输入输出测量噪声干扰下连续Hammerstein模型参数直接辨识

对输入输出测量噪声干扰下连续Hammerstein模型进行参数重组处理,得到线性微分方程。利用小波调制函数对该线性微分方程进行调制积分处理,得到等价的代数方程。在研究调制函数对输入输出测量噪声影响的基础上,提出用广义噪声模型来处理输入输出测量噪声并提出调制广义最小二乘算法来实现代数方程的无偏参数估计。最后利用奇异值分解(SVD)方法获得Hammerstein模型参数。数字仿真和工业应用实例验证了所提出方法的有效性和实用性。     

二自由度悬架质量辨识

车辆行驶过程中由于簧载质量及减振器温度的变化,悬架参数并不是固定不变的,在悬架的控制中需要对悬架参数进行辨识。首先建立二自由度悬架动力学模型,然后建立运动微分方程,在微分方程中加入滤波器得到仅包含加速度信号的输入输出方程。通过四分之一台架试验得到簧上簧下质量的加速度信号,基于递推最小二乘算法使用五个滤波器自然频率及五个滤波器阻尼比对悬架参数分别进行辨识,得到悬架辨识质量、辨识阻尼、最佳滤波器自然频率范围以及最佳滤波器阻尼比范围。通过加入滤波器,采用各加速度信号为输入,在悬架辨识中使得信号的采集更加简单。     

球面二自由度冗余驱动并联机器人系统动力学参数辨识及控制

以伺服电机驱动的球面2-DOF冗余驱动并联机器人为研究对象，首先，建立了机构惯性参数辨识模型，并规划了惯性参数辨识轨迹；其次，建立了机构运动副摩擦参数辨识模型和驱动系统的摩擦参数辨识模型，分别分析了二者的辨识原理，并规划了摩擦参数辨识轨迹；再次，通过辨识实验得到了机构惯性参数、机构转动副摩擦参数和驱动系统摩擦参数的辨识结果，利用辨识结果对原机构参数进行修正，获得了更为准确的机器人系统动力学模型，并通过轨迹测试实验，对辨识结果进行了验证；最后，制定了基于机器人系统动力学模型的前馈控制策略，与传统的机构运动学闭环控制策略进行实验对比，验证了该控制策略的可行性。     

一种并联机器人机电耦合多能域系统动力学参数辨识、控制及试验

以平面2-DOF冗余驱动并联机器人为研究对象,结合拉格朗日方程和键合图两种方法,建立了该机器人机电耦合多能域系统动力学模型。针对该机构特点,提出了一种将动力学模型线性化的待定系数法,通过该方法,经过严密的数学推导,得到了机电耦合多能域系统动力学模型的线性化形式,避免了传统的简化方法得到动力学模型线性化形式带来的误差。以五次多项式改进的傅里叶级数优化并联机构末端激励轨迹。搭建了动力学参数辨识试验平台,以加权最小二乘法对其机电耦合多能域系统的动力学参数进行了基于试验的辨识研究。所提的辨识策略不仅可以辨识出机器人机构本体的惯性参数与关节摩擦参数而且还可以辨识出电动机和减速机的等效转动惯量以及等效阻尼系数。设计了基于计算力矩的力位混合控制策略,并将辨识出的动力学参数应用到控制策略中,通过试验验证了机电耦合多能域系统动力学参数辨识的实用性与基于计算力矩的力位混合控制策略的有效性。     

基于快速动力学辨识的机器人力/位混合控制碰撞检测研究

针对机器人力/位混合控制时发生异常碰撞所导致的安全问题,提出一种基于快速动力学辨识的碰撞检测方案。首先,建立机器人快速动力学的辨识模型,基于拉格朗日法整理出机器人关节重力矩的最简三角函数回归矩阵,运用连续摩擦模型建模关节摩擦力;然后,采用最小二乘法分别辨识出机器人关节的重力矩最简参数集和连续摩擦模型参数集;最后,为验证提出方法的有效性,设计并完成机器人快速动力学辨识和碰撞检测实验。结果表明:提出的方法能够快速有效地辨识机器人的动力学参数,可实时检测机器人位置控制方向上4 N·m,力控制方向8 N·m以上的异常碰撞,有效保障操作人员和设备的安全,具有一定的工程参考价值。     

基于扩张状态观测器的迟滞非线性系统辨识

针对一类迟滞非线性系统提出一种参数辨识新方法。通过构造合适的周期输入信号,分析Bouc-Wen模型的积分特性,该特性在后续线性参数与迟滞参数辨识中起到重要作用。利用扩张状态观测器获得系统状态和等效扰动构造方程组,实现线性参数和非线性参数的分离辨识,所有参数通过线性方程组求解得到。通过数值仿真验证了方法的有效性。最后,方法应用于一类压电系统的迟滞非线性模型辨识,所得模型能够很好地反应实际系统的特性。     

