新一类的机器人鲁棒跟踪控制策略

本文提出了一类基于计算力矩结构的变增益鲁棒控制策略，用于参数不确定性机器人的轨迹跟踪．其特点是利用了机器人动力学的一种特殊的参数变量分离方法，只需知道一个集中的系统不确定性参数，能够有效的消除参数误差带来的不确定性影响，最后保证系统达到３种不同的稳定性结果．另外，在该参数未知时，我们还设计了一个简单的在线辨识器，可保证系统全局的收敛．理论和仿真，均证明了其可靠性和有效性．     

指数稳定的机器人鲁棒跟踪控制

本文提出了一种用于控制具有参数不确性机器人轨迹踊跃的鲁棒控制策略，该控制器的设计根据Ｌｙａｐｕｎｏｖ理论，由一个基于Ｓｌｏｔｉｎｅ方法的标称控制器和一个非线性连续反馈补偿器组成。     

一类非线性不确定系统的鲁棒跟踪

讨论一类含有时变不确定性的非线性不确定系统的鲁棒跟踪问题，其中的未知参数变量以非线性形式出现。通过构造适当的Ｌｙａｐｕｎｏｖ函数，给出了该类系统的鲁棒跟踪控制器的设计。     

动基座机器人的末端受限鲁棒跟踪控制

结合具有扰动基座末端受限机器人的动力学特性,提出了虚构线性不确定系统的匹配模型概念.通过引入线性不确定系统的鲁棒跟踪控制器设计方法,发展了一种新的受约束机器人的力鲁棒跟踪控制方法.文中给出了动基座PUMA562机器人的实验结果.     

一种不确定系统的鲁棒稳定控制

本文讨论了同时具有结构性和非结构不确定性的系统的鲁棒稳定控制问题。首先考虑输入和输出阵同时存在参数摄动系统的Ｈ∞设计方法给出了鲁棒稳定控制问题的一个解。     

鲁棒渐近跟踪控制器设计的新方法

对于线性不确定系统,本文基于Riccati方程的正定解提出一种设计鲁棒渐近跟踪控制器的新方法.所设计的控制器,对于所有允许的系统参数变化,均使系统输出渐近跟踪某一参考输入.这种方法的特点是设计简单、实现方便.     

不依赖模型的机器人鲁棒自适应跟踪控制

提出了一种新颖的鲁棒自适应控制策略，用于不确定性机器人的轨迹跟踪。它不需要任何模型知识，唯一需了解的是系统的阶数和输出的位置及速度状态。理论和仿真均证明，系统的不确定性诸如摩擦力、外部扰动及未建模动力学带来的不确定性影响，均可被设计的控制律补偿，最后可保证全局指数收敛或全局一致最后有界的结果。另外，本文还给出了跟踪误差的暂态测量。     

鲁棒输出反馈控制器设计

研究了满足匹配条件的 不 确定线性系统鲁棒输出反馈控制器的设计问题，。首先推导了受约束Ｌｙａｐｕｎｏｖ问题的两个构造性结论，基于此，给出输出反馈控制器的设计。最后的算例表明了该方法的有效性。     

线性时滞不确定系统的鲁棒稳定控制

对于线性时滞不确定系统，设计了一个新的鲁棒稳定控制器，文中就匹配与不匹配类不确定系统进行了研究。与现有一些方法相比，按本文方法设计的系统不但器增益较小，实现方便，而且可以容许较大的系统不确定性。     

一类互联机器人系统的鲁棒分散跟踪控制

研究互联机器人系统在受到模型不确定性和外部干扰情况下的鲁棒轨迹跟踪问题.针对系统中存在的不确定动力学问题,在不确定项的连续界函数已知的情况下,基于Lyapunov设计方法提出一种鲁棒分散控制器的设计方法,实现互联机器人系统位置和速度的渐近跟踪.仿真算例表明了该方法的有效性.     

A robust trajectory tracking control of a polishing robot system based on CAM data

Polishing a die that has free-form surfaces is a time-consuming and tedious job, and requires a considerable amount of high-precision skill. In order to reduce the polishing time and cope with the shortage of skilled workers, a user-friendly automatic polishing system was developed in this research. The polishing system is composed of two subsystems, a three-axis machining center and a two-axis polishing robot. The developed polishing system with five degrees of freedom is able to keep the polishing tool normal to the die surface during operation. A sliding mode control algorithm with velocity compensation is proposed to reduce tracking errors. Trajectory tracking experiments showed that the effect of reducing the tracking error by the proposed sliding mode control is superior to that by the proportional derivative control. The polishing data is generated from computer-aided design (CAD) data or from teaching data by PolyCAM, a computer-aided manufacturing (CAM) system consisting of 4 modules: a geometric modeller, a CAD data exchange module, a polishing data generation module, and a graphic simulator. To evaluate the performance of the polishing robot system, some polishing experiments on a shadow-mask die were performed.     

