刚体连杆电驱动机器人的分散鲁棒跟踪控制

该文针对不确定刚体连杆电驱动机器人的跟踪控制问题，提出了一种新的分散控制器设计方法：首先设计标称控制器使标称闭环系统具有理想的跟踪性能；然后设计鲁棒补偿器以抑制非线性耦合、关节摩擦、参数不确定性和外扰等因素的影响。理论分析及仿真结果表明，在具有足够带宽的情况下，不需要测量电枢电流，该控制器可以保证跟踪误差局部终值有界，并具有可在线调整的特点。     

3-RRRT并联机器人鲁棒自适应模糊滑模控制

针对3-RRRT型搬运并联机器人提出了一种直接自适应模糊滑模控制方法.根据机器人的系统动力学模型特点,基于Lyapunov函数的综合设计方法和滑模控制理论,利用模糊逻辑系统与自适应技术相结合,提出了一种控制律,然后进行了系统控制仿真实验.结果表明,采用这种直接自适应模糊滑模控制方法的3-RRRT型并联机器人在周期干扰状况下达到了较高的轨迹控制精度,其闭环系统具有较强的自适应性和鲁棒稳定性.     

电力系统非线性鲁棒自适应分散励磁控制设计

利用反步法设计了多机电力系统中的非线性鲁棒自适应励磁控制方案,控制目标是调节发电机功角和频率至稳态运行点的极小领域,并使闭环系统对发电机阻尼系数和电抗参数的不确定性具有自适应能力,且对模型误差和外部有界干扰具备鲁棒性,同时保证各控制器是分散化和本地化的。采用4机系统进行的数字仿真结果表明,实施此方案能有效地提高发电机的功角稳定性。     

高压直流换流站分散鲁棒自适应控制器的设计

针对高压直流输电系统（HVDC），提出了一种换流站的分散鲁棒自适应控制器的设计方法，设计中引入自适应非线性阻尼项来抑制系统非线性不确定参数和未知有界干扰的影响，同时采用反演设计方法来克服控制器设计的复杂性，最后获得高压直流输电系统换流站的分散鲁棒自适应控制策略的一般表达式，并提供了整个系统的稳定性证明，所得控制器仅利用本地测量量实现，控制策略具有分散性和适应性，通过NETOMAC数字仿真，仿真结果证明该控制器比常规的PI控制器具有更好的控制效果。     

具有电枢反应非线性不确定性的直流电机速度鲁棒跟踪控制研究

该文针对电枢反应引起的非线性不确定性及具有参数变化和负载扰动的直流电机速度跟踪控制问题，构造了一个适当的增广被控对象，将其转化为一标准设计问题，设计了速度控制系统的鲁棒状态反馈控制器，进而利用二自由度鲁棒跟踪设计方法设计了速度鲁棒跟踪控制器。仿真研究结果表明，该文所设计的速度鲁棒跟踪控制系统，不仅对于电机的非线性不确定性有较好的控制效果，而且可以有效地抑制电机负载扰动的影响。     

一种具有参数不确定性的直流电机系统鲁棒自适应摩擦补偿方法

针对陀螺漂移测试转台直流力矩电机系统中存在的非线性动态摩擦和电机参数不确定性，为提高转台摇摆状态位置跟踪精度，提出了一种新的鲁棒自适应补偿控制器。电机中摩擦模型采用摩擦参数为非一致性变化的LuGre动态摩擦模型。该控制器包含一个参数自适应律和等效PID控制律来估计未知LuGre模型参数和电机参数并给与补偿。最后Lyapunov方法和仿真结果证明该鲁棒自适应补偿控制器保证了闭环系统全局稳定性和对期望位置信号的渐进跟踪，提高了转台摇摆跟踪精度。     

移动臂式服务机器人的鲁棒补偿控制

由移动平台和操作臂构成的服务机器人同时具有可移动性和操作性,但移动平台和操作臂之间存在着耦合干扰,系统建模复杂.基于此,建立了服务机器人的标称模型,利用非线性反馈实现了系统解耦,提出了计算力矩加比例和微分反馈的控制算法.针对控制系统存在的建模不确定性和干扰,对已建立的控制律进行补偿,并采用Lyapunov方法确定补偿项,实现了移动服务机器人对期望轨迹跟踪的鲁棒控制.对移动平台系统和机械臂系统进行了仿真实验,实验结果表明,所提出的控制方案能实现对移动臂式服务机器人的鲁棒控制,验证了所设计控制律的有效性和正确性.     

