基于信号重构的可重构机械臂主动分散容错控制

针对可重构机械臂系统传感器故障,提出一种基于信号重构的主动分散容错控制方法. 基于可重构机械臂系统模块化属性,采用自适应模糊分散控制系统实现正常工作模式时模块关节的轨迹跟踪控制. 当在线检测出位置或速度传感器故障时,分别采用数值积分器或微分跟踪器重构相应信号,并以之代替故障信号进行反馈实现系统的主动容错控制. 此方法充分利用了冗余信息,避免了故障关节控制性能的下降对其他关节的影响. 数值仿真结果验证了所提出容错控制方法的有效性.     

考虑多传感器故障的可重构机械臂主动取代分散容错控制

针对可重构机械臂系统位置传感器和速度传感器多故障, 提出一种主动取代分散容错控制方法. 基于可重构机械臂的模块化属性, 设计正常工作模式下的分散神经网络控制器. 利用微分同胚原理将子系统结构进行非线性变换, 将传感器故障转化成伪执行器故障, 设计分散滑模观测器以对多传感器故障进行实时检测, 并利用其输出信号取代故障传感器信号, 实现了多传感器故障情形下可重构机械臂的主动容错控制. 仿真结果表明了所设计的容错控制方法的有效性.     

一种可重构机械臂的自组织协调控制

主要研究一种新的具有树型结构的可重构机械臂的自组织协调控制问题，首先给出这种可重构机械臂的运动学、动力学方程及其结构变化的关系；然后通过研究一个较通用的任务模型建立了系统的动力学方程，由此提出一个自组织协调控制策略，最后仿真结果证明了控制规律是有效的。     

漂浮基空间机械臂的反演滑模容错控制

讨论了载体位置不受控制的情况下,漂浮基三杆空间机械臂系统的滑模容错控制问题.选择合适的坐标系,利用拉格朗日第二动力学方程,结合系统质心定义,根据系统动量守恒原理,建立漂浮基三杆空间机械臂系统的动力学方程.依据非奇异滑模控制和积分滑模控制理论提出切换函数,基于反演的控制策略,结合高阶滑模控制理论,提出了一个新型的控制率,...     

基于观测器的可重构机械臂分散自适应模糊控制

提出一种基于观测器的可重构机械臂分散自适应模糊控制方案.将可重构机械臂的动力学描述为一个交联子系统的集合,子系统控制器由自适应模糊系统和鲁棒控制项组成.基于状态观测器观测值构建的自适应模糊系统用于逼近子系统动力学模型和交联项,鲁棒控制项用于抵消模糊逼近误差对轨迹跟踪的影响.数值仿真证明了所提出的分散控制方案的有效性.     

基于速度观测模型的可重构机械臂补偿控制

针对可重构机械臂动力学中存在的模型参数摄动和外界扰动,本文阐述了一种基于速度观测模型的模糊RBF神经网络补偿控制算法.利用Lyapunov函数给出了网络的权值、隶属度函数中心和宽度倒数的在线更新律,并证明了所提出的观测模型及其补偿控制算法的最终一致有界性.最后以RRP(revolute-revolute-prismatic)构形的可重构机械臂为例,通过仿真研究了算法对轨迹跟踪问题的有效性,同时与基于速度观测模型的RBF神经网络补偿控制进行了仿真对比及分析,给出了神经网络和模糊神经网络在可重构机械臂轨迹控制应用中各自的优缺点.     

基于深度强化学习的机械臂容错控制方法

针对机械臂突发单关节故障的情况,提出一种基于深度强化学习的机械臂容错控制方法。在建立环境模型和奖罚机制的基础上,针对机械臂正常运行和故障运行的情况,使用无模型的强化学习算法进行离线训练。在Rviz中建立机械臂模型并使用上述网络进行在线控制。实验证明:该算法可以有效完成机械臂的正常控制和容错控制。     

基于运动学模型重构的单关节故障机械臂容错路径规划

针对单关节故障机械臂的路径规划问题,提出一种基于运动学模型重构的容错路径规划方法.首先基于旋量理论进行单关节故障机械臂的通用运动学模型重构;然后分析机械臂的退化工作空间,并以运动性能平稳为约束对其进行栅格化处理;最后通过改进传统的A$^\ast$算法,在退化工作空间中搜索出能够满足任务要求的轨迹.以七自由度机械臂为对象进行仿真实验,验证了所提出方法的正确性和有效性.     

