气动肌肉并联关节的位姿轨迹跟踪控制

针对多输入多输出的气动肌肉并联关节,建立包含任务空间负载动态方程、容腔压力动态方程和高速开关阀平均流量方程的多阶动态系统数学模型。为保证气动肌肉并联关节系统良好动态特性的同时具有高精度的位姿轨迹跟踪,采用基于非连续投影算法的自适应鲁棒控制策略。该策略通过自适应参数估计来消除因气动肌肉并联关节系统动态数学模型的参数未知而引起的较大参数不确定,通过鲁棒反馈来消除因气动肌肉的伸缩力模型误差、摩擦力时变和关节系统的不可知干扰等引起的严重非线性不确定,且控制器基于反推设计,对多输入多输出的多阶耦合动态系统具有很好的适用性。试验结果表明：所研究的气动肌肉并联关节阶跃响应的静态误差小于0.09°,连续轨迹跟踪的标准误差小于0.15°,且具有较强的自适应性和鲁棒性。     

Adaptive robust motion trajectory tracking control of pneumatic cylinders with LuGre model-based friction compensation

Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation（RLSE） to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This paper constructs an adaptive robust controller     

基于光反馈柔性气动手爪设计与研究

针对传统柔性气动手爪分层制作导致的易损及无闭环反馈等问题,通过低温石蜡与3D打印技术,设计并制作了重量仅为15 g的一体式、低成本柔性手爪,提高了柔性手爪的耐压性能及使用寿命。通过采用光感知反馈算法,实现了柔性手爪的闭环反馈控制,并对不同物品进行了抓取试验。结果表明:建立的光强-弯曲数学模型,不仅具有较高的位置控制精度,同时可对目标物进行准确的尺寸识别,不同尺寸下识别误差率为2%~6.7%,为柔性手爪的低成本闭环反馈控制方式提供了新思路。     

Fuzzy Torque Control of the Bionic Flexible Manipulator Actuated by Pneumatic Muscle Actuators

A bionic flexible manipulator driven by pneumatic muscle actuator(PMA) can better reflect the flexibility of the mechanism.Current research on PMA mainly focuses on the modeling and control strategy of the pneumatic manipulator system.Compared with traditional electro-hydraulic actuators,the structure of PMA is simple but possesses strong nonlinearity and flexibility,which leads to the difficulty in improving the control accuracy.In this paper,the configuration design of a bionic flexible manipulator is performed by human physiological map,the kinematic model of the mechanism is established,and the dynamics is analyzed by Lagrange method.A fuzzy torque control algorithm is designed based on the computed torque method,where the fuzzy control theory is applied.The hardware experimental system is established.Through the co-simulation contrast test on MATLAB and ADAMS,it is found that the fuzzy torque control algorithm has better tracking performance and higher tracking accuracy than the computed torque method,and is applied to the entity control test.The experimental results show that the fuzzy torque algorithm can better control the trajectory tracking movement of the bionic flexible manipulator.This research proposes a fuzzy torque control algorithm which can compensate the error more effectively,and possesses the preferred trajectory tracking performance.     

Precision control of a piezo-actuated micro telemanipulation system

Piezoelectric actuators are widely used in micro manipulation applications. However hysteresis nonlinearity limits accuracy of these actuators. This paper presents a novel approach for utilizing a piezoelectric nano-stage as slave manipulator of a teleoperation system. The Prandtl-Ishlinskii (PI) model is used to model actuator hysteresis in feedforward scheme to cancel out this nonlinearity. To deal with the influence of parametric uncertainties, unmodeled dynamics, and PI identification error a perturbation term is added to the slave model and apply a sliding mode based impedance control with perturbation estimation. The stability of the entire system is guaranteed by Llewellyn’s absolute stability criterion. Performance of the proposed controllers is verified through experiments.     

