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1.
曹伟  孙明 《控制理论与应用》2012,29(11):1495-1500
针对一类非线性离散时变系统的故障诊断问题,提出了一种新的故障检测与估计算法.该算法在选取的优化时域内,利用残差信号通过迭代学习方法调整引入的虚拟故障,并利用实际输出和故障跟踪估计器输出向量空间的角度关系,来修正虚拟故障的迭代学习律,以此来加快算法的收敛速度.该算法不仅能够实现不同类型故障信号的检测与估计,而且还充分利用了估计器输出信号中的新信息,使得算法的收敛速度得到明显提高.最后仿真结果验证了该方法的有效性.  相似文献   

2.
针对迭代学习算法在非线性系统故障检测与估计过程中存在估计误差较大和收敛速度较慢等不足的问题,提出了一种基于龙格–库塔故障估计观测器模型的自适应迭代学习算法,有效降低了故障估计误差;并引入H∞性能指标,提高了故障估计观测器的收敛速度.该算法首先设计故障检测观测器对故障进行检测,然后设计故障估计观测器,并将自适应算法与迭代学习策略相结合,使得估计故障逐渐逼近真实故障,从而实现对非线性系统中多种常见故障的精确检测与估计.最后,通过机械臂旋转关节驱动电机的执行器故障仿真验证了所提算法的有效性.  相似文献   

3.
基于迭代学习的离散线性时变系统故障诊断   总被引:1,自引:0,他引:1  
曹伟  丛望  李金  郭媛 《控制与决策》2013,28(1):137-140
针对一类离散线性时变系统的故障诊断问题,提出一种新的故障检测与估计算法.该算法通过引入虚拟故障构建离散故障跟踪估计器,在选取的优化时域内,利用估计器输出和系统实际输出产生的残差信号,采用迭代学习算法来调节虚拟故障,使虚拟故障逼近系统中实际发生的故障,从而达到对系统故障诊断的目的.该方法不仅能检测出系统不同类型的故障,还可以实现对故障信号的精确估计.仿真结果验证了所提出方法的有效性.  相似文献   

4.
针对一类存在执行器和传感器故障的非线性系统,提出基于滤波器的故障重构方法。为了使算法同时适用于状态和输出端,通过由系统方程构造新状态方程对系统作扩展变换,将原系统输出端非线性和故障转换到扩展系统的状态方程,在此基础上设计故障诊断滤波器,采用迭代学习调节算法更新虚拟故障使之逼近实际故障。该算法可以检测和估计系统故障,并且对不同类型故障具有一定的适应性。在单关节机器人模型上进行仿真实验,实验结果验证了所提出算法的可行性和有效性。  相似文献   

5.
针对一类带有不确定参数项的线性重复系统间歇性故障估计问题, 本文提出一种基于迭代学习的故障估计算法.该算法通过设计基于迭代学习的故障估计器和状态观测器, 构造李雅普诺夫方程和优化函数证明该算法的鲁棒性和收敛性, 并通过线性矩阵不等式, 求解出算法中的观测器增益矩阵和迭代学习参数矩阵.区别于其他观测器方法, 本文中的方法利用上一次基于迭代学习观测器输出和系统实际输出产生的残差信号, 对本次的故障信号进行跟踪估计, 从而准确地估计出故障的幅值和形状.仿真结果说明了该算法的有效性和准确性.  相似文献   

6.
基于故障跟踪估计器的非线性时滞系统故障诊断   总被引:4,自引:0,他引:4  
提出一种可有效检测和估计一类非线性时滞系统故障的故障跟踪估计器.根据预测控制和迭代学习控制的思想,在所选取的优化时域长度内,通过迭代算法调节故障跟踪估计器中的可调参数,使之逼近系统中实际发生的故障.与以往基于观测器的故障诊断方法不同的是,故障跟踪估计器可同时检测和估计系统中发生的故障,而且针对不同类型的故障亦有很好的适应性.仿真结果表明了所提出算法的可行性和有效性.  相似文献   

7.