可重构模块机器人分散容错控制

针对可重构模块机器人的执行器故障,提出一种基于自适应模糊系统的分散被动容错控制方法.该方法不需要机器人动力学模型与模块之间的信息交换,模块控制器分别采用间接和直接自适应方法设计,自适应参数的更新律基于Lyapunov稳定性理论设计,保证了系统的稳定性和H∞跟踪性能.数值仿真结果表明了所提出方法的有效性.     

改进非线性干扰观测器的机械臂自适应反演滑模控制

针对传统滑模和传统干扰观测器在机械臂关节位置跟踪中存在的控制输入抖振、需要测量加速度项、应用模型受限等问题,提出一种改进非线性干扰观测器的机械臂自适应反演滑模控制算法。首先,设计改进的非线性干扰观测器进行在线测试,在滑模控制律中加入干扰估计值对可观测的干扰进行补偿;然后选择合适的设计参数,使观测误差指数型收敛;其次,引入反演自适应控制律,对不可观测的干扰进行估计,进一步改善控制系统的跟踪性能;最后,利用李雅普诺夫函数验证了闭环系统的渐近稳定性,并将其应用于机械臂关节位置跟踪。实验结果表明,与传统滑模算法比较,所提控制算法不但加快了系统的响应速度,而且能有效地削弱系统抖振、避免测量加速度项并扩大应用模型使用范围。     

具有时滞的柔性关节多机械臂协同自适应位置/力控制

由于关节机械臂长期运行后,齿轮间隙扩大产生的时间滞后将使得系统跟踪性能降低.针对此问题,本文提出了一种自适应位置/力控制策略来保证闭环系统稳定性以及位置/力跟踪性能.首先,对多机械臂和物体系统进行任务空间动力学建模.随后,利用Pade理论将时间滞后近似为二阶有理分式.同时,利用神经网络自适应算法克服模型建模误差对系统稳定性的影响,利用同时包含位置误差和力误差的线性滑模项,设计位置/力控制器.通过李雅普诺夫稳定性理论,证明控制策略能实现位置误差和内力误差的渐近收敛.最后,仿真验证证明所设计控制策略的有效性.     

基于反推方法的一类自适应神经网络容错控制

针对一类可控标准型基础上添加非线性模型误差与故障项的MIMO非线性系统,结合反推技术,提出了神经网络自适应控制方案,对模型误差与故障项进行在线估计。文中鲁棒项用于补偿逼近模型误差,当检测出系统故障时,通过调整各步骤的虚拟控制量来补偿故障项,消除故障项对系统的影响。通过理论证明实现了提出的控制方法使得各残差信号一致有界,并最终收敛到一个小的邻域内。实例仿真表明该方案的可行性。     

Decentralized adaptive fuzzy sliding mode control for reconfigurable modular manipulators

A stable decentralized adaptive fuzzy sliding mode control scheme is proposed for reconfigurable modular manipulators to satisfy the concept of modular software. For the development of the decentralized control, the dynamics of reconfigurable modular manipulators is represented as a set of interconnected subsystems. A first‐order Takagi–Sugeno fuzzy logic system is introduced to approximate the unknown dynamics of subsystem by using adaptive algorithm. The effect of interconnection term and fuzzy approximation error is removed by employing an adaptive sliding mode controller. All adaptive algorithms in the subsystem controller are derived from the sense of Lyapunov stability analysis, so that resulting closed‐loop system is stable and the trajectory tracking performance is guaranteed. The simulation results are presented to show the effectiveness of the proposed decentralized control scheme. Copyright © 2009 John Wiley & Sons, Ltd.     

