空间三关节机器人模糊积分滑模控制

研究提高关节机器人轨迹跟踪控制的性能,由于关节机器人运动中产生振动,影响系统的稳定性能。为解决上述问题,提出了一种反馈线性化的自适应模糊积分滑模控制方法。在上述方法的基础上,对机器人非线性动力学模型反馈线性化。为了进一步提高滑模控制的精度,设计了一种积分滑模面的滑模控制器,可以减弱积分滑模控制的抖振。通过设计一个模糊控制器,根据积分滑模面的大小自适应地调节积分滑模控制的切换部分,达到削弱抖振的目的。利用李亚普诺夫定理证明了控制系统的稳定性。仿真结果表明,改进方法有效地提高了关节机器人跟踪控制性能。     

基于Sigmoid函数的机器人鲁棒滑模跟踪控制系统设计

为了保证机器人能够在保持稳定的情况下,按照规划轨迹执行工作任务,从硬件和软件两个方面,设计了基于Sigmoid函数的机器人鲁棒滑模跟踪控制系统。装设机器人传感器与状态观测器,改装机器人鲁棒滑模跟踪控制器,完成系统硬件设计;综合机器人结构、运动机理和动力机制3个方面,构建机器人数学模型;根据状态数据采集结果与规划轨迹之间的偏差,计算机器人跟踪控制量;依据滑模运动与切换方程,利用Sigmoid函数生成机器人鲁棒滑模控制律,将生成控制指令作用在机器人执行元件上,实现系统的鲁棒滑模跟踪控制功能;在系统测试与分析中,所设计控制系统的平均位置跟踪控制误差为0.93 mm,与设定轨迹目标基本重合,机器人姿态角跟踪控制误差为0.06 mm,具有较好的鲁棒滑模跟踪控制效果,能够有效提高机器人鲁棒滑模跟踪控制精度。     

机械臂卷积神经网络滑模轨迹跟踪控制

针对工业技术的发展对于多关节机械臂的精度与快速控制高要求,提出了一种机械臂卷积神经网络滑模轨迹跟踪控制方法。分析机械臂动力学方程,提取其中的不确定部分,针对不确定部分,构建深度卷积神经网络对其进行补偿,将补偿部分引入到滑模控制律中,通过改进后的滑模控制实现对机械臂轨迹跟踪的精确控制,并通过构建Lyapunov函数论证了系统的稳定性。仿真结果显示该方法能够满足轨迹跟踪要求,且减小了抖振现象。通过与其余三种典型控制方法的对比,测试结果表明,该方法加快了轨迹跟踪误差的收敛,且跟踪精度有了明显的提高。     

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.     

Adaptive integral backstepping sliding mode control for opto-electronic tracking system based on modified LuGre friction model

In order to improve the control accuracy and stability of opto-electronic tracking system fixed on reef or airport under friction and external disturbance conditions, adaptive integral backstepping sliding mode control approach with friction compensation is developed to achieve accurate and stable tracking for fast moving target. The nonlinear observer and slide mode controller based on modified LuGre model with friction compensation can effectively reduce the influence of nonlinear friction and disturbance of this servo system. The stability of the closed-loop system is guaranteed by Lyapunov theory. The steady-state error of the system is eliminated by integral action. The adaptive integral backstepping sliding mode controller and its performance are validated by a nonlinear modified LuGre dynamic model of the opto-electronic tracking system in simulation and practical experiments. The experiment results demonstrate that the proposed controller can effectively realise the accuracy and stability control of opto-electronic tracking system.     

动态滑模控制及其在移动机器人输出跟踪中的应用

针对轮式移动机器人的输出跟踪问题,提出一种动态滑模控制方法,首先给出机器人的动力学简化模型,然后将其分解成两个低阶子系统,并给出其输出跟踪的动态滑模控制器设计方法,仿真试验表明该方法能明显地削弱滑模控制系统的抖振。     

Robust Sliding Control of Robotic Manipulators Based on a Heuristic Modification of the Sliding Gain

A task space robust trajectory tracking control is developed for robotic manipulators. A second order linear model, which defines the desired impedance for the robot, is used to generate the reference position, velocity and acceleration trajectories under the influence of an external force. The control objective is to make the robotic manipulator’s end effector track the reference trajectories in the task space. A sliding mode based robust control is used to deal with system uncertainties and external perturbations. Thus, a sliding manifold is defined by a linear combination of the tracking errors of the system in the task space built from the difference between the real and the desired position, velocity and acceleration trajectories in comparison with previous works where the sliding manifold was defined by the desired impedance and the external force. Moreover, the ideal relay has been substituted by a relay with a dead-zone in order to fit in with the actual way in which a real computational device implements the typical sign function in sliding mode control. Furthermore, a higher level supervision algorithm is proposed in order to reduce the amplitude of the high frequency components of the output associated to an overestimation of the system uncertainty bounds. Then, the robust control law is applied to the case of a robot with parametric uncertainty and unmodeled dynamics. The closed-loop system is proved to be robustly stable with all signals bounded for all time while the control objective is fulfilled in practice. Finally, a simulation example which shows the usefulness of the proposed scheme is presented.     