提出一种可有效检测和估计一类非线性时滞系统故障的故障跟踪估计器.根据预测控制和迭代学习控制的思想,在所选取的优化时域长度内,通过迭代算法调节故障跟踪估计器中的可调参数,使之逼近系统中实际发生的故障.与以往基于观测器的故障诊断方法不同的是,故障跟踪估计器可同时检测和估计系统中发生的故障,而且针对不同类型的故障亦有很好的适应性.仿真结果表明了所提出算法的可行性和有效性.

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8.
姚利娜  薛霄  任景莉 《计算机仿真》2009,26(6):168-170,174
对一般的非线性系统提出了一种新的主动容错控制方法.系统正常工作时,采用基于迭代学习观测器的输出反馈控制策略,控制器为迭代学习观测器的状态和调节参数的函数,此输出反馈控制器能良好地镇定该非线性系统.当系统发生故障后,进行控制器重组,在调节参数的自适应调节律中引入了故障估计的信息,使得系统发生故障后包含故障估计信息的重组控制器仍然能使系统稳定,实现了非线性系统的主动容错控制.计算机模拟显示所提出算法的有效性.  相似文献   

9.
即时学习算法在非线性系统迭代学习控制中的应用   总被引:4,自引:1,他引:4       下载免费PDF全文
孙维  王伟  朱瑞军 《控制与决策》2003,18(3):263-266
运用即时学习算法来解决一类非线性系统的迭代学习控制初值问题。对于任何类型的迭代学习控制算法,即时学习算法都能有效地估计初始控制量,减小了初始输出误差,加快了算法的收敛速度,使得经过有限次迭代后系统输出能严格跟踪理想信号。对机器人系统的仿真结果表明了该方法的有效性。  相似文献   

10.
针对一类满足Lipschitz条件的多输入多输出非线性可逆系统执行器故障问题,提出了一种基于迭代学习观测器的逆系统内模故障调节方法。引入PD型迭代学习策略,设计了迭代学习故障诊断观测器,用于对执行器未知时变故障进行快速、准确估计。根据故障估计值,结合逆系统方法对逆模型进行补偿,使得补偿后的逆模型与非线性被控对象串联仍为伪线性系统;再结合内模控制实现了伪线性系统的容错控制。最后,通过仿真算例验证了该方案的有效性。  相似文献   

11.
This paper deals with the fault estimation problem for a class of linear time‐delay systems with intermittent fault and measurement noise. Different from existing observer‐based fault estimation schemes, in the proposed design, an iterative learning observer is constructed by using the integrated errors composed of state predictive error and tracking error in the previous iteration. First of all, Lyapunov function including the information of time delay is proposed to guarantee the convergence of system output. Subsequently, a novel fault estimation law based on iterative learning scheme is presented to estimate the size and shape of various fault signals. Upon system output convergence analysis, we proposed an optimal function to select appropriate learning gain matrixes such that tracking error converges to zero, simultaneously to ensure the robustness of the proposed iterative learning observer which is influenced by measurement noise. Note that, an improved sufficient condition for the existence of such an estimator is established in terms of the linear matrix inequality (LMI) by the Schur complements and Young relation. In addition, the results are both suit for the systems with time‐varying delay and the systems with constant delay. Finally, three numerical examples are given to illustrate the effectiveness of the proposed methods and two comparability examples are provided to prove the superiority of the algorithm.  相似文献   

12.
For a class of non-uniform output sampling hybrid system with actuator faults and bounded disturbances, an iterative learning fault diagnosis algorithm is proposed. Firstly, in order to measure the impact of fault on system between every consecutive output sampling instants, the actual fault function is transformed to obtain an equivalent fault model by using the integral mean value theorem, then the non-uniform sampling hybrid system is converted to continuous systems with timevarying delay based on the output delay method. Afterwards, an observer-based fault diagnosis filter with virtual fault is designed to estimate the equivalent fault, and the iterative learning regulation algorithm is chosen to update the virtual fault repeatedly to make it approximate the actual equivalent fault after some iterative learning trials, so the algorithm can detect and estimate the system faults adaptively. Simulation results of an electro-mechanical control system model with different types of faults illustrate the feasibility and effectiveness of this algorithm.   相似文献   