Adaptive Robust Tracking Control of Pressure Trajectory Based on Kalman Filter

When adaptive robust control(ARC) strategy based on backstepping design is applied in pneumatic servo control, accurate pressure tracking in motion is especially necessary for both force and position trajectories tracking of rodless pneumatic cylinders, and therefore an adaptive robust pressure controller is developed in this paper to improve the tracking accuracy of pressure trajectory in the chamber when the pneumatic cylinder is moving. In the proposed adaptive robust pressure controller, off-line fitting of the orifice area and on-line parameter estimation of the flow coefficient are utilized to have improved model compensation, and meanwhile robust feedback and Kalman filter are used to have strong robustness against uncertain nonlinearities, parameter fluctuations and noise. Research results demonstrate that the adaptive robust pressure controller could not only track various pressure trajectories accurately even when the pneumatic cylinder is moving, but also obtain very smooth control input, which indicates the effectiveness of adaptive model compensation. Especially when a step pressure trajectory is tracked under the condition of the movement of a rodless pneumatic cylinder, maximum tracking error of ARC is 4.46 kPa and average tracking error is 0.99 kPa, and steady-state error of ARC could achieve 0.84 kPa, which is very close to the measurement accuracy of pressure transducer.     

2-RPaRSS并联操作手运动副间隙误差分析及补偿

针对新型3T1R并联操作手2-RPaRSS存在运动副间隙引起的定位偏差,造成操作手的实际轨迹与理论轨迹不吻合的问题,提出了一种基于自适应混合粒子群优化(AHPSO）算法的轨迹修正方法。建立操作手包含的各类运动副误差模型,在模型中将间隙误差完全等效成杆长误差;根据逆运动学方程建立并联操作手2-RPaRSS的位姿误差模型,得到关于输入、输出的微分关系式,并引入驱动杆输入角补偿量;利用粒子群优化(PSO)算法对补偿量寻优,将间隙误差补偿问题转化为求适应度极小值问题;通过混合权值自适应调整、学习因子自适应调节、混沌扰动范围自适应调节策略改进了PSO算法,得到AHPSO算法。仿真结果表明AHPSO算法性能优良,具有更好的收敛性和稳定性,对并联操作手运动副间隙误差的补偿是一种有效方法,补偿后定位精度得到了明显改善。     

柔性臂杆、柔性关节空间机械臂TS模糊轨迹跟踪及双柔振动并行综合控制

针对存在参数不确定和外界干扰的柔性臂杆、柔性关节空间机械臂追踪期望运动的问题,设计了基于TS模糊模型的滑模鲁棒控制方案和双柔性振动并行控制方案。首先,设计了关节柔性补偿器以提高系统的等效关节刚度。其次,利用反馈线性化技术建立了系统追踪期望轨迹的误差动力学方程,通过对系统Lyapunov稳定性证明来选择滑模控制参数;简化并改进TS模糊推理规则,提出了模糊滑模鲁棒控制方法,可解决滑模控制的抖振问题并具有计算量少、控制力矩小的优点。再次,提出了柔性臂杆振动模态的直接反馈控制方案,解决了双柔性并行综合控制的问题。最后,运用逐步仿真的方法,对比仿真结果,证实了所设计轨迹跟踪、双柔性并行综合控制方案的有效性和稳定性。     

基于小脑模型神经网络的气动六自由度并联平台的复合控制方法研究

针对气动驱动系统的强非线性特性,本文采用基于小脑模型(CMAC)神经网络和PD的复合控制结构,用于气动六自由度并联平台各驱动关节的轨迹跟踪控制,以提高系统的跟踪精度和抗干扰能力。CMAC网络采用不均匀的输入量化函数,在零值误差附近增加量化等级,以提高系统的控制精度;而在误差较大处减小输入量化级数,从而在不增加存储空间的情况下,加大输入信号的范围。系统的仿真和实验结果都表明,与PD控制相比,该方法能有效地提高系统的轨迹跟踪精度。     

基于遗传算法的机器人末端位置补偿轨迹规划

提出了一种机器人末端位置调整补偿的轨迹规划方法,利用遗传算法求解了机器人末端位置调整引起的关节变化量。利用该方法,机器人可在不精确环境下进行校正式示教学习,通过示教还原后可实现模糊环境中的机器人末端连续轨迹扫描。利用该方法在4自由度机器人上获取了理论关节轨迹与校正轨迹,试验结果证明了该方法的可行性。     

