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Javier Moreno-Valenzuela Víctor Santibáñez Ricardo Campa 《Journal of Intelligent and Robotic Systems》2008,51(1):65-88
The trajectory tracking of robot manipulators is addressed in this paper. Two important practical situations are considered:
the fact that robot actuators have limited power, and that only position measurements are carried out. Let us notice that
a few solutions for the torque-bounded OFT (output feedback tracking) control has been proposed. In this paper we contribute
to this subject by presenting a class of OFT controllers for torque-constrained robots. The theory of singularly perturbed
systems is crucial in the analysis of the closed-loop system trajectories. As a second contribution of this paper, we present
a detailed experimental study of six control schemes, which were tested in a two degrees-of-freedom direct-drive robot, confirming
the advantages of the proposed methodology. 相似文献
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Javier Moreno-Valenzuela Ricardo Campa Víctor Santibáñez 《International journal of systems science》2014,45(3):254-270
This article addresses the control of robotic manipulators under the assumption that the desired motion in the operational space is encoded through a velocity field. In other words, a vectorial function assigns a velocity vector to each point in the robot workspace. Thus, the control objective is to design a control input such that the actual operational space velocity of the robot end-effector asymptotically tracks the desired velocity from the velocity field. This control formulation is known in the literature as velocity field control. A new velocity field controller together with a rigorous stability analysis is introduced in this article. The controller is developed for a class of electrically-driven manipulators. In this class of manipulators, the passivity property from the servo-amplifier voltage input to the joint velocity is not satisfied. However, global exponential stability of the state space origin of the closed-loop system is proven. Furthermore, the closed-loop system is proven to be and output strictly passive map from an auxiliary input to a filtered error signal. To confirm the theoretical conclusions, a detailed experimental study in a two degrees-of-freedom direct-drive manipulator is provided. Particularly, experiments consist of comparing the performance of a simple PI controller and a high-gain PI controller with respect to the new control scheme. 相似文献
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加速度传感器装在机械手手部,各关节的加速度由加速度分解算法得到.然后,提出了一种学习控制法,这种控制法利用加速度误差校正驱动器运动.并提出了一种基于几何级数的极限条件估计学习控制过程收敛条件的理论方法.本文所提出的学习控制理论的有效性通过 PUMA-562 机器人的计算机仿真实验得到了证实. 相似文献
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Jesús Sandoval;Luis Cervantes-Pérez;Víctor Santibáñez;Javier Moreno-Valenzuela;Rafael Kelly; 《国际强度与非线性控制杂志
》2024,34(2):1032-1053
》2024,34(2):1032-1053
This paper presents a controller for joint position tracking of torque-driven robot manipulators affected by torque disturbances. In particular, the proposed approach allows concluding global exponential stability (GES) of the state-space origin of the closed-loop system when constant disturbances affect the robot dynamics. Besides, when time-varying disturbances are presented, the trajectories of the closed-loop system are proven to be bounded as result of the input-to-state stability. The main contribution is the design of the control law and a nonlinear observer based on an alternative energy shaping approach. The nonlinear observer is designed to compute and compensate for unknown disturbances, whether they are constant or time-varying. Furthermore, a detailed stability analysis of the closed-loop system based on Lyapunov theory and input-to-state stability is presented. As far as the authors know, this is the first energy-shaping controller for trajectory tracking control of robot manipulators affected by constant disturbances that achieves global exponential stability. Real-time experiments on a manipulator arm of two degrees-of-freedom illustrate the performance of the proposed controller. 相似文献
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针对一类迭代学习控制(ILC)系统的不确定项,根据时域中扩张状态观测器的思想,提出迭代域中线性迭代扩张状态观测器(LIESO),该线性迭代扩张状态观测器可以利用迭代过程的跟踪误差给出迭代学习控制系统的不确定项的显式估计。给出了基于该估计的迭代学习控制算法,并应用类Lyapunov方法证明其收敛性。仿真结果表明,所提出的迭代学习控制算法是有效的,应用迭代扩张状态观测器可以大幅度提高迭代学习效率。 相似文献