液压挖掘机上车结构参数与液压缸摩擦力参数辨识

在液压挖掘机上车机械臂的动力学分析基础上,提出利用液压缸平稳低速运行时的动力学特性建立与摩擦力无关的挖掘机臂动力学模型,并运用该模型通过离线辨识确定臂的结构参数。基于经典摩擦力模型建立液压缸的辨识模型,通过在线辨识实验得到了液压缸的摩擦力参数,为深入研究液压挖掘机的动力学特性、建立可靠的系统仿真模型及实现臂运动的精确控制提供了依据。     

挖掘臂动力学参数与液压缸摩擦力参数辨识

建立了挖掘臂单关节动力学模型及液压缸驱动力模型,将模型中的未知动力学参数及非线性摩擦力参数线性化表示。利用测量的系统压力及角度信息,分别采用带遗忘因子的递推最小二乘法及递推增广最小二乘法对系统参数进行辨识。对辨识所得的两个模型进行仿真,与实际系统对比分析结果表明,辨识模型能很好地逼近实际系统。误差对比分析结果表明:递推增广最小二乘法比带遗忘因子的递推最小二乘法误差减小约28%,对系统噪声有更好的鲁棒性。     

移动质量简支梁耦合时变系统建模与实验设计

建立了移动质量简支梁耦合时变系统的动力学模型,通过数值仿真分析了移动质量速度及加速度对耦合时变系统模态参数的影响,得到移动质量诱导产生的附加阻尼。设计并搭建移动质量简支梁实验系统,通过参考实验得到实验系统的初始阻尼,并分别采用频域和时域模态参数辨识方法对质量块不同移动速度下的实验系统进行辨识。结果表明,所建立动力学模型能够对移动质量问题进行准确描述,实验系统可为时变结构动力学分析的理论研究提供实验支持,特别是对时变结构模态参数辨识方法进行实验验证。     

谐波驱动柔性臂系统耦合动力学建模及辨识

为研究谐波驱动的柔性臂系统耦合动力学建模问题,分别进行了谐波驱动模型的参数辨识和柔性机械臂振动特性的耦合动力学模型辨识。通过阶跃电流激励和低匀速转动实验辨识出了关节的库伦摩擦力,在伪随机二进制信号的激励下,辨识得到了包含驱动系统转动惯量和黏性摩擦因数的驱动传递函数模型,将其与实际结构系统比较验证了此模型的准确性。理论分析了振动耦合力矩和柔性臂应变输出电压之间的线性关系,辨识得到了从电机转动角位移到柔性臂应变电压输出之间的传递函数,其输出在时域和频域上都与实际系统比较吻合,说明了建立的传递函数模型对于实际系统的适用性。综合两个辨识得到传递函数模型,实现了对谐波驱动的柔性机械臂系统的耦合动力学建模。     

Dynamic analysis of a geometrical non-linear plate using the continuous-time system identification

The dynamic analysis of a plate with non-linearity due to large deformation was investigated in this study. There have been many theoretical and numerical analyses of the non-linear dynamic behavior of plates examining theoretically or numerically. The problem is how correctly an analytical model can represent the dynamic characteristics of the actual system. To address the issue, the continuous-time system identification technique was used to generate non-linear models, for stiffness and damping terms, and to explain the observed behaviors with single mode assumption after comparing experimental results with the numerical results of a linear plate model.     

Optimistic value based optimal control for uncertain linear singular systems and application to a dynamic input-output model

In this paper, optimal control problems for uncertain discrete-time singular systems and uncertain continuous-time singular systems are considered under optimistic value criterion. The above singular systems are assumed to be regular and impulse-free, and optimistic value method is employed to optimize uncertain objective functions. Firstly, based on Bellman's principle of optimality, a recurrence equation is presented for settling optimal control problems subject to uncertain discrete-time singular systems. Then, by applying the principle of optimality and uncertainty theory, an equation of optimality for an optimal control model subject to an uncertain continuous-time singular system is derived. The optimal control problem can be settled through solving the equation of optimality. Two numerical examples and a dynamic input-output model are given to show the effectiveness of the results obtained.     

System identification with measurement noise compensation based on polynomial modulating function for fractional-order systems with a known time-delay

This study presents a system identification method based on polynomial modulating function for fractional-order systems with a known time-delay involving input and output noises in the time domain. Based on the polynomial modulating function and fractional-order integration by parts, the identified fractional-order differential equation is transformed into an algebraic equation. By using the numerical integral formula, the least squares form for the system identification is obtained. In order to reduce the effect of noises existing in the input and output measurements, the compensation method for the input and output noises is also studied by introducing an auxiliary high-order fractional-order system in the revised identification algorithm. Finally, the effectiveness of the proposed algorithm is verified by the simulation result of an illustrative example and the experimental result of temperature identification for a thermal system.     