基于PID+ESO控制器的气动机械手控制仿真分析及试验研究

针对现实中的气动机械手存在的停滞及控制精度不高等缺点,为了使气动机械手具有更好的运动轨迹跟踪特性,降低非线性,通过分析PID+ESO控制器原理,对采用PID控制和扩张状态观测器PID控制下的气动机械手进行了理论研究。通过对控制器的设计,在MATLAB/Simulink软件上分别对两种不同的控制方法进行仿真,得到各轴的目标跟踪曲线和跟踪误差曲线。将此控制器原理应用于气动试验台,得出基于扩张状态观测器PID控制下的误差较低。应用于直角坐标气动机械手响应速度快、控制精度高。     

气动三自由度并联平移型机器人的同步控制

气动三自由度并联平移机器人由固定平台、动平台、3个辅助臂和3个驱动臂组成,3个辅助臂约束机器人动平台的转动,3个气缸驱动机器人动平台沿x, y, z方向的运动。根据并联平移机器人的机械结构及运动特征,得到动平台的运动学正解和逆解。在并联平移机器人的运动控制中,不仅要减少单个驱动臂的跟踪误差,还需考虑驱动臂间的运动协调性。由于气体的可压缩性、负载的时变性和摩擦力等因素,精确的驱动臂模型难以建立,因此针对单个驱动臂设计了线性自抗扰控制器;此外,根据机器人结构特点设计基于驱动臂跟踪误差分解组合的协调控制器,解决了运动协调的问题,进一步减小了空间轨迹的跟踪误差。实验证明了该控制策略的有效性。     

气动人工肌肉并联机器人平台

提出一种基于气动人工肌肉的新型3自由度并联机器人平台,该机器人平台结构简单,具有3转动自由度。在对该新型3自由度并联机器人平台运动学和动力学特性理论分析的基础上,采用模糊变结构控制策略设计了新型3自由度并联机器人平台的两层滑模模糊变结构控制器,并建立了试验系统,开展了新型3自由度并联机器人平台的试验研究,其最大位置跟踪误差0．3 mm,当气源压力改变后,最大跟踪误差仍小于0．6 mm。试验结果表明,采用气动人工肌肉作为驱动装置设计的3自由度并联机器人平台是可行的,两层滑模模糊变结构控制策略对于该系统是适合的。     

Improvement of the control performance of pneumatic artificial muscle manipulators using an intelligent switching control method

Problems with the control, oscillatory motion and compliance of pneumatic systems have prevented their widespread use in advanced robotics. However, their compactness, power/weight ratio, ease of maintenance and inherent safety are factors that could be potentially exploited in sophisticated dexterous manipulator designs. These advantages have led to the development of novel actuators such as the McKibben Muscle, Rubber Actuator and Pneumatic Artificial Muscle Manipulators. However, some limitations still exist, such as a deterioration of the performance of transient response due to the changes in the external inertia load in the pneumatic artificial muscle manipulator. To overcome this problem, a switching algorithm of the control parameter using a learning vector quantization neural network (LVQNN) is newly proposed. This estimates the external inertia load of the pneumatic artificial muscle manipulator. The effectiveness of the proposed control algorithm is demonstrated through experiments with different external inertia loads.     

基于6维力/力矩传感器的并联机器人惯性参数辨识方法

提出了基于6维力/力矩传感器的并联机器人惯性参数辨识新方法,这种方法不需要了解关节摩擦和驱动器动力学特性的精确模型,推导了一般并联机器人的惯性参数辨识模型,分析了并联机器人的基惯性参数,提出了并联机器人惯性参数辨识轨迹的选择原则,并给出了两种新型空间并联机器人的分析实例。     