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鳗鱼机器人的动力学模型非线性强、高度欠驱动,导致多关节鳗鱼机器人的切向速度跟踪控制极具挑战．本文采用P型迭代学习控制与步态生成器相结合的方法对多关节鳗鱼机器人的切向速度进行跟踪控制．首先,采用解析牛顿-欧拉法建立非惯性系下的鳗鱼机器人动力学模型,直接获得切向速度子动力学模型;然后,利用带饱和函数的P型迭代学习控制器控制步态参数,并且利用复合能量函数和切向速度子动力学模型分析该控制器的收敛性,得到切向速度跟踪误差的收敛条件;最后,提出鳗鱼机器人的运动控制框架,并对多模块的鳗鱼机器人进行仿真和实验．实验结果表明,实际的切向速度随着迭代次数的增加而逐渐跟踪上了期望的切向速度,故而验证了鳗鱼机器人切向速度跟踪控制器的有效性． 相似文献
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为解决机器人动力学模型未知问题并提升系统鲁棒性,本文基于扰动观测器,考虑动力学模型未知的情况,设计了一种自适应神经网络（Neural network,NN）跟踪控制器.首先分析了机器人运动学和动力学模型,针对模型已知的情况,提出了刚体机械臂通用模型跟踪控制策略;在考虑动力学模型未知的情况下,利用径向基函数（Radial basis function,RBF）神经网络设计基于全状态反馈的自适应神经网络跟踪控制器,并通过设计扰动观测器补偿系统中的未知扰动.利用李雅普诺夫理论证明所提出的控制策略可以使闭环系统误差信号半全局一致有界（Semi-globally uniformly bounded,SGUB）,并通过选择合适的增益参数可以将跟踪误差收敛到零域.仿真结果证明所提出算法的有效性并且所提出的控制器在Baxter机器人平台上得到了实验验证. 相似文献
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This paper addresses the output feedback tracking control of a class of multiple‐input and multiple‐output nonlinear systems subject to time‐varying input delay and additive bounded disturbances. Based on the backstepping design approach, an output feedback robust controller is proposed by integrating an extended state observer and a novel robust controller, which uses a desired trajectory‐based feedforward term to achieve an improved model compensation and a robust delay compensation feedback term based on the finite integral of the past control values to compensate for the time‐varying input delay. The extended state observer can simultaneously estimate the unmeasurable system states and the additive disturbances only with the output measurement and delayed control input. The proposed controller theoretically guarantees prescribed transient performance and steady‐state tracking accuracy in spite of the presence of time‐varying input delay and additive bounded disturbances based on Lyapunov stability analysis by using a Lyapunov‐Krasovskii functional. A specific study on a 2‐link robot manipulator is performed; based on the system model and the proposed design procedure, a suitable controller is developed, and comparative simulation results are obtained to demonstrate the effectiveness of the developed control scheme. 相似文献
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为提高移动机器人对特定轨迹的重复跟踪能力,提出了采用开闭环PD型迭代学习控制算法对移动机器人进行轨迹跟踪控制的方法。建立了包含外界干扰的非完整约束条件下的轮式移动机器人运动学模型,给出了系统的控制算法和控制结构。仿真结果表明,采用开闭环PD型迭代学习控制算法对轨迹跟踪是可行有效的,收敛速度优于其他迭代学习算法。 相似文献
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利用Lyapunov方法, 提出了一种不确定性机器人系统的自适应鲁棒迭代学习控制策略, 整个系统在迭代域里是全局渐近稳定的. 所考虑的机器人系统同时包含了结构和非结构不确定性. 在设计时, 系统的不确定性被分解成可重复性和非重复性两部分, 并考虑了系统的标称模型. 在所提出的控制策略中, 自适应策略用来估算做法确定性的界, 界的修正与迭代学习控制量一样的迭代域得以实现的. 计算机仿真表明本文提出的控制策略是有效的. 相似文献
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Krzysztof Tchoń 《International journal of control》2013,86(11):2253-2260
The method of iterative learning control, to a large extent, has been inspired by robotics research, focused on the control of stationary manipulators. In this article we deal with the inverse kinematics problem for mobile manipulators, and show that a very basic singularity robust Jacobian inverse can be derived in a natural way within the framework of iterative learning control. To achieve this objective we have exploited the endogenous configuration space approach. The introduced Jacobian inverse defines the singularity robust Jacobian inverse kinematics algorithm for mobile manipulators. A Kantorovich-type estimate of the region of guaranteed convergence of the algorithm is derived. For two example kinematics, this estimate has been computed efficiently. 相似文献
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针对参数不确定及存在外部扰动的情况下,载体位置不控、姿态受控的漂浮基空间机器人末端抓手轨迹跟踪控制问题,提出了一种基于扰动观测器的鲁棒控制方法.结合动量守恒定律,采用拉格朗日第二类方程建立了系统动力学方程.假设外部扰动是随时间变化的未知量,设计了扰动观测器估计由外部干扰和参数不确定构成的总扰动,并基于估计的总扰动引入扰... 相似文献
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Jinbao Zhao Ke Zhang Maxiao Hou Hao Zhang Yunfei Bai Yanzheng Huang Jianan Li 《野外机器人技术杂志》2023,40(2):147-160
The main construction method of building wall is artificial masonry, the main problem is that the process is associated with low construction efficiency and poor safety, workers are prone fall from high altitude. The research of automatic masonry robot has become an urgent need. The masonry mechanical arm system is the main executing part of the masonry robot, special attention should be paid to the robot fault. Therefore, it is necessary to establish a suitable model to detect the actuator faults of the manipulator system. In this paper, a dynamic model of manipulator fault is presented and a fault detection scheme of masonry robot manipulator arm is proposed based on the model. The model is simplified by analyzing the state parameters of each joint during