基于神经网络的自由漂浮空间机器人关节空间鲁棒跟踪控制

针对存在不确定性以及干扰的自由漂浮空间机器人关节空间轨迹跟踪问题,提出了一种基于鲁棒控制思想的神经网络鲁棒控制方法.对于控制器中由系统惯性参数不确定性引起的非线性不确定项,利用径向基函数(RBF)神经网络进行逼近,并且利用鲁棒控制器使系统镇定并保证从干扰到跟踪误差的增益小于或等于给定的指标.最后,对本文提出的控制方案进...     

Sliding mode control for robust and smooth reference tracking in robot visual servoing

An approach based on sliding mode is proposed in this work for reference tracking in robot visual servoing. In particular, 2 sliding mode controls are obtained depending on whether joint accelerations or joint jerks are considered as the discontinuous control action. Both sliding mode controls are extensively compared in a 3D‐simulated environment with their equivalent well‐known continuous controls, which can be found in the literature, to highlight their similarities and differences. The main advantages of the proposed method are smoothness, robustness, and low computational cost. The applicability and robustness of the proposed approach are substantiated by experimental results using a conventional 6R industrial manipulator (KUKA KR 6 R900 sixx [AGILUS]) for positioning and tracking tasks.     

A robust control scheme for asymptotic tracking of robot motion

In this paper, a controller structure is developed to provide for asymptotic tracking of robot motion. The design tool is the theory of hyperstability and the analysis has led to a simple and an easy-to-implement robust version of the inverse dynamics. Simulation studies are worked out to demonstrate the controller performance. A comparison with other methods is done to show the merits of the developed scheme vs. other recently developed schemes. The implementation and computational requirements of the control schemes are determined and shown to be within the capabilities of new control hardware.This work was supported by the Kuwait University Research Administration under Grant No. EE063.     

A robust adaptive control of a parallel robot

The work presented in this article deals with the robust adaptive control tracking of a 6 degree of freedom parallel robot, called C5 parallel robot. The proposed approach is based on the coupling of sliding modes and multi-layers perceptron neural networks (MLP-NNs). It does not require the inverse dynamic model for deriving the control law. The MLP-NN is added in the control scheme to estimate the gravitational and frictional forces along with the non-modelled dynamic effects. The nonlinearity problem, present in neural networks, is resolved using Taylor series expansion. The proposed approach allows to adjust the parameters of neural network and sliding mode control terms by taking into account a reference model and the closed-loop stability in the Lyapunov sense. We implemented our approach on the C5 parallel robot of LISSI laboratory and performed experiments to observe its effectiveness and the robust behaviour of the controller against external disturbances.     

Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.     

四轮移动机器人智能预瞄轨迹跟踪控制

针对后轮驱动四轮移动机器人存在非完整约束、模型复杂等特点,提出一种基于多预瞄点的轨迹跟踪混合控制算法。该算法设计从仿人驾车的角度出发,根据不同路况通过模糊控制在线调节机器人的速度、预瞄点个数和预瞄距离。采用免疫控制方法在线整定PID控制器的参数。从控制稳定性角度出发提出轨迹偏离度评价指标。仿真结果表明该控制器的有效性。     

参数不确定机器人分散鲁棒跟踪控制

提出了一种新的参数不确定机器人分散控制器设计方法．首先将关节子系统的动力学模型分解为人工标称模型和非线性时变不确定模型两部分；然后分别设计相应的标称控制器和鲁棒补偿器．标称控制器使得标称闭环系统具有理想的跟踪性能；鲁棒补偿器可以抑制参数不确定和关节间非线性耦合等因素的影响，实现鲁棒跟踪．所设计的控制器只需要局部关节的位置反馈，具有易于实现和可在线调整的优点．仿真结果说明了该方法的有效性．     

一类非线性系统的误差轨迹跟踪鲁棒学习控制算法

针对一类含非参数不确定性的非线性系统,提出一种鲁棒迭代学习控制算法,该算法放宽了常规迭代学习控制方法的初始定位条件,迭代初值可任意取值.基于类Lyapunov方法设计误差轨迹跟踪控制器,通过鲁棒限幅学习机制对不确定性进行估计和补偿,能够在整个作业区间上实现误差对给定期望误差轨迹的精确跟踪,期望误差轨迹根据迭代起始时刻的误差值设置.利用期望误差轨迹的衰减性状,可使系统误差在预设的时间点后收敛于原点的邻域内,邻域半径的大小可根据需要任意设置.理论分析和仿真结果表明了控制方法的有效性.