气动机械手轨迹的Terminal滑模控制方法

应用Terminal滑模控制方法对三轴直角坐标型气动机械手进行连续轨迹控制。首先建立了气动位置伺服系统的数学模型,然后运用Terminal滑模控制对机械手进行轨迹控制。仿真研究结果表明,采用高阶非线性的Terminal滑模控制方法,可以使该机械手对空间直线轨迹的跟踪误差只在未达到收敛点的时间段内较大,在到达收敛点后能完全跟踪目标轨迹。     

空间机械手模型参数在轨标定方法研究

为了在轨辨识空间机械手真实模型参数,该文分析了模型参数误差来源,提出了基于遗传算法的空间机械手模型参数在轨标定方法,设计了关节变量误差和DH参数误差两组仿真数据对该方法进行验证。仿真结果表明,该方法切实可行,能够比较准确地识别出模型参数误差,有效地更新机械手运动学模型。与传统标定方法相比,基于智能优化算法的标定方法更具有广泛性。     

基于标定和关节空间插值的工业机器人轨迹误差补偿

轨迹精度是工业机器人重要的动态性能,目前工业机器人的轨迹精度远低于定位精度,提出一种基于机器人运动学标定和关节空间插值误差补偿的方法来提高机器人轨迹精度。基于MD-H方法建立机器人的运动学模型,在此基础上运用机器人微分运动学理论建立末端位置误差模型和轨迹误差模型。为克服最小二乘法等传统方法在数据噪声较大且不符合高斯分布时收敛慢甚至发散的问题,提出一种基于扩展卡尔曼滤波算法的机器人运动学参数辨识方法,实现运动学参数辨识的快速收敛。经过分析发现机器人误差在关节空间具有连续性的特点,为此提出一种关节空间插值误差补偿方法,建立网格形式的误差补偿数据库,并利用关节空间距离权重函数和已知的网格顶点误差计算各控制点的关节转角误差。通过试验对所提出的参数辨识和关节空间误差补偿方法进行了验证,试验结果表明：经过运动学参数辨识和补偿后机器人的绝对定位精度由1.039 mm提高到0.226 mm,轨迹精度由2.532 mm提高到1.873 mm,应用关节空间插值误差补偿后机器人的轨迹精度进一步提高到1.464 mm。     

一种基于D-H参数的7自由度机械臂机构精度综合方法研究

提出了一种基于最佳精度模型的机械臂机构精度综合的方法,利用遗传算法对D-H参数公差优化分配,为机械臂的精度设计提供理论依据。以一种基于双电机伺服驱动关节的7自由度协作机械臂为研究对象,机械臂的几何定位精度的设计目标为1.4 mm,建立该型机械臂末端执行器的几何定位误差模型;对参数误差进行敏感性分析,找出对机械臂末端执行器几何定位误差影响相对较大的参数误差;根据最佳精度数学模型,利用遗传算法对D-H参数公差优化分配;经过对误差仿真计算分析,机械臂的最大几何定位误差为1.226 7 mm,均值为0.485 9 mm,方差为0.216 5 mm,满足设计要求。为该机械臂的制造装配提供了理论参考依据。与基于最小成本模型的精度综合法相比,提出的精度综合方法不需要统计加工制造成本信息,能够确保机械臂的设计精度满足设计要求,可用于单个或者小批量生产制造机械臂的精度设计。     

Observer-based sliding mode control with adaptive perturbation estimation for micropositioning actuators

Control of piezoelectric actuators is under the effects of hysteresis that could affect actuators micropositioning accuracy. In this paper a modified Prandtl-Ishlinskii (PI) operator and its inverse is utilized for both identification and real time compensation of the hysteresis effect. As a result, the actuator dynamic model would be transformed to the second order linear dynamic model. Considering the parametric uncertainties, PI estimation error and probably unmodeled dynamics, a variable structure controller coupled with adaptive perturbation estimation is proposed for trajectory tracking of the piezoelectric position. Considering the very noisy output of the actuator, a high-gain observer would estimate full states from the only measurable position trajectory. The stability of the controller in the presence of the estimated state is demonstrated with the Lyapunov criterion. Comparing to the widely used proportional-integral controller, the experimental results depicts that the proposed approach is greatly achieved in precisely tracking of multiple frequency trajectories.