应曲线,达到了满意的效果。     

Adaptive robust control of fully-constrained cable driven parallel robots

In this paper, adaptive robust control (ARC) of fully-constrained cable driven parallel robots is studied in detail. Since kinematic and dynamic models of the robot are partly structurally unknown in practice, in this paper an adaptive robust sliding mode controller is proposed based on the adaptation of the upper bound of the uncertainties. This approach does not require pre-knowledge of the uncertainties upper bounds and linear regression form of kinematic and dynamic models. Moreover, to ensure that all cables remain in tension, proposed control algorithm benefit the internal force concept in its structure. The proposed controller not only keeps all cables under tension for the whole workspace of the robot, it is chattering-free, computationally simple and it does not require measurement of the end-effector acceleration. The stability of the closed-loop system with proposed control algorithm is analyzed through Lyapunov second method and it is shown that the tracking error will remain uniformly ultimately bounded (UUB). Finally, the effectiveness of the proposed control algorithm is examined through some experiments on a planar cable driven parallel robot and it is shown that the proposed controller is able to provide suitable tracking performance in practice.     

基于射频隐身的采样周期和辐射功率控制方法研究

为进一步提高雷达的射频隐身能力,合理分配相控阵雷达的工作参数,在目标跟踪时,对雷达的采样周期和辐射功率控制方法进行研究。首先,根据目标运动状态的不同,对雷达采样周期与辐射功率自适应设计方法进行分析,在满足系统跟踪性能要求的前提下,建立了控制参数的优化模型;然后,利用粒子群算法优化自适应采样周期和自适应辐射功率等参数,有效地降低了跟踪性能误差,提高了雷达系统的射频隐身性能。与传统的雷达采样周期和辐射功率算法进行了仿真比较,结果表明所提的算法取得了较好射频隐身效果。     

Autonomous and teleoperation control of a mobile robot

The present work proposes an autonomous tracking control system and a control structure to combine autonomous and teleoperation commands in a bicycle-type mobile robot. This compounded operation renders great flexibility to the control system of the mobile robot. For autonomous operation, a simple tracking controller that includes compensation of the robot dynamics is developed. This tracking control system is proved to be stable in the sense that it asymptotically reaches the tracking objective. Teleoperation with visual access to the robot’s workspace is integrated via a joystick with the autonomous operation of the robot. Simulations and experimental results on a prototype robot show the feasibility and performance of the proposed control system.     

考虑多变路况的机器人循迹优化教学实验

在教学中为了使学生更好的理解模糊控制理论,设计了在模糊控制下的机器人路径循迹优化实验,利用课堂教学与翻转课堂相结合的授课模式,展显智能控制的突出优势,同时也解决理论与实践相分离的问题。通过对模糊控制及传统PID控制下机器人对多复杂路径的跟踪循迹对比,加深学生对模糊控制的理解。实验证明,该控制方法不仅能降低系统的循迹误差,还可帮助学生更好的理解模糊控制理论。     

Optimal motion planning and control of a nonholonomic spherical robot using dynamic programming approach: simulation and experimental results

Optimal motion planning and control of a nonholonomic spherical mobile robot is studied. Dynamic Programming (DP) as a direct and online approach is used to navigate the robot in an environment with/without obstacles. The optimal trajectory, which corresponds to the minimum cost, is determined in the case of presence of obstacles in the environment, and the robot can move towards the target optimally, without colliding with obstacles. DP yields optimal control inputs in a closed-loop form. In fact, a traditional control system is no longer needed to track the obtained trajectory since the resulted DP table includes optimal control inputs for every state in the admissible region. The effect of different final states and alternative intervals of the allowable state and control values are also studied. Results from several simulations show that the proposed method enables the robot to find an optimal trajectory from any given state towards a predefined target. An experimental setup is designed wherein a real spherical robot is driven according to the developed algorithm. A vision system monitors the robot and outputs the location/orientation of the robot at each step via image processing. Experimental results are then compared with simulations to validate the model and evaluate the control strategy.     

Robust Smooth-Trajectory Control of Nonlinear Servo Systems Based on Neural Networks

The electromagnetic torque introduces ripples into the electromechanical motion system due to nonlinearities, such as uncertain changes of magnet field, load, and friction, which generate speed oscillations and deteriorate the tracking performance of servo system. Furthermore, the minimum time response and smooth trajectory tracking are cruces in servo control. In this paper, an available method is proposed to solve them by using neural networks (NNs) and a nonlinear smooth trajectory filter (STF) for the robust smoothing feedforward control of a class of general nonlinear systems. First, the online weight-tuning scheme based on Lyapunov function can guarantee the boundedness of tracking error by good performance of NNs modeling nonlinear functions. Second, a feedforward controller based on the output of nonlinear STF is designed to guarantee minimum time response and smooth trajectory tracking. Finally, as a example, the motion system can be equivalent to the two-order system under the linear closed-loop current control in view of the (d,q) mathematic model for PM synchronous motor, so that this robust smoothing control method using neutral networks can be applied into position servo control. Moreover, the validity and effectiveness of this control method are verified through simulations and experiments     

Intelligent optimal control of single-link flexible robot arm

This paper addresses the design and properties of an intelligent optimal control for a nonlinear flexible robot arm that is driven by a permanent-magnet synchronous servo motor. First, the dynamic model of a flexible robot arm system with a tip mass is introduced. When the tip mass of the flexible robot arm is a rigid body, not only bending vibration but also torsional vibration are occurred. In this paper, the vibration states of the nonlinear system are assumed to he unmeasurable, i.e., only the actuator position can be acquired to feed into a suitable control system for stabilizing the vibration states indirectly. Then, an intelligent optimal control system is proposed to control the motor-mechanism coupling system for periodic motion. In the intelligent optimal control system a fuzzy neural network controller is used to learn a nonlinear function in the optimal control law, and a robust controller is designed to compensate the approximation error. Moreover, a simple adaptive algorithm is proposed to adjust the uncertain bound in the robust controller avoiding the chattering phenomena. The control laws of the intelligent optimal control system are derived in the sense of optimal control technique and Lyapunov stability analysis, so that system-tracking stability can be guaranteed in the closed-loop system. In addition, numerical simulation and experimental results are given to verify the effectiveness of the proposed control scheme.