直接驱动型机械手的变结构控制

针对直接驱动型机械手的随动控制问题,提出了一种基于滑动模态扰动观测器的变结构控制器.通过观测由系统的非线性、模型的不确定性和外来干扰所造成的广义扰动,将非线性、强耦合的机械手动力学系统线性化,并解耦为多个单输入、单输出线性系统.控制器的设计不再依赖于机械手的精确模型.在二连杆机械手上做的仿真研究表明,在负载大范围变化的条件下,采用滑动模态扰动观测器的控制系统,比全状态反馈的控制系统具有更好的鲁棒性.     

Adaptive sliding mode disturbance rejection control with prescribed performance for robotic manipulators

This study proposes an adaptive sliding mode disturbance rejection control with prescribed performance for robotic manipulators. A transformation with respect to tracking error using certain performance functions is used to ensure the transient and steady-state performances of the trajectory tracking control for robotic manipulators. Using the transformed error, a nonsingular terminal sliding mode surface is proposed. A continuous terminal sliding mode control (SMC) is presented to stabilize the system. To compensate for the uncertainty and external disturbance, a novel sliding mode disturbance observer is proposed. Considering the unknown boundary of the derivative of a lumped disturbance, an adaptive law based on the idea of equivalent control is designed. Combining the adaptive law, continuous nonsingular terminal SMC, and sliding mode disturbance observer, the adaptive sliding mode disturbance rejection control with prescribed performance is developed. Simulations are carried out to demonstrate the effectiveness of the proposed approach.     

基于状态观测器的球形机器人状态反馈控制系统设计

基于能量耗散形式下的拉格朗日方程,建立了基于状态观测器的球形机器人的动力学方程,得出这是一个非线性的仿射系统。根据机器人的实际运动情况和理论仿真曲线对方程进行了线性化处理和仿射变换,在新建立的平衡点处应用线性理论进行控制系统的设计。考虑到某些状态变量的不可测量性,构建了状态观测器对系统的全维状态进行实时观测,在此基础上设计了系统的状态反馈控制器。仿真结果表明了所设计控制器的有效性。     

基于交流伺服电机驱动的并联机器人动态滑模控制

并联机器人具有刚度大、承载能力强、误差小等特点,针对以交流伺服电机驱动的并联机器人机构--GPM-200并联机构,建立了控制系统模型,并在其工作空间中进行了轨迹规划,而后设计了一种动态滑模控制算法,在Matlab/Simulink上进行了仿真实验,结果表明:该算法鲁棒性好,且系统抗干扰能力强,对系统参数变化不敏感,具有良好的跟踪性能,实现了对该并联机器人的高精度实时控制.     

On position/force tracking control problem of cooperative robot manipulators using adaptive fuzzy backstepping approach

In this paper, the position and force tracking control problem of cooperative robot manipulator system handling a common rigid object with unknown dynamical models and unknown external disturbances is investigated. The universal approximation properties of fuzzy logic systems are employed to estimate the unknown system dynamics. On the other hand, by defining new state variables based on the integral and differential of position and orientation errors of the grasped object, the error system of coordinated robot manipulators is constructed. Subsequently by defining the appropriate change of coordinates and using the backstepping design strategy, an adaptive fuzzy backstepping position tracking control scheme is proposed for multi-robot manipulator systems. By utilizing the properties of internal forces, extra terms are also added to the control signals to consider the force tracking problem. Moreover, it is shown that the proposed adaptive fuzzy backstepping position/force control approach ensures all the signals of the closed loop system uniformly ultimately bounded and tracking errors of both positions and forces can converge to small desired values by proper selection of the design parameters. Finally, the theoretic achievements are tested on the two three-link planar robot manipulators cooperatively handling a common object to illustrate the effectiveness of the proposed approach.     

Sliding mode output feedback control based on tracking error observer with disturbance estimator

For a class of systems who suffers from disturbances, an original output feedback sliding mode control method is presented based on a novel tracking error observer with disturbance estimator. The mathematical models of the systems are not required to be with high accuracy, and the disturbances can be vanishing or nonvanishing, while the bounds of disturbances are unknown. By constructing a differential sliding surface and employing reaching law approach, a sliding mode controller is obtained. On the basis of an extended disturbance estimator, a creative tracking error observer is produced. By using the observation of tracking error and the estimation of disturbance, the sliding mode controller is implementable. It is proved that the disturbance estimation error and tracking observation error are bounded, the sliding surface is reachable and the closed-loop system is robustly stable. The simulations on a servomotor positioning system and a five-degree-of-freedom active magnetic bearings system verify the effect of the proposed method.     