robot masonry and the interval observer with more design freedom was designed based on the established mathematical model of actuator faults. In this paper, a joint method for solving S and L matrices is proposed, which avoids the limitation of the traditional method for solving L matrices by two-step. In the presence of external interference, / performance are introduced into the generation process of residual interval, and the interval observer has better disturbance robustness and fault sensitivity. Simulation experiments verify that the scheme can effectively detect the actuator fault of the manipulator, and experiments are carried out on a 6-axis manipulator. The experimental results show that when actuator faults occur at joints 2 and 3, the residual rapidly exceeds the threshold range, which proves the effectiveness of the fault detection scheme designed in this paper. 相似文献
16.
In this article, an adaptive neural controller is developed for cooperative multiple robot manipulator system carrying and manipulating a common rigid object. In coordinated manipulation of a single object using multiple robot manipulators simultaneous control of the object motion and the internal force exerted by manipulators on the object is required. Firstly, an integrated dynamic model of the manipulators and the object is derived in terms of object position and orientation as the states of the derived model. Based on this model, a controller is proposed that achieves required trajectory tracking of the object as well as tracking of the desired internal forces arising in the system. A feedforward neural network is employed to learn the unknown dynamics of robot manipulators and the object. It is shown that the neural network can cope with the unknown nonlinearities through the adaptive learning process and requires no preliminary offline learning. The adaptive learning algorithm is derived from Lyapunov stability analysis so that both error convergence and tracking stability are guaranteed in the closed loop system. Finally, simulation studies and analysis are carried out for two three-link planar manipulators moving a circular disc on specified trajectory. 相似文献
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Hejia Gao;Zele Yu;Juqi Hu;Changyin Sun; 《国际强度与非线性控制杂志
》2024,34(12):7764-7785
》2024,34(12):7764-7785
This article presents a novel adaptive composite learning (ACL) control strategy combining reinforcement learning and a disturbance observer (DOB) to address vibration issues in a flexible two-link manipulator (FTLM) system affected by unknown spatiotemporally varying disturbances. Based on the assumed mode method, the FTLM system is initially transformed into an ordinary differential equation model, while effectively capturing the elastic deformation and vibration characteristics of the flexible link. A composite learning controller, based on the actor-critic algorithm and DOB, is then developed to achieve trajectory tracking and vibration suppression in the FTLM system. The DOB in the controller compensates for unknown disturbances resulting in reduced system error. It is noting that the proposed optimal control strategy is continuously gathering system experience and evaluating the current policy's effectiveness. The stability and robustness of the closed-loop system incorporating the composite controller are analyzed using Lyapunov's direct method, and the semi-global uniform ultimate boundedness of the tracking and vibration errors are also demonstrated. To validate the effectiveness and superiority of the proposed ACL controller, comparative simulations and experiments are conducted on the Quanser experimental platform. 相似文献
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To realize high-precision attitude stabilization of a flexible spacecraft in the presence of complex disturbances and measurement noises, an iterative learning disturbance observer (ILDO) is presented in this paper. Firstly, a dynamic model of disturbance is built by augmenting the integral of the lumped disturbance as a state. Based on it, ILDO is designed by introducing iterative learning structures. Then, comparative analyses of ILDO and traditional disturbance observers are carried out in frequency domain. It demonstrates that ILDO combines the advantages of high accuracy in disturbance estimation and favorable robustness to measurement noise. After that, an ILDO based composite controller is designed to stabilize the spacecraft attitude. Finally, the effectiveness of the proposed control scheme is verified by simulations. 相似文献