13.
In this paper, the extension of the Bayesian framework for sensor fault detection of nonlinear systems proposed in [25] is studied utilizing particle filtering and the expectation maximization (EM) algorithm, in which the fault probability is calculated. The proposed algorithm is implemented on a wind turbine benchmark model to detect drivetrain sensor faults, which are one of the most addressed and likely faults in offshore wind turbines. The fault probability estimation effectively eliminates the need for installing identical redundant sensors. Indeed, because of the use of the unknown wind speed estimator, the residual signal, constructed based on the drivetrain estimated states, is not able to clearly signify the fault periods, a situation in which the fault probability accurately does this task. Also, using the proposed algorithm, the fault size for each sensor is estimated via a one‐step calculation, which decreases the complexity of this algorithm. The fault identification is performed using the recursive least square method and two other modifications, including exponentially weighted and windowed estimates. Additionally, in the fault accommodation step, the concept of a virtual sensor is used to remove the need for reconfiguring the current controller, which reduces complexity and expense. In the simulation section, using a real measured wind speed for two different fault scenarios, the proposed algorithm is evaluated and finally, conclusions are stated.  相似文献   

14.

针对一类执行器故障不确定离散重复过程, 提出一种有限频率范围的迭代学习容错控制算法. 通过定义故障系数矩阵和输出跟踪系统的等价二维模型, 沿故障系统的时间轴和批次轴设计迭代学习被动容错控制器, 以线性矩阵不等式形式分别给出基于KYP 引理的全频、分频区域重复控制系统稳定的充分必要条件, 同时保证故障系统在时域和频域范围内的容错性能. 最后, 以重复注塑过程的注射速度控制仿真验证了所提出分频控制算法的有效性.

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15.
曹伟  乔金杰  孙明 《控制与决策》2023,38(4):929-934
为了解决非仿射非线性多智能体系统在给定时间区间上一致性完全跟踪问题,基于迭代学习控制方法设计一种分布式一致性跟踪控制算法.首先,由引入的虚拟领导者与所有跟随者组成多智能体系统的通信拓扑,其中虚拟领导者的作用是提供期望轨迹.然后,在只有部分跟随者能够获得领导者信息的条件下,利用每个跟随者及其邻居的跟踪误差构造每个跟随者的迭代学习一致性跟踪控制器.同时采用中值定理将非仿射非线性多智能体系统转化仿射形式,并基于压缩映射方法证明所提算法的收敛性,给出算法的收敛条件.理论分析表明,在智能体的非线性函数未知情况下,利用所提算法可以使非仿射非线性多智能体系统在给定时间区间上随迭代次数增加逐次实现一致性完全跟踪.最后,通过仿真算例进一步验证所提算法的有效性.  相似文献   

16.
This paper deals with the intermittent fault estimation problem for a class of nonlinear time‐delay systems with measurement noise. The time delays are assumed to occur in state vector, nonlinear term as well as output vector, thus reflecting the time delays influence in reality more closely. The aim of the problem is to estimate the intermittent fault by using iterative learning scheme, with the property of index, hence attenuating the influence from measurement noise. Different from existing fault estimating schemes, the state error information and fault estimating information in the previous iteration are used in the current iteration to improve the estimating results. The stability and convergence of iterative learning observer and uniform boundedness of dynamic error system are achieved by using Lyapunov function and optimal function design. Simultaneously, an improved sufficient condition for the existence of such an estimator is established in terms of the linear matrix inequality by the Schur complements and Young relations. Furthermore, the results are both suited for the systems with time‐varying delay and the systems with constant delay. Finally, two numerical examples are proposed to illustrate the effectiveness of the proposed method, and a comparability example is presented to demonstrate its superiority. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   

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