Sliding mode based trajectory linearization control for hypersonic reentry vehicle via extended disturbance observer

This paper proposes a novel hybrid control framework by combing observer-based sliding mode control (SMC) with trajectory linearization control (TLC) for hypersonic reentry vehicle (HRV) attitude tracking problem. First, fewer control consumption is achieved using nonlinear tracking differentiator (TD) in the attitude loop. Second, a novel SMC that employs extended disturbance observer (EDO) to counteract the effect of uncertainties using a new sliding surface which includes the estimation error is integrated to address the tracking error stabilization issues in the attitude and angular rate loop, respectively. In addition, new results associated with EDO are examined in terms of dynamic response and noise-tolerant performance, as well as estimation accuracy. The key feature of the proposed compound control approach is that chattering free tracking performance with high accuracy can be ensured for HRV in the presence of multiple uncertainties under control constraints. Based on finite time convergence stability theory, the stability of the resulting closed-loop system is well established. Also, comparisons and extensive simulation results are presented to demonstrate the effectiveness of the control strategy.     

Learning from adaptive neural network output feedback control of a unicycle-type mobile robot

This paper studies learning from adaptive neural network (NN) output feedback control of nonholonomic unicycle-type mobile robots. The major difficulties are caused by the unknown robot system dynamics and the unmeasurable states. To overcome these difficulties, a new adaptive control scheme is proposed including designing a new adaptive NN output feedback controller and two high-gain observers. It is shown that the stability of the closed-loop robot system and the convergence of tracking errors are guaranteed. The unknown robot system dynamics can be approximated by radial basis function NNs. When repeating same or similar control tasks, the learned knowledge can be recalled and reused to achieve guaranteed stability and better control performance, thereby avoiding the tremendous repeated training process of NNs.     

焊接机器人非奇异Terminal滑模控制系统研究

针对焊接机器人不确定性系统的特点,进行了非奇异Terminal滑模控制系统研究。建立了焊接机器人动态模型;确定了控制系统的硬件结构,并在此基础上探讨了系统非奇异Terminal滑模控制的基本原理。最后,结合实例对焊接机器人非奇异Terminal滑模控制系统进行了数值仿真。结果表明,该控制系统的自适应性强,精度高,误差可以快速收敛到0。     

快速终端滑模控制在并联机器人中的应用

针对二自由度冗余驱动并联机器人,提出了并联机器人的快速终端滑模控制(FTSMC)以实现其鲁棒控制,并利用Lyapunov函数证明了该控制系统的稳定性。仿真结果表明,该控制系统跟踪效果好,系统误差小,可以满足并联机器人控制的要求。与采用普通滑模控制相比,该控制系统具有状态响应速度快,系统状态在有限时间内收敛到零的特点。仿真实验证实了该控制策略的正确性和有效性。     

基于FNTFSMC的国产腹腔镜手术机器人轨迹控制

针对国产腹腔镜手术机器人轨迹跟踪控制的关键问题,在动力学模型的基础上,构建了自适应模糊滑模控制系统。该方法采用快速非奇异终端滑模面,确保系统能够在有限时间内收敛,并且避免了控制奇异的问题,同时运用模糊逻辑控制,根据系统误差的变化动态调节滑模切换项的大小,在保留滑模控制鲁棒性的基础上,减小了系统的抖振,提高了被控系统的跟踪精度和鲁棒性。仿真结果显示,所设计的方法具有收敛速度快、稳态精度高、力矩脉动小的特点,能够将位置的收敛时间从0. 6～0. 9 s减小到0. 1 s,稳态误差峰值由0. 035 rad减小到0. 01 rad。针对动物活体组织的实验结果显示,所设计的控制系统能够实现机械手术臂对医生操作信息的准确跟踪,为手术的顺利实施提供了保障。     

移动机械臂的输出跟踪控制

移动机械臂通常由移动机器人和装在移动机器人上的机械臂组成。它既具有移动机器人的可移动性又具有机械臂的操作灵活性,有极高的实际应用价值。本文针对由二轮驱动的移动平台和二连杆机械臂组成的移动机械臂的输出跟踪问题,利用滑模控制原理为其设计了动态滑模控制器。首先给出了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4个低阶子系统,并给出了其输出跟踪的动态滑模控制器的设计方法。仿真实验表明,所设计的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。     

纵向打滑状态下轮式移动机器人轨迹跟踪控制

针对轮式移动机器人纵向打滑状态下滑动参数未知的轨迹跟踪控制问题,提出了一种轨迹跟踪控制方法。建立了纵向打滑状态下移动机器人的运动学模型,用滑动 参数表示左右轮的打滑程度;设计合适的滑模观测器对未知的滑动参数进行估计,并通过低通滤波器减少抖振对估计结果产生的影响;基于Lyapunov直接法设计轨迹跟踪控制律,并提出了一种根据控制系统的极点分布确定控制参数的方法。仿真结果验证了所提方法的准确性和有效性。     

基于高性能单片机的循迹机器人控制系统设计

循迹机器人是一种实现较为容易、发展前景广阔的智能导引系统.该文基于16位的高性能单片机,设计了激光导引循迹机器人的控制系统.该系统除了实现稳定高速的循迹功能外,还具有路径规划、避障、无线控制等实用功能,具有能耗低、计算及存储功能强等特点.     

