一种全局稳定的直接预测自适应控制器

本文提出一种基于多阶段二次型滚动优化指标的预测控制算法，在假定被控系统前Ｌ个脉冲响应系数已知的条件下，用标准的自适应分析方法证明了直接预测控制算法的全局稳定性及渐近最优性。     

工业机器人自适应力控制的新方法

机器人力控制系统的稳定性对接触环境刚性的变化很敏感，为了解决这一问题，本文首先建立了一种机器人与刚性环境相接触的动力学模型，然后，基于Ｐｏｐｏｖ超稳定理论设计出了一种机器人自适应力控制算法，该算法通过辨识环境刚性以获取与接触环境相适应的力控制反馈增益系数，理论分析和实现结果都证明这种方法在环境刚性大范围变化时，均能获得的控制效果。     

自适应容错控制的发展与展望

自适应容错控制出现了一些新进展及其代表性工作.首先,给出自适应容错控制的内涵;然后,将其分为四大类:基于故障参数估计的自适应容错控制,基于近似模型的自适应容错控制,基于多模切换与校正的自适应容错控制和直接自适应容错控制,重点论述了模型参考自适应容错控制;最后,提出了一些具有挑战性的问题.     

磁悬浮自适应控制

以自适应PID结构针对磁悬浮系统设计非线性控制器，并在磁悬浮球装置上进行了试验，结果证实这种控制器具有完全的鲁棒性、良好的参数适应性，设计方法也有广泛的适用性。     

国家教委科技委员会第二次第二届自动控制学科组专题报告

辨识与控制的配合袁震东（华东师范大学数学系·上海，２０００６２）辨识与控制应该相互配合似乎是一种不言而喻的常识，然而真正认识这一问题的本质及其重要性还只是近几年的事．众所周知，辨识与控制的自然结合出现于自适应控制中．１９８０年ｔｈｅｄｗｉｎ，Ｒａｒｎ...     

具有降阶模型的多变量鲁棒自适应前馈控制器

本文提出了一种多变量鲁棒自适应前馈控制器。该控制器采用低阶模型来控制参数未知的高阶多变量系统时,在可测干扰和有界不可测干扰作用下能保证自适应系统稳定运行。当可测干扰与系统输出之间存在未建模动态时,它可以对可测干扰实行有效的动静态补偿。当只有有界干扰作用时,它能使有界干扰对系统产生的影响最小。本文还给出了采用所提出的控制器控制某钢厂间歇式余热锅炉的仿真结果。     

增益模糊修正和自适应律

本文给出了一种兼顾系统鲁棒性和暂态特性的自适应律，我们称之为增益模糊修正自适应律，分析及仿真表明，它除保持了死区修正方案相对于有界扰动的鲁棒性之外，又克服了死区修正方案及原始的积分式自适应律方案暂态品质差的问题，尤其是对一类严重欠阻尼的二阶对象，与死区修正适应方案或积分式自适应方案相比，它显著地提高了系统的暂态品质。     

Adaptive non-singular fast terminal sliding mode based on prescribed performance for robot manipulators

A fast convergent non-singular terminal sliding mode adaptive control law based on prescribed performance is formulated to solve the uncertainties and external disturbances of robot manipulators. First, the tracking error of robot manipulators is transformed by using the prescribed performance function, which improves the transient behaviors and steady-state accuracy of robot manipulators. Then, a novel fast convergent non-singular terminal sliding mode surface is brought up according to the transformed error, and the control law is derived to meet the stability requirements of robot manipulators. In practice, the upper boundary of the lumped disturbances cannot be accurately obtained. Therefore, an adaptive prescribed performance control (PPC) controller to lumped disturbances is brought up to ensure the stability and finite-time convergence of robot manipulators. Finally, the system stability of robot manipulators is proved by the Lyapunov theorem. Simulation results and comparative analysis demonstrate the superiority and robustness of the raised strategy.     

航天器自适应快速非奇异终端滑模容错控制

针对存在外部干扰、转动惯量矩阵不确定以及执行器故障的航天器姿态跟踪控制问题,本文提出了基于自适应快速非奇异终端滑模的有限时间收敛故障容错控制方案.通过引入能够避免奇异点,且具有有限时间收敛特性的快速非奇异终端滑模面,设计了满足多约束条件有限时间收敛的姿态跟踪容错控制律,利用参数自适应方法使控制器不依赖转动惯量和外部干扰的上界信息.Lyapunov稳定性分析表明:在存在外部干扰、转动惯量矩阵不确定以及执行器故障等约束条件下,本文设计的控制律能够保证闭环系统的快速收敛性,而且对执行器故障具有良好的容错性能.数值仿真校验了该控制律在姿态跟踪控制中的优良性能.     

