基于导纳控制的膝关节外骨骼摆动控制研究

针对膝关节外骨骼机械腿运动过程中对操作者的运动跟随问题,提出了一种基于导纳原理的等效惯量补偿控制方法.设计导纳控制器将外骨骼与操作者间的交互力矩转化为期望的运动轨迹;通过低通滤波加速度与惯量增益的乘积形成的闭环反馈实现等效惯量补偿;结合腿部肌肉表面肌电信号进行人体摆腿运动换向的预判,实施膝关节外骨骼机械腿的摆动控制,实验结果表明,膝关节外骨骼与受试者之间的关节角度相对误差为±12%,膝关节外骨骼机械腿对受试者的摆腿运动能实现较好的运动跟随.     

基于时间延时估计和自适应模糊滑模控制器的双机械臂协同阻抗控制

多机械臂的精准协同控制已成为当前机器人领域的研究难点,为实现双机械臂精准控制,通过建立双机械臂动力学模型,采用时间延时估计简化机械臂动力学模型,在保证控制系统稳定性的前提下,引入自适应模糊滑模控制器实现对估计误差的修正和补偿,设计基于时间延时估计和自适应模糊滑模控制的双机械臂协同阻抗控制器,实现双机械臂协同操作的末端轨迹控制以及接触力精准控制.最后,将该控制器应用于两台六自由度机械臂仿真平台,实现双臂夹取和搬运同一目标物体的操作,通过与其他控制器进行对比实验,表明所设计的控制器具有响应快、无抖震、精度高的特点.     

自适应模糊PID前馈补偿在机载挂飞摆扫转台控制中的应用

针对机载挂飞转台的摆扫速度控制问题,提出了一种利用模糊自适应PID技术进行前馈补偿的复合控制策略。首先根据实际应用提出摆扫转台的期望摆扫速度曲线,并对直流力矩电机驱动的摆扫转台进行了建模;然后根据扰动前馈补偿的控制原理,提出了模糊自适应PID前馈补偿方法,为摆扫转台的速度环设计了模糊PID控制器,并在此基础上设计了与之相适应的的自适应前馈补偿函数;最后进行了仿真结果验证。通过Matlab仿真结果表明,相对于模糊PID控制,所设计的模糊自适应PID前馈补偿控制器能有效的跟踪期望的转台摆扫速度,大幅地提高了在有稳定干扰和摆扫速度越变情况下的跟踪精度。     

非线性动态突变系统的多模型自适应执行器故障补偿设计

本文针对因多重不确定执行器故障而引起系统动态突变的非线性系统,设计了一种基于多模型切换的自适应执行器故障补偿控制策略,以提高系统应对动态突变的能力,同时实现不确定执行器故障的快速精确补偿.针对执行器故障模式的不确定性问题,采用基于多模型的参数估计方法,设计了自适应控制器组;基于最优性能指标函数,提出了一种控制切换机制,...     

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.     

双容液位系统鲁棒自适应容错控制

针对双容液位控制系统的泄漏等故障,通过线性化建模,研究了鲁棒自适应主动容错控制问题.首先在系统无故障正常运行情形,考虑建模误差和外界干扰等不确定性,利用不确定性上界自适应估计,设计了鲁棒自适应控制器.与此同时,对系统进行故障监控,设计了故障诊断滤波器,并利用对不确定性上界的估计终值提出了一种新的故障检测算法,进一步基于神经网络故障逼近,研究了一种修正控制律的自适应鲁棒容错控制器设计方法,该控制器通过补偿故障所带来的影响使闭环系统最终一致有界稳定.最后,通过仿真试验,验证了提出的方法的有效性.     

滑动及侧滑影响下的移动机器人轨迹跟踪控制

对受滑动及侧滑影响的移动机器人轨迹跟踪控制问题进行研究。在动力学部分,通过模糊系统逼近系统中的未知非线性,H_∞控制对滑动和侧滑干扰因素的补偿,利用Lyapunov函数推导出模糊参数的自适应律,设计出基于动力学的自适应模糊控制器。在运动学部分,设计逆运动学控制器,处理移动机器人实际位置与期望位置的误差,得到移动机器人运动的期望速度。将逆运动学控制器与自适应模糊控制器级联,并通过Lyapunov方法证明控制系统的稳定性。与自适应动力学控制器进行比较。仿真结果表明:在滑动及侧滑的影响下提出的策略具有较好的轨迹跟踪性能。     

小型无人机舵面故障的控制重构设计

小型无人机一般采用单余度设计,舵面故障后重构控制只能根据系统解析冗余进行设计,传统辨识方法复杂而且往往不能满足无人机重构控制的实时性。对由于舵面故障多样性引起的无人机参数大范围跳变进行分析,采用基于线性模型的方法离线重构控制器参数,实际飞行中在线自适应选择控制律,并针对存在大扰动的重构过程设计了动态补偿方案,保证无人机在故障发生后重构完成前的过渡过程的安全性。仿真实验表明,该方法能满足无人机舵面故障时控制律重构的实时性要求,保证过渡过程平稳,而且基于线性模型的控制器设计方法简便,工程实用性强。     

