仿生假手抓握力控制策略

为了使仿生假手完成各种精细作业,提出一种抓握力控制策略.在自由空间和约束空间中分别使用基于位置的阻抗控制和力跟踪阻抗控制.在过渡过程中使用模糊观测器切换控制模式.两种控制模式采用同一个基于位置的阻抗控制器,在约束空间向阻抗控制器中引入参考力,以满足约束空间的抓握力控制要求.这种方法可以使关节在自由空间和约束空间中分别实现良好的轨迹跟踪和力矩跟踪,在过渡过程中实现控制模式的可靠切换和系统的稳定过渡.提出一种自适应滑模摩擦力补偿方法,利用终端滑模思想设计了滑模函数,使得系统跟踪误差在有限时间内收敛,避免了传统线性滑模面状态跟踪误差无法在有限时间内收敛至0的问题.根据指数形式摩擦力的特点,利用终端滑模控制思想获得包含摩擦力参数估计的滑模控制律,并基于李亚普诺夫稳定性定理推导了估计参数的在线自适应律.对该抓握力控制策略在HIT假手上进行了抓取实验,实验结果证明了控制策略的有效性.     

基于模糊混合控制的自治水下机器人路径跟踪控制

基于模糊混合控制策略,本文提出了一种用于非线性欠驱动自治水下机器人的鲁棒路径跟踪控制方法.利用Sugeno型模糊推理系统,将PD滑模控制器与非奇异终端滑模控制器光滑连接,构造了模糊混合控制器.它能充分融合这两类控制器的优势,无论系统远离平衡点还是在其附近,都能取得快速收敛的效果.如果,借助于非时间参考量,将该混合控制器用于自治水下机器人路径跟踪控制,将有利于提高它在不确定环境中的跟踪能力.最后,通过仿真计算结果验证了该控制策略的有效性.     

基于FNN的滑模自适应控制

研究一类不确定性非线性系统的直接自适应控制方法。该方法由滑模控制器和模糊神经网络构成，通过平滑切换实现自适应控制策略。仿真结果表明，这种方法既有强鲁棒性，又能有效地消除高频颤动。     

基于模糊扰动观测器的PMSM积分滑模控制研究

为了克服传统永磁同步电机(Permanent magnet synchronous motor,PMSM)的滑模控制增益大容易产生抖振的问题,提出基于模糊观测器的PMSM积分滑模控制策略。采用新型趋近律设计积分滑模控制器取代传统的滑模控制器,提高系统的动态响应性能。结合模糊控制与自适应控制的特点,设计模糊扰动观测器,能够迅速有效地观测系统内部参数变化和外部扰动,并对积分滑模速度控制器进行前馈补偿,削弱系统抖振的同时提高了系统的鲁棒性。通过李雅普诺夫理论证明了该控制系统的稳定性。仿真及实验结果验证了该方法具有较强的鲁棒性,可以实现良好的跟踪效果并且无抖动。     

PHANTOM Omni机器人的自适应模糊滑模控制

针对PHANTOM Omni机器人的位置轨迹跟踪问题,采用了一种基于模糊逻辑的自适应模糊滑模控制方案。利用滑模控制中的切换函数作为输入,根据模糊系统的逼近能力设计控制器,并基于李雅谱诺夫方法设计自适应律对控制器所需参数进行实时调节。仿真中将其与传统的滑模控制进行了比较,仿真结果表明：自适应模糊滑模控制能使PHANTOM Omni机器人更好地实现期望的位置轨迹跟踪并有效地减轻抖振现象,从而证明了该方法在PHANTOM Omni机器人上实施的可行性。     

电液伺服系统的多滑模鲁棒自适应控制

针对一类参数与外负载非匹配不确定的非线性高阶系统,提出了一种基于逐步递推方法的多滑模鲁棒自适应控制策略.应用逐步递推的多滑模控制方法简化了高阶系统的控制问题,同时在自适应控制中加入鲁棒控制的方法,以消除不确定性对控制性能的影响.首先利用逐步递推方法与状态反馈精确线性化理论,得出确定系统的多滑模控制器设计方法;然后基于Lyapunov稳定性分析方法,给出不确定系统的参数自适应律,及鲁棒自适应控制器的设计方法.本文把该控制策略应用到电液伺服系统的位置跟踪控制中,仿真结果显示,该控制方法具有较强的鲁棒性及良好的跟踪效果.     