感应电机的神经网络鲁棒自适应动态面控制

针对感应电机的高阶、强耦合的非线性,设计一种具有自适应性和鲁棒性的动态面控制律,以实现对感应电机的控制。首先通过变量代换,将五阶感应电机模型变为块三角形式;接着采用神经网络逼近,将模型转化为含有结构不确定性和参数不确定性的参数化模型。对于感应电机系统中的参数不确定性,在动态面控制方法的基础上设计参数自适应律,在线估计其未知参数;对于感应电机系统中的结构不确定性,设计鲁棒控制律,使得电机控制系统具有鲁棒性。最后通过仿真实现,以验证所提出的控制方法的有效性与实用性。     

高压直流输电系统换流站鲁棒自适应输出反馈控制

针对高压直流输电系统,设计了一种鲁棒自适应输出反馈控制器.首先,将高压直流输电系统换流站动态模型转换成用输入输出表示的非线性系统.然后,利用自适应非线性阻尼项来抑制系统的非线性动态不确定性和未知有界扰动,应用Lyapunov稳定性理论构造出控制器和自适应参数的表达式.Lyapunov稳定性分析结果表明,文中所提出的控制器保证了闭环系统的稳定性.最后,将设计的控制器应用到一个3机直流输电系统中,仿真结果表明,与传统的PI控制器相比较,文中控制器可大大提高系统的稳定性和鲁棒性.     

多机电力系统自适应鲁棒Terminal滑模励磁控制

设计了多机电力系统发电机励磁的自适应鲁棒Terminal滑模控制器,将L2增益干扰抑制、自适应逆推法、Terminal滑模控制相结合,可以自适应估计发电机的不确定阻尼系数,对扰动具有鲁棒性。给出了控制器的设计过程。针对2区域4机系统的仿真结果表明,所设计的自适应鲁棒Terminal滑模励磁控制器能够快速抑制功率振荡,有效提高电力系统的暂态稳定性,并保持机端电压的恒定。     

Identification for the robust control of robot manipulators

In this paper an identification scheme, which yields bounds on unmodelled dynamics along with an estimate for the parameters of a nominal dynamic model, has been presented. These estimates are useful for designing a robust controller for trajectory control of robot manipulators, if they satisfy certain conditions. These conditions have been stated mathematically. Guidelines are provided for selecting a data set for identification such that the obtained estimates satisfy the above conditions. Simulation results are presented for a two‐link serial manipulator, when frictional torques are treated as unmodelled. Copyright © 2001 John Wiley & Sons, Ltd.     

机器人的神经网络鲁棒轨迹跟踪控制

考虑了一类具有外界扰动和参数不确定性机器人系统的轨迹跟踪鲁棒控制问题。提出了两种控制方法：第一种应用输入输出线性化方法以及Lyapunov函数法,推导出鲁棒输出跟踪控制器。所获得的控制器可确保系统输出按指数规律跟踪期望输出,同时相应闭环系统的状态一致最终有界。第二种方法在第一种控制方法的基础上,利用一个RBF神经网络自适应学习系统不确定性的未知上界,有效的克服了系统不确定性的影响,提高了控制精度。     

Neural adaptive robust output feedback control of wheeled mobile robots with saturating actuators

This paper addresses the output feedback tracking control problem of electrically driven wheeled mobile robots subjected to actuator constraints. The main drawback of previously proposed controllers is the actuator saturation problem, which degrades the transient performance of the closed‐loop control system. In order to alleviate this problem, a saturated tracking controller has been proposed using the hyperbolic tangent function. A new nonlinear observer is introduced in order to leave out the velocity sensors in the robot system to decrease the cost and weight of the system for practical applications. A dynamic surface control strategy is effectively used to reduce the design complexity when considering actuator dynamics. In addition, neural network approximation capabilities and adaptive robust techniques are also adopted to improve the tracking performance in the presence of uncertain nonlinearities and unknown parameters. Semi‐global stability of the closed‐loop system is presented using direct Lyapunov method. Simulation results are provided to illustrate the effectiveness of the proposed control system for a differential drive mobile robot in practice. Copyright © 2014 John Wiley & Sons, Ltd.     