Finite-time Extended State Observer based fault tolerant output feedback control for attitude stabilization

This work addresses the challenging problem of finite-time fault tolerant attitude stabilization control for the rigid spacecraft attitude control system without the angular velocity measurements, in the presence of external disturbances and actuator failures. Consider the severe circumstances with above failures and uncertainties, a novel continuous finite-time Extended State Observer is first established to observe the attitude angular velocity and the synthetic failure simultaneously. Unlike the existing observers, the finite-time methodology and Extended State Observer are utilized, to achieve the finite-time uniformly ultimately bounded stability of the attitude angular velocity and extended state observation errors. Furthermore, a novel continuous finite-time attitude controller is developed by using the nonsingular terminal sliding mode control and super-twisting method. The main feature of this work stems from our use of multiply advanced techniques or methodologies that enables the finite-time stability of the closed-loop attitude control system and the designed control scheme is continuous with the property of chattering restraining. Finally, numerical simulation results are presented to illustrate the effectiveness and fine performances of the finite-time observer and controller for the attitude control system.     

漂浮基柔性两杆空间机械臂基于状态观测器的鲁棒控制及振动控制

讨论了漂浮基柔性空间机械臂基于状态观测器的鲁棒控制及振动最优控制问题。首先通过合理选择联体坐标系,实现两柔性杆弹性变形之间的解耦;根据拉格朗日方程与动量守恒原理,建立了载体位置无控、姿态受控飘浮基两杆柔性空间机械臂系统的动力学方程。接着利用奇异摄动法,将这个柔性两杆空间机械臂系统分解为一个慢变子系统与一个快变子系统。以此为基础,提出了一个包含慢变控制项与快变控制项的复合控制器。利用动态滑模观测器得到慢变子系统的观测速度矢量,基于这个观测速度矢量设计系统的鲁棒慢变控制律来实现载体姿态、关节轨迹的跟踪。利用线性观测器得到快变子系统的观测速度矢量,基于这个观测速度矢量与线性系统的最优控制理论设计系统的快变控制力矩,实现两柔性杆振动的抑制。最后通过系统的数值仿真,证实了方法的有效性。     

机器人臂的多项式PD型学习控制方法

提出一种用于机器人臂的带有重力补偿的多项式PD型(PPD)学习控制器,基于多项式神经网络给出了这种控制器的比例系数连续学习算法,由非线性机器人动力学模型与所提出的学习控制器所组成的闭环系统被证明在满足李雅普诺夫直接法和拉萨尔不变集定理时是全局渐近稳定的,除了理论结果,也提供了在两自由度机器人臂位置控制中的仿真实验比较,结果表明PPD学习控制器在系统快速响应性方面优于常规PD控制器。PPD学习控制器为机器人控制系统提供了一种新的途径。     

RBF神经网络滑模变结构控制在并联机器人中的应用

并联机器人系统结构复杂,具有强耦合、非线性等特点。滑模变结构控制对参数不确定性和外部扰动具有强鲁棒性,不需要被控对象精确数学模型且基于该方法的控制器设计过程是自然解耦过程,适用于并联机器人控制,但是滑模控制普遍存在抖振问题。鉴于此,该文提出RBF神经网络与滑模控制相结合的控制方法,利用RBF神经网络对滑模控制器切换项的增益进行调节,可以有效地降低滑模控制的抖振,获得较好的控制效果。仿真结果表明,该控制方法跟踪性能好,系统误差小,具有较强的鲁棒性,可以满足并联机器人的控制要求。     

Adaptive second-order fast nonsingular terminal sliding mode control for robotic manipulators

This paper presents an adaptive chattering-free sliding mode controller for trajectory tracking of robotic manipulators in the presence of external disturbances and inertia uncertainties. To achieve fast convergence and desirable tracking precision, a second-order fast nonsingular terminal sliding mode (SOFNTSM) controller is designed to guarantee system performance and robust stability. Chattering is eliminated using continuous control law due to high-frequency switching terms contained in the first derivative of actual control signals. Meanwhile, uncertainties are compensated by introducing the adaptive technique, whose prior knowledge about upper bound is not required. Finally, simulation results validate the effectiveness of the proposed control scheme.