基于模糊滑模控制器的伺服跟踪控制研究

为了有效地消除精密机床伺服进给系统的参数变化和外部扰动对其跟踪性能的影响,将滑模控制引入其伺服跟踪控制.文章将模糊逻辑与滑模控制相结合提出了一种简捷的模糊滑模控制器设计的方法以减小滑模控制器的颤抖.实验结果表明采用该方法设计的模糊滑模控制器与离散准滑模控制器相比具有较强的鲁棒性和跟踪性能.最后将该控制器用于超精密机床伺服跟踪控制取得了良好的控制效果.     

无刷直流电动机积分反演模糊滑模控制

针对普通的无刷直流电动机控制策略受电动机本身因素影响,难以达到理想效果的问题,介绍了一种积分反演自适应滑模变结构控制和模糊控制相结合的控制器。该控制器在滑模面中加入积分项,实现了对速度信号的无静差跟踪,提高了系统的稳态精度;用模糊控制器来解决切换控制增益设定只能靠经验的问题;采用模糊控制算法对不确定性进行估计,有效地减小了滑模控制方法带来的抖振;为了进一步提高控制性能,重新设计了趋近律。仿真结果表明,该控制器能够大幅提升无刷直流电动机控制系统的性能。     

基于阿克曼公式模糊切换增益调节的滑模控制

针对一类具有不确定性和外部干扰的线性系统,基于模糊滑模控制原理,提出了一种基于阿克曼公式模糊切换增益调节的滑模控制器的设计方法;使用了一种新的方法设计滑模面,使系统在趋近切换平面的过程中始终跟踪理想的趋近过程,提高系统的位置跟踪精度;将该方法用于交流伺服控制系统位置控制器的设计,对该控制算法进行了稳定性分析,并进行了建模与仿真;通过选择合理的切换矢量C,使系统在趋近滑模平面的过程中始终跟踪理想的趋近过程,快速到达滑模平面;结果表明系统具有较强的鲁棒性和较快的收敛速度,验证了该方案的有效性.     

无刷直流电动机积分反演模糊滑模控制

针对普通的无刷直流电动机控制策略受电动机本身因素影响,难以达到理想效果的问题,介绍了一种积分反演自适应滑模变结构控制和模糊控制相结合的控制器。该控制器在滑模面中加入积分项,实现了对速度信号的无静差跟踪,提高了系统的稳态精度;用模糊控制器来解决切换控制增益设定只能靠经验的问题;采用模糊控制算法对不确定性进行估计,有效地减小了滑模控制方法带来的抖振;为了进一步提高控制性能,重新设计了趋近律。仿真结果表明,该控制器能够大幅提升无刷直流电动机控制系统的性能。     

Force Control of Robotic Manipulators Using a Fuzzy Predictive Approach

This paper proposes a force control strategy for robotic manipulators considering a non-rigid environment described by a nonlinear model. This approach uses a fuzzy predictive algorithm to generate, in an optimal way, the reference or virtual position to the classical impedance controller in order to apply a desired force profile on the environment. The main advantage of this control strategy is the possibility of including a nonlinear model of the environment in the controller design in a straightforward way, improving the global force control performance, especially in non-rigid environments. Moreover, in order to reduce the oscillations on the optimized reference position a fuzzy scaling machine is included on the force control strategy. The performance of the force control scheme is illustrated for a two degree-of-freedom PUMA 560 robot, which end-effector is forced to move along a flat surface located on the vertical plane. The simulation results obtained with the fuzzy control scheme reveal significant improvement in the force tracking performance, when compared to the impedance control with force tracking in non-rigid environments.     

基于神经滑模的柔性连杆机械手末端位置控制

：为了提高柔性机械手末端位置控制的鲁棒性和精度,提出了一种基于神经滑模的控制策略．首先采 用输入/输出线性化方法将动力学模型部分线性化,使之分成输入/输出子系统与内动态子系统．输入/输出子系统 采用神经滑模控制,内动态子系统采用状态反馈控制器镇定．随后,对控制系统内动态稳定性进行了分析,并在 两自由度柔性连杆机械手控制的仿真试验中得到了满意的结果．试验结果表明,在存在模型不确定性时,该控制 策略提高了控制系统的鲁棒性和控制精度．     

Robust trajectory tracking control for unmanned tail‐sitters in aggressive flight mode transitions

In this paper, the trajectory tracking control problem is investigated for a new typical tail‐sitter. A robust hierarchical control method is proposed to achieve aggressive flight mode transitions. The proposed control method results in a composite controller including a translational controller and a rotational controller to control the position and attitude respectively. Continuous aggressive flight mode transitions can be achieved without switching on the coordinate systems or the controller structures. It is proven that the tracking errors of the designed closed‐loop system can converge into a given neighborhood of the origin in a finite time. Simulation results show the effectiveness of the proposed control strategy.     