Robust adaptive fault-tolerant control for time delay uncertain nonlinear systems with time-varying performance bounds

In this paper, a robust adaptive fault tolerant controller guaranteeing with time-varying performance bounds is designed for a class of time delay uncertain nonlinear systems subject to actuator failures and external disturbance. The influence of time delay on the system is mitigated and the system performance can be guaranteed by introducing a positive nonlinear control gain function and the generalised restricted potential function. A new method with more design degrees of freedom is developed to ensure the norm of the system state within a-priori, user-defined time varying performance bounds. Using the online estimation information provided by adaptive mechanism, a robust adaptive fault-tolerant control method guaranteeing time varying performance bounds is proposed. It is shown that all the signals of the resulting closed-loop system are bounded and the system state less than a-priori, user-defined performance bounds. Finally, simulation results are given to demonstrate the efficacy of the proposed fault-tolerant control method.     

Differentiator-based time delay control for uncertain robot manipulators

High-quality acceleration signal plays a significant role in fast and precise trajectory tracking of robot manipulators via time delay control (TDC). This paper proposes a fast transient tracking differentiator (FTD) for obtaining the noise-less time derivative from a noisy measurement within the framework of tracking differentiator (TD) design methodology. Global asymptotic convergence of the proposed FTD is proven by Lyapunov's direct method and TD theory. The proposed FTD is cascaded to construct an acceleration estimation and is integrated with the commonly used TDC for an improved trajectory tracking of robot manipulators in the presences of parametric uncertainties and bounded disturbances. Numerical simulations and real-time experimental validation comparisons demonstrate that the proposed approach provides an easy-going model-free improved design for fast and accurate trajectory tracking of robot manipulators with position measurement only.     

带有完全分布式观测器的多智能体系统自适应容错一致性

针对一类同时带有执行器故障,未知非线性动态和非匹配干扰的多智能体系统,本文提出一种新的自适应容错控制方案.首先,设计一种适用于有向切换拓扑的完全分布式观测器估计领导者的信息,将一致性问题转化为局部的信号跟踪问题.其次,拆解转化后的误差系统为两个耦合的子系统,实现非匹配干扰与匹配因子分离.然后,利用径向基神经网络近似非线...     

Integrated multiple-model adaptive fault identification and reconfigurable fault-tolerant control for Lead-Wing close formation systems

This paper investigates the attitude and position tracking control problem for Lead-Wing close formation systems in the presence of loss of effectiveness and lock-in-place or hardover failure. In close formation flight, Wing unmanned aerial vehicle movements are influenced by vortex effects of the neighbouring Lead unmanned aerial vehicle. This situation allows modelling of aerodynamic coupling vortex-effects and linearisation based on optimal close formation geometry. Linearised Lead-Wing close formation model is transformed into nominal robust H-infinity models with respect to Mach hold, Heading hold, and Altitude hold autopilots; static feedback H-infinity controller is designed to guarantee effective tracking of attitude and position while manoeuvring Lead unmanned aerial vehicle. Based on H-infinity control design, an integrated multiple-model adaptive fault identification and reconfigurable fault-tolerant control scheme is developed to guarantee asymptotic stability of close-loop systems, error signal boundedness, and attitude and position tracking properties. Simulation results for Lead-Wing close formation systems validate the efficiency of the proposed integrated multiple-model adaptive control algorithm.     

A fully adaptive decentralized control of robot manipulators

In this paper, we develop a fully adaptive decentralized controller of robot manipulators for trajectory tracking. With high-order and adaptive variable-structure compensations, the proposed scheme makes both position and velocity tracking errors of robot manipulators globally converge to zero asymptotically while allowing all signals in closed-loop systems to be bounded, even without any prior knowledge of robot manipulators. Thus this control scheme is claimed to be fully adaptive. Even when the proposed scheme is modified to avoid the possible chattering in actual implementations, the overall performance will remain appealing. Finally, numerical results are provided to verify the effectiveness of the proposed schemes at the end.     

时滞柔性关节机械臂自适应位置/力控制

针对具有时滞的柔性关节机械臂自适应位置和力控制问题进行了研究.首先,通过坐标变换得出降维的位置/力控制模型.随后,将时间滞后近似表示成一阶滞后,进行时滞补偿.利用自适应算法修正机械臂系统参数,克服模型参数不确定性对系统的影响.同时,采用反步控制技术设计机械臂位置/力控制器,运用Lyapunov稳定性定理证明控制器能使机械臂位置和力跟踪误差收敛.最后的仿真研究验证了控制方案的有效性.