A generalized global adaptive tracking control scheme for robot manipulators with bounded inputs

In this work, a generalized adaptive scheme for the global motion control of robot manipulators with constrained inputs is proposed. It gives rise to various families of bounded adaptive controllers defined through a general class of saturation functions. Compared with adaptive tracking control algorithms previously developed in a bounded input context, the proposed adaptive approach guarantees the motion control objective for any initial condition, avoiding discontinuities throughout the scheme, preventing the inputs to reach their natural saturation bounds, and permitting innovation on the saturating structure through its generalized form, giving a wide range of possibilities for performance improvement. Experimental results corroborate the efficiency of the proposed scheme. Copyright © 2014 John Wiley & Sons, Ltd.     

A class of adaptive regulators for robot manipulators

In this paper we propose a framework to adaptive regulator design of robot manipulators. A class of global regulators for robot is characterized for which we provide guidelines to derive adaptive versions. The class of regulators is described by control laws comprising the gradient of an artificial potential energy depending in a linear manner on the robot and payload unknown parameters plus a linear velocity feedback. We provide explicit sufficient conditions on the artificial potential energy which allow to obtain an adaptive regulator which yields a stable closed-loop system and global positioning. Using this framework we revise two previously proposed adaptive regulators and we suggest two new ones. © 1998 John Wiley & Sons, Ltd.     

模型不确定的下肢康复机器人轨迹跟踪自适应控制

为了实现康复训练过程中高精度的轨迹跟踪控制,针对下肢康复机器人的模型参数和外界干扰等不确定性因素对其轨迹跟踪造成严重影响,提出一种模型不确定的下肢康复机器人轨迹跟踪自适应控制方法。根据所提方案,设计了相应的轨迹跟踪自适应控制器;并进行了轨迹跟踪控制仿真实验对比分析,结果表明,计算力矩控制方法在系统模型不确定时,膝关节的最大角度跟踪误差高达11.3°,髋关节最大稳态误差4.6°;而轨迹跟踪自适应控制方法在模型不确定的情况下,髋关节和膝关节的角度跟踪稳态误差均收敛于零;轨迹跟踪自适应控制方法可以显著提高下肢康复机器人轨迹跟踪的精度。     

基于自适应模糊滑模控制的机器人轨迹跟踪算法

针对控制参数的不确定性以及存在未知外部扰动情况下移动机器人的轨迹跟踪问题,提出一种基于光滑非线性饱和函数的自适应模糊滑模轨迹跟踪控制算法。通过建立不确定非线性移动机器人运动控制模型,利用自适应模糊逻辑系统构建自适应模糊滑模控制器。为了增强轨迹跟踪控制算法对随机不确定外部扰动适应能力的同时削弱滑模控制算法中的输入抖振现象,利用有界输入有界输出(BIBO)稳定的方法,通过带有自适应调节算法的模糊系统对滑模控制律中非线性函数项进行自适应逼近,并设计了模糊系统中可调参数的自适应控制律,保证了控制系统的稳定与收敛。实验结果表明,所设计的控制器对系统参数不确定性和外界扰动均具有较强的轨迹跟踪性能和鲁棒性。与传统的滑模控制算法相比,该算法不仅能有效减小输入抖振而且轨迹跟踪控制精度提高了18.89%。     

Decentralized adaptive linear control of complex systems using relative deadzones

This paper aims to analyse the system stability when decentralized adaptive controllers are applied to multi-input/multi-output non-linear interconnected systems. The local adaptive controllers are designed based on linear models by employing relative deadzones. Using a small-gain-type argument, we can derive an M-matrix test condition for local stability. If the system to be controlled can be described by global Lipschitz functions, a global stable closed-loop system is obtained. © 1997 by John Wiley & Sons, Ltd.     

Issues,progress and new results in robust adaptive control

We overview recent progress in the field of robust adaptive control with special emphasis on methodologies that use multiple‐model architectures. We argue that the selection of the number of models, estimators and compensators in such architectures must be based on a precise definition of the robust performance requirements. We illustrate some of the concepts and outstanding issues by presenting a new methodology that blends robust non‐adaptive mixed µ‐synthesis designs and stochastic hypothesis‐testing concepts leading to the so‐called robust multiple model adaptive control (RMMAC) architecture. A numerical example is used to illustrate the RMMAC design methodology, as well as its strengths and potential shortcomings. The later motivated us to develop a variant architecture, denoted as RMMAC/XI, that can be effectively used in highly uncertain exogenous plant disturbance environments. Copyright © 2006 John Wiley & Sons, Ltd.