协作机械臂碰撞环境下的安全控制

针对人机协作过程中机械臂末端与操作者之间可能存在物理碰撞的问题,本文提出一种基于自适应导纳和滑模控制的机械臂安全控制方法.首先,采用基于广义动量的干扰观测器估计机械臂各关节和末端执行器上的干扰力.然后,设计一个双环控制结构,内环是基于干扰观测的双幂次趋近律滑模轨迹跟踪控制器,用以克服外界干扰的影响,达到期望的轨迹跟踪精度;外环是自适应导纳控制器,依据碰撞外力的大小和方向更新期望轨迹,以保证机械臂碰撞发生时的柔顺性和碰撞解除后迅速恢复工作状态的能力.最后,对所提算法进行仿真和实验验证.实验结果表明,协作机械臂碰撞环境下的安全控制算法能保证人机协作的安全性和机械臂工作的连续性,满足人机协作过程中的工作需求.     

可重构机械臂反演时延分散容错控制

针对存在模型参数不确定性的可重构机械臂系统执行器故障,提出一种基于反演设计与时延技术相结合的容错控制方法.该方法利用反演设计的基本思想,通过神经网络补偿子系统动力学模型中的参数不确定项和关联项.利用时延控制的逼近能力来补偿执行器的故障,使得故障发生时能及时实现容错控制.该方法具有不需要在线进行故障诊断的特点,仿真结果表明了所提出控制方法的有效性.     

An adaptive fuzzy design for fault-tolerant control of MIMO nonlinear uncertain systems

This paper presents a novel control method for accommodating actuator faults in a class of multiple-input multiple-output (MIMO) nonlinear uncertain systems.The designed control scheme can tolerate both the time-varying lock-in-place and loss of effectiveness actuator faults.In each subsystem of the considered MIMO system,the controller is obtained from a backstepping procedure;an adaptive fuzzy approximator with minimal learning parameterization is employed to approximate the package of unknown nonlinear functions in each design step.Additional control effort is taken to deal with the approximation error and external disturbance together.It is proven that the closed-loop stability and desired tracking performance can be guaranteed by the proposed control scheme.An example is used to show the effectiveness of the designed controller.     

含正反馈振动主动控制系统的混合自适应控制

对于存在结构正反馈的振动主动控制系统,传统的基于有限冲击响应的自适应前馈控制器设计方法难以同时保证控制系统稳定与良好的控制性能.本文在分析正反馈对前馈控制系统影响的基础上,基于无限冲击响应控制器设计模式,提出一种结合前馈自适应控制器和反馈自适应控制器的混合自适应振动主动控制方法.其中前馈自适应控制器采用参考传感器采集到的扰动相关信号作为参考信号,反馈自适应控制器通过构建扰动的估计量作为参考信号,控制器参数更新采用Landau参数递推算法.以一典型的具有固有正反馈性质的机械振动系统为控制对象,给出了该混合自适应控制算法的详细推导过程以及稳定性和收敛性分析过程,得到了算法稳定与收敛的严格正实条件以及相应放松严格正实条件的要求.在此基础上,通过构建实时振动主动控制实验平台,针对多种振动扰动开展对比实验分析.相关实验结果验证了本文提出的混合自适应振动主动控制方法的可行性和有效性.     

一类非参数不确定系统的自适应重复学习控制

本文针对一类非参数不确定系统提出一种全限幅自适应重复学习控制方法. 利用期望轨迹的周期特性, 构 造周期性期望控制输入, 并基于Lyapunov方法设计自适应重复学习控制器, 实现系统对周期性期望轨迹的高精度跟 踪, 且无需已知非参数不确定性的上界. 设计全限幅学习律估计未知的期望控制输入, 保证估计值被限制在指定的 界内. 同时, 通过构造完全平方式消除部分误差相关项, 控制器设计中可避免使用符号函数, 从而抑制控制器抖振问 题. 最后, 基于Lyapunov方法对误差收敛性进行了分析, 并通过仿真对比验证本文所提方法的有效性.     

Adaptive Controller Design for Unknown Systems Using Measured Data

This paper presents a measurement‐based adaptive control design approach for unknown systems working over a wide range of operating conditions. Traditional control design approaches usually require the availability of a mathematical model. However, it has been shown in many practical situations that, due to complex dynamics of physical systems, some simplifying assumptions are made for the derivation of mathematical models. Hence, controller design based on simplified models may result in degradation of the desired closed‐loop performance. Data‐based control design approaches can be viewed as an alternative approach to model‐based methods. Most data‐based control methods available in the literature aim to design controllers for unknown systems that operate only at a given operating point. However, the dynamical behavior of plants may change for different operating conditions, which makes the task of designing a controller that works over the entire range of operating conditions more challenging. In this paper, we address such a problem and propose to design adaptive controllers based on measured data. Such a proposed method is based on designing a set of measurement‐based controllers validated at a finite set of pre‐specified operating points. Then, the parameters of the adaptive controller are obtained by interpolating between the set of pre‐designed controller parameters to derive a gain‐scheduling controller. Moreover, low‐order adaptive controllers can be designed by simply selecting the desired controller structure. The efficacy of the proposed approach is experimentally validated through a practical application to control a heating system operated over a large range of flow rate.     