Sliding mode variable structure control for visual servoing system

A visual servoing tracking controller is proposed based on the sliding mode control theory in order to achieve strong robustness against parameter variations and external disturbances. A sliding plane with time delay compensation is presented by the pre-estimate of states. To reduce the chattering of the sliding mode controller, a modified exponential reaching law and hyperbolic tangent function are applied to the design of visual controller and robot joint controller. Simulation results show that the visual servoing control scheme is robust and has good tracking performance.     

受动态约束的谐波传动式可重构模块机器人分散积分滑模控制

针对受外界动态约束的谐波传动式可重构模块机器人轨迹跟踪问题, 提出一种基于关节力矩反馈的分散积分滑模控制方法. 在无力/力矩传感器且存在耦合模型不确定性的条件下即能获得良好的控制品质. 基于谐波传动模型, 仅采用位置测量数据估计关节力矩, 并建立机器人子系统动力学模型. 基于可变增益超螺旋算法(VGSTA) 设 计分散积分滑模控制器, 补偿模型不确定性并削弱控制器抖振. 采用Lyapunov 理论对系统的渐近稳定性进行了证明. 值仿真结果验证了所设计的控制器的优越性.

     

On-line genetic algorithm-based fuzzy-neural sliding mode controller using improved adaptive bound reduced-form genetic algorithm

In this article, a novel on-line genetic algorithm-based fuzzy-neural sliding mode controller trained by an improved adaptive bound reduced-form genetic algorithm is developed to guarantee robust stability and good tracking performance for a robot manipulator with uncertainties and external disturbances. A general sliding manifold, which can be non-linear or time varying, is used to construct a sliding surface and reduce control law chattering. In this article, the sliding surface is used to derive a genetic algorithm-based fuzzy-neural sliding mode controller. To identify structured system dynamics, a B-spline membership function fuzzy-neural network, which is trained by the improved genetic algorithm, is used to approximate the regressor of the robot manipulator. The sliding mode control with a general sliding surface plays the role of a compensator when the fuzzy-neural network does not approximate the dynamics regressor of the robot manipulator well in the transient period. The adjustable parameters of the fuzzy-neural network are tuned by the improved genetic algorithm, which, with the use of the sequential-search-based crossover point method and the single gene crossover, converges quickly to near-optimal parameter values. Simulation results show that the proposed genetic algorithm-based fuzzy-neural sliding mode controller is effective and yields superior tracking performance for robot manipulators.     

PHANTOM Omni机器人的自适应模糊滑模控制

针对PHANTOM Omni机器人的位置轨迹跟踪问题,采用了一种基于模糊逻辑的自适应模糊滑模控制方案。利用滑模控制中的切换函数作为输入,根据模糊系统的逼近能力设计控制器,并基于李雅谱诺夫方法设计自适应律对控制器所需参数进行实时调节。仿真中将其与传统的滑模控制进行了比较,仿真结果表明：自适应模糊滑模控制能使PHANTOM Omni机器人更好地实现期望的位置轨迹跟踪并有效地减轻抖振现象,从而证明了该方法在PHANTOM Omni机器人上实施的可行性。     

二阶动态滑模控制在移动机械臂输出跟踪中的应用

针对移动机械臂的输出跟踪问题,结合高阶滑模控制和动态滑模控制的设计思想为其设计了一种二阶动态滑模控制器.首先给出了包括驱动电机动态特性的移动机械臂的简化动态模型,然后通过微分同胚和输入变换将其分解为四个低阶子系统,并给出了其输出跟踪的二阶动态滑模控制器的设计方法.仿真结果表明,所设计的二阶动态滑模控制器不仅能很好地跟踪给定轨迹,而且能有效地削弱滑模控制系统的抖振.     

Robust Tracking Control for Self-balancing Mobile Robots Using Disturbance Observer

In this paper, a robust tracking control scheme based on nonlinear disturbance observer is developed for the self-balancing mobile robot with external unknown disturbances. A desired velocity control law is firstly designed using the Lyapunov analysis method and the arctan function. To improve the tracking control performance, a nonlinear disturbance observer is developed to estimate the unknown disturbance of the self-balancing mobile robot. Using the output of the designed disturbance observer, the robust tracking control scheme is presented employing the sliding mode method for the selfbalancing mobile robot. Numerical simulation results further demonstrate the effectiveness of the proposed robust tracking control scheme for the self-balancing mobile robot subject to external unknown disturbances.      