Adaptive Task-Space Control of Flexible-Joint Manipulators

This paper considers the motion control and compliance control problemsfor uncertain rigid-link, flexible-joint manipulators, and presents newadaptive task-space controllers as solutions to these problems. The motioncontrol strategy is simple and computationally efficient, requires littleinformation concerning either the manipulator or actuator/transmissionmodels, and ensures uniform boundedness of all signals and arbitrarilyaccurate task-space trajectory tracking. The proposed compliant motioncontrollers include an adaptive impedance control scheme, which isappropriate for tasks in which the dynamic character of theend-effector/environment interaction must be controlled, and an adaptiveposition/force controller, which is useful for those applications thatrequire independent control of end-effector position and contact force. Thecompliance control strategies retain the simplicity and model independenceof the trajectory tracking scheme upon which they are based, and are shownto ensure uniform boundedness of all signals and arbitrarily accuraterealization of the given compliance control objectives. The capabilities ofthe proposed control strategies are illustrated through computer simulationswith a robot manipulator possessing very flexible joints.     

基于滑模控制的独立光伏发电系统控制策略

针对独立运行的光伏发电系统,提出了基于滑模控制的最大功率跟踪(MPPT)策略;针对光伏微源输出功率随机性引起的逆变器输入侧直流母线电压波动,通过储能控制实现电压稳定;针对负载变化引起的系统输出电压波动,设计了系统输出电压电流双闭环控制器。通过MatLab/Simulink对提出控制策略进行了仿真验证。分析结果表明,所提出滑模控制策略可实现光伏电池的MPPT;储能控制策略可有效抑制光伏微源输出功率波动引起的直流母线电压波动;输出电压控制策略能稳定系统电压,确保安全可靠运行。     

Control System Design for an Upper-Limb Rehabilitation Robot

Control system implementation is one of the major difficulties in rehabilitation robot design. The purpose of our study is to present newly developed control strategies for an upper-limb rehabilitation robot. The Barrett WAM Arm manipulator is used as the main hardware platform for the functional recovery training of the past-stroke patient. Passive and active recovery training have been implemented on the WAM Arm. A fuzzy-based PD position control strategy is proposed for the passive recovery exercise to control the WAM Arm stably and smoothly to stretch the impaired limb to move along predefined trajectories. An adaptive impedance force controller is employed in the active motion mode in which a fuzzy logic regulator is used to adjust the desired impedance between the robot and impaired limb to generate adaptive force in agreement with the change of the impaired limb's muscle strength. In order to evaluate the change of the impaired limb's muscle power, the impaired limb's mechanical impedance parameters as an objective evaluation index is estimated online by using a recursive least-squares algorithm with an adaptive forgetting factor. Experimental results demonstrate the effectiveness and potential of the proposed control strategies.     

Type-2 Fuzzy Logic Control of a Flexible-Joint Manipulator

A type-2 fuzzy logic controller (FLC) is proposed in this article for robot manipulators with joint elasticity and structured and unstructured dynamical uncertainties. The proposed controller is based on a sliding mode control strategy. To enhance its real-time performance, simplified interval fuzzy sets are used. The efficiency of the control scheme is further enhanced by using computationally inexpensive input signals independently of the noisy torque and acceleration signals, and by adopting a trade off strategy between the manipulator’s position and the actuators’ internal stability. The controller is validated through a set of numerical experiments and by comparing it against its type-1 counterpart. It is shown through these experiments the higher performance of the type-2 FLC in compensating for larger magnitudes of uncertainties with severe nonlinearities. This work was partially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canadian Microelectronics Corporation (CMC).     

基于双重饱和函数的不确定机器人分散控制

针对具有集中不确定性的机器人轨迹跟踪问题,在传统PD控制基础上,引用双重饱和函数提出了一种不依赖于机器人动力学模型的基于多项式的分散控制结构。该控制器由PD控制器和针对参数和非参数不确定性的非线性补偿控制器构成。将滑模控制原理与饱和函数特性有机结合起来,减轻了一般滑模控制的抖振现象,有效抑制了执行器的饱和。通过李亚普诺夫定理,证明了控制系统的渐近稳定性和跟踪误差的有界性。仿真结果表明了所提出的控制策略的有效性。