基于神经网络的不确定机器人自适应滑模控制

提出一种机器人轨迹跟踪的自适应神经滑模控制。该控制方案将神经网络的非线性映射能力与变结构控制理论相结合,利用RBF网络自适应学习系统不确定性的未知上界,神经网络的输出用于自适应修正控制律的切换增益。这种新型控制器能保证机械手位置和速度跟踪误差渐近收敛于零。仿真结果表明了该方案的有效性。     

A Robust Adaptive Terminal Sliding Mode Control for Rigid Robotic Manipulators

In this paper, a robust adaptive terminal sliding mode controller is developed for n-link rigid robotic manipulators with uncertain dynamics. An MIMO terminal sliding mode is defined for the error dynamics of a closed loop robot control system, and an adaptive mechanism is introduced to estimate the unknown parameters of the upper bounds of system uncertainties in the Lyapunov sense. The estimates are then used as controller parameters so that the effects of uncertain dynamics can be eliminated and a finite time error convergence in the terminal sliding mode can be guaranteed. Also, a useful bounded property of the derivative of the inertial matrix is explored, the convergence rate of the terminal sliding variable vector is investigated, and an experiment using a five bar robotic manipulator is carried out in support of the proposed control scheme.     

机器人的非奇异终端神经滑模轨迹跟踪控制

针对具有不确定性的机器人系统,为提高系统的稳态跟踪精度,提出一种非奇异终端神经滑模轨迹跟踪控制方案.控制器采用改进的非奇异终端滑模面,并基于径向基函数神经网络自适应调整控制律的切换项,不但克服了在设计中需要知道系统不确定性的上界的限制,而且平滑了控制信号.可应用Lyapunov稳定性理论证明了系统的渐近稳定性和跟踪误差的渐近收敛性.仿真结果验证了控制方法不仅能够保证机器人系统轨迹跟踪控制的快速性和鲁棒性,而且有效地削弱了抖振,可见方案是可行且有效的.     

基于终端滑模的机械手鲁棒自适应控制

对于不确定的机械手系统,提出一种鲁棒自适应控制方法,用自适应控制来估计系统的未知参数,用终端滑模控制来减少不确定因素的影响,为了避免因干扰的存在使自适应的估计参数发生漂移,引入死区自适应控制．仿真表明,滑模控制不仅抑制了误差,而且消除了死区自适应算法的局限性,该算法在取得较好控制效果的同时,具有很强的鲁棒性．     

Design of an adaptive tracker for n-link rigid robotic manipulators based on super-twisting global nonlinear sliding mode control

This paper develops an adaptive super-twisting global nonlinear sliding mode control technique for n-link rigid robotic manipulators. A novel control law is designed to guarantee elimination of the reaching phase and existence of the sliding mode around the surface right from the initial time. Furthermore, the adaptive tuning law eliminates requirement of the knowledge about the upper bounds of external disturbances. By using the proposed method, a robust controller is designed so that the tracking error of rigid manipulator is convergent to the global nonlinear sliding surface in a finite time, and strong robustness with respect to large uncertainties and disturbances is guaranteed. Illustrative simulations on a two-link elbow robot manipulator and a three degree of freedom rigid manipulator are presented to show the robustness and effectiveness of the suggested design compared to other method. Moreover, a simulation as well as experimental study of a rotary inverted pendulum system demonstrates the applicability of the proposed method.     

Buck型变换器非奇异固定时间滑模控制

针对存在参数不确定性的Buck变换器系统,提出一种非奇异固定时间滑模控制方法。首先,设计非奇异固定时间滑模面,并基于该滑模面设计固定时间控制器,保证系统输出电压误差在固定时间内收敛到平衡点的邻域内,且其收敛时间上界与系统初始状态无关。其次,设计自适应律估计系统不确定干扰上界,有效抑制不确定干扰对系统的影响,该方法无需干扰上界的先验知识。最后,仿真结果验证了所提方法的有效性。     

Adaptive nonsingular fast terminal sliding mode control for underwater manipulator robotics with asymmetric saturation actuators

In this paper, an adaptive nonsingular fast terminal sliding mode control (ANFTSMC) is proposed for underwater manipulator robotics with asymmetric actuator saturations and unknown time-varying (TV) external disturbances. Firstly, the nonsingular fast terminal sliding mode (NFTSM) control scheme is conducted for the underwater manipulator robotics, which guarantees the boundedness of all the signals in the control system. Secondly, the adaptive method and the smooth hyperbolic tangent (tanh) function are introduced to address the unknown TV external disturbances and the input saturation errors. Thus the prior knowledge about the upper bounds of the system uncertainties is not needed in this paper. To deal with the nonlinear asymmetric input saturation issue, a Gaussian error function is employed in the asymmetric saturation module so that the discontinuous input signals can be transformed into smooth forms. Thirdly, the rigorous mathematical verification is conducted to demonstrate the stability and finite-time convergence of the closed-loop control system via the Lyapunov theory. Finally, numerical simulations are performed on a two-link underwater manipulator robotic system to illustrate the effectiveness of the proposed controller.     

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.