Implicit fault-tolerant control: application to induction motors

In this paper we propose an innovative way of dealing with the design of fault-tolerant control systems. We show how the nonlinear output regulation theory can be successfully adopted in order to design a regulator able to offset the effect of all possible faults which can occur and, in doing so, also to detect and isolate the occurred fault. The regulator is designed by embedding the (possible nonlinear) internal model of the fault. This idea is applied to the design of a fault-tolerant controller for induction motors in presence of both rotor and stator mechanical faults.     

Adaptive Active Fault Tolerant Control for Discrete‐Time Systems with Uncertainties

An active fault‐tolerant control scheme for discrete‐time systems is proposed to solve a difficult problem of fault‐tolerant controller design in the presence of partial loss of actuator effectiveness faults and structural parameter uncertainties assumed to be matched, using adaptive control techniques to help a faster and more accurate compensation of failure and uncertainty. An automated fault estimation scheme is developed together with an adaptive model parameter identification to obtain system parameter estimates. With these estimates fed back to the system, a model reference adaptive controller is constructed to achieve a desired tracking performance. Since parameters are obtained and updated online, the control system has an automatic failure compensation capability so as to recognize or reconfigure the control law in real time in response to failure indications. The stability and convergence follow from discrete‐time Lyapunov arguments. Simulation results from the linearized lateral dynamics model of the Boeing 747 airplane are presented to show the efficiency of proposed methods.     

Robust fault-tolerant controller design for linear time-invariant systems with actuator failures: an indirect adaptive method

In this paper, indirect adaptive state feedback control schemes are developed to solve the robust faulttolerant control (FTC) design problem of actuator fault and perturbation compensations for linear time-invariant systems. A more general and practical model of actuator faults is presented. While both eventual faults on actuators and perturbations are unknown, the adaptive schemes are addressed to estimate the lower and upper bounds of actuator-stuck faults and perturbations online, as well as to estimate control effectiveness on actuators. Thus, on the basis of the information from adaptive schemes, an adaptive robust state feed-back controller is designed to compensate the effects of faults and perturbations automatically. According to Lyapunov stability theory, it is shown that the robust adaptive closed-loop systems can be ensured to be asymptotically stable under the influence of actuator faults and bounded perturbations. An example is provided to further illustrate the fault compensation effectiveness.     

带有执行器故障的网络控制系统的自适应容错H∞控制

针对带有执行器故障的网络控制系统, 提出了一种自适应容错控制方法. 首先基于最近提出的一种新的网络诱导时滞模型, 设计了状态反馈形式的自适应容错控制器. 然后以线性矩阵不等式的形式给出了控制器存在的充分条件. 该条件不仅保证了系统在执行器故障和正常情形下均能达到稳定, 而且使得其H∞性能最优. 最后通过一个数值例子证明了所提方法的有效性.     

Robust fault-tolerant controller design for linear time-invariant systems with actuator failures: an indirect adaptive method

In this paper, indirect adaptive state feedback control schemes are developed to solve the robust faulttolerant control (FTC) design problem of actuator fault and perturbation compensations for linear time-invariant systems. A more general and practical model of actuator faults is presented. While both eventual faults on actuators and perturbations are unknown, the adaptive schemes are addressed to estimate the lower and upper bounds of actuator-stuck faults and perturbations online, as well as to estimate control effectiveness on actuators. Thus, on the basis of the information from adaptive schemes, an adaptive robust state feed-back controller is designed to compensate the effects of faults and perturbations automatically. According to Lyapunov stability theory, it is shown that the robust adaptive closed-loop systems can be ensured to be asymptotically stable under the influence of actuator faults and bounded perturbations. An example is provided to further illustrate the fault compensation effectiveness.     

An adaptive integral sliding mode FTC scheme for dissimilar redundant actuation system of civil aircraft

ABSTRACT

This paper proposed a new adaptive integral sliding mode FTC scheme to deal with the actuator faults and failure. The scheme combines integral sliding mode control, control allocation scheme and adaptive strategy. The unknown actuator faults are handled by adaptive modulation gain of nonlinear ISMC law. To cope with complete failure, control allocation scheme is integrated with the baseline controller to provide tolerance. The proposed strategy relies on the estimate of actuator effectiveness. Therefore, an adaptive sliding mode observer based fault reconstruction scheme is proposed in this paper. The proposed scheme is implemented on dissimilar redundant actuation system driven by hydraulic and electro-hydraulic actuators. In nominal and faulty conditions, both actuators are contributing to achieving the desired control surface deflection. However, when the actuator failure occurs, the control signals are reallocated to the redundant actuator. The problem of dynamics mismatch is addressed using fractional order controller designed in an inner loop. The comparison with the existing literature is also conducted in the simulation to validate the dominant performance.