机械手的模糊逆模型鲁棒控制

提出一种基于模糊聚类和滑动模控制的模糊逆模型控制方法,并将其应用于动力学方程未知的机械手轨迹控制.首先,采用C均值聚类算法构造两关节机械手的高木-关野(T-S)模糊模型,并由此构造模糊系统的逆模型.然后,在提出的模糊逆模型控制结构中,离散时间滑动模控制和时延控制(TDC)用于补偿模糊建模误差和外扰动,保证系统的全局稳定性并改进其动态和稳态性能.系统的稳定性和轨迹误差的收敛性可以通过稳定性定理来证明.最后,以两关节机械手的轨迹跟随控制为例,揭示了该设计方法的控制性能.     

Fractional-order sliding mode control for a novel magneto-electro-elastic microtube robot

In this paper, a tracking controller based on a non-integer sliding surface is proposed for a magneto-electro-elastic (MEE) fluid-conveying microtube robot. The smart/adaptive MEE material enables us to control the robot with no need for external sensors and actuators. The micro-robot lateral motion is modeled by Euler–Bernoulli beam equations. The governing equation of the robot is derived using the constitutive equations of MEE materials and Maxwell's principle followed by Hamilton's variational method. Based on the extracted dynamic model, a novel non-integer order sliding mode controller is introduced to suppress the microtube vibration and to provide robust path following for the robot tip. This control approach is compatible with the parameter-varying nature of the robot dynamics. Theoretical analyses, based on Lyapunov theory, are also conducted to verify the stability of the closed-loop system. Comparative simulations are finally performed to show the efficiency of the proposed system in comparison with the conventional micro tubes made of smart materials and with an integer order sliding mode controller (SMC). The results demonstrate that the proposed robot properly meets the performance requirements in terms of vibration suppression and trajectory tracking, even in the presence of disturbances.     

受约束空间机器人降阶自适应神经网络滑模控制

为了实现受约束空间机器人的高精度控制,提出了一种基于U-K(Udwadia-Kalaba)方程的降阶自适应神经网络滑模控制算法;基于U-K方程,同时考虑受约束空间机器人各个关节的理想约束力与非理想约束力,推导得到详细的动力学方程;考虑到非理想约束力具有不确定性且单独采用滑模控制会出现抖振现象,提出了自适应神经网络滑模控制算法,实现各关节角度、角速度以及非理想约束力的高精度跟踪;针对系统受约束模型,对动力学方程和滑模控制器进行了降阶求解,减少了变量并简化了计算过程;为了验证所提算法的正确性与合理性,以2自由度受约束空间机器人为例进行了仿真验证;仿真结果表明：受约束空间机器人的各关节角度、角速度以及非理想约束力的跟踪误差均低于10^-4量级。     

Fuzzy sliding mode control for a robot manipulator

This work presents the design of a robust control system using a sliding mode controller that incorporates a fuzzy control scheme. The presented control law superposes a sliding mode controller and a fuzzy logic controller. A fuzzy tuning scheme is employed to improve the performance of the control system. The proposed fuzzy sliding mode control (FSMC) scheme utilizes the complementary cooperation of the traditional sliding mode control (SMC) and the fuzzy logic control (FLC). In other words, the proposed control scheme has the advantages which it can guarantee the stability in the sense of Lyapunov function theory and can ameliorate the tracking errors, compared with the FLC and SMC, respectively. Simulation results for the trajectory tracking control of a two-link robot manipulator are presented to show the feasibility and robustness of the proposed control scheme. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler–Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.     

基于遥感GIS信息融合的测绘机器人滑动模跟踪控制系统

测绘机器人是实现测绘自动化的执行设备,测绘机器人的工作空间更为复杂,给机器人的跟踪控制工作带来较大挑战。为提高测绘机器人跟踪控制效果,设计了基于遥感GIS信息融合的测绘机器人滑动模跟踪控制系统。加设遥感信息采集器和GIS信息采集器,改装遥感GIS信息处理器以及滑动模跟踪控制器,完成硬件系统的优化设计。考虑信息结构以及信息之间的逻辑关系,构建系统数据库,为遥感GIS信息提供充足的存储空间。根据测绘任务生成机器人滑动模移动轨迹,作为机器人的控制目标。采集测绘机器人实时遥感与GIS信息,利用遥感GIS信息融合技术跟踪机器人实时位姿,比对位姿跟踪结果与生成的控制目标,计算滑动模跟踪控制量,完成系统的测绘机器人滑动模跟踪控制软件功能优化。系统测试结果表明:设计系统的控制误差平均值为1.9 m,抖振幅值为0.8 dB,具有较好的控制效果。     

高阶滑模控制在非完整移动机器人鲁棒输出跟踪中的应用

给出了移动机器人鲁棒输出跟踪的高阶滑模控制器, 它不仅可以削弱滑模控制系统的抖振问题, 还对系统存在的不确定性具有良好的鲁棒性. 数值仿真表明了该控制器的有效性.