Dynamic compensation of load cell response: A time-varying approach

This paper presents a new method for dynamic compensation of the load cell response using linear time-varying continuous-time filter. Load cells have an oscillatory response which always needs time to settle down. Therefore, it is justified to search a technique for an effective improvement of the sensor response. The paper describes a theoretical implementation of the proposed time-varying filter, and suggests the implementation technique with the aid of which this kind of filter can be implemented in practice. Simulation results verifying the effectiveness of the proposed filter are presented and compared to the traditional time-invariant configuration.     

Identification of the Dynamics of a Moving Object with the Use of Neural Networks

A method for identification of the dynamics of a quadrotor-type vehicle is proposed. The method is based on the Elman recurrent neural network, which corresponds to the canonical form of a dynamic system in the space of states and does not require structural correction. The results of a numerical experiment reveal the convergence of the network learning algorithm with the use of an extended Kalman filter.     

System identification of two-dimensional continuous-time systems using wavelets as modulating functions

In this paper, parameter identification of two-dimensional continuous-time systems via two-dimensional modulating functions is proposed. In the proposed method, trigonometric functions and sine-cosine wavelets are used as modulating functions. By this, a partial differential equation on the finite-time intervals is converted into an algebraic equation linear in parameters. The parameters of the system can then be estimated using the least square algorithms. The underlying computations utilize a two-dimensional fast Fourier transform algorithm, without the need for estimating the unknown initial or boundary conditions, at the beginning of each finite-time interval. Numerical simulations are presented to show the effectiveness of the proposed algorithm.     

基于子系统的非线性时变系统辨识方法

针对非线性时变系统提出一种基于子系统的辨识方法，用于时变多自由度（multiple degree-of-freedom，简称MDOF）系统中非线性的定位和估计，并且无需关于系统的先验知识。所提出的新方法提供一个连续时间模型，MDOF系统按照自由度被分解为不同的子系统。设计正交化算法和误差减小率（error reduction ratio, 简称ERR），可以确定子系统中质量和自由度之间的线性及非线性连接的所有信息。在辨识过程中，时变参数的时间表达式可以由新方法准确给出。用一个3自由度（degree-of-freedom, 简称DOF）集中质量系统和一个机械臂结构的辨识过程为例，对所提出的方法进行验证。由于简单性及高效性，此方法将在实际工程中取得广泛的应用。     

A modified NARMAX model-based self-tuner with fault tolerance for unknown nonlinear stochastic hybrid systems with an input–output direct feed-through term

A modified nonlinear autoregressive moving average with exogenous inputs (NARMAX) model-based state-space self-tuner with fault tolerance is proposed in this paper for the unknown nonlinear stochastic hybrid system with a direct transmission matrix from input to output. Through the off-line observer/Kalman filter identification method, one has a good initial guess of modified NARMAX model to reduce the on-line system identification process time. Then, based on the modified NARMAX-based system identification, a corresponding adaptive digital control scheme is presented for the unknown continuous-time nonlinear system, with an input–output direct transmission term, which also has measurement and system noises and inaccessible system states. Besides, an effective state space self-turner with fault tolerance scheme is presented for the unknown multivariable stochastic system. A quantitative criterion is suggested by comparing the innovation process error estimated by the Kalman filter estimation algorithm, so that a weighting matrix resetting technique by adjusting and resetting the covariance matrices of parameter estimate obtained by the Kalman filter estimation algorithm is utilized to achieve the parameter estimation for faulty system recovery. Consequently, the proposed method can effectively cope with partially abrupt and/or gradual system faults and input failures by the fault detection.     

基于液压驱动控制夹具的模型设计

为了使夹具能够更精确地控制工件,采用液压来对夹具的位移量进行了精确的控制,先是利用有限元方法对一个固定部分和驱动系统的动态特性进行了研究,随后液压传动装置提供了自适应夹紧力,建立一个小型模型,可以准确地描述动态行为的一部分,这种方法是想获得部分简化模型,并融合于夹具模型中。经过比例控制和过滤器的动态补偿后,结果表明该位置反馈可以有效地加以利用,以减少不必要的工件位移,使生产效率可以提高。     

Impact of uncertainties in accelerometer modeling on the maximum values of absolute dynamic error

The paper considers the impact of uncertainties associated with estimated parameters of the accelerometer model on the maximum values of absolute dynamic error. Assessment of such impact constitutes a novelty in determination of the maximum values of absolute dynamic error.The parameter estimation method of the accelerometer mathematical model in the frequency domain and the procedure for calculation of the associated uncertainties under the current regulations, are discussed in detail in the second section of this paper.The procedures for determining the maximum values of absolute dynamic error generated at the output of an accelerometer, when the input signals are constrained in magnitude and both in magnitude and rate of change, are discussed in the third section. This dynamic error has been determined in relation to the standard represented by the 15-th order Butterworth filter. The possibilities of application of both the continuous and the discrete procedures of error calculation have also been presented. For the execution of numerical integration, the Romberg method has been applied.Based on theoretical consideration, the results of both the parameter estimation of the Endevco87 accelerometer and calculation of the corresponding uncertainties are presented in the fourth section.The fifth section is devoted to the presentation of the most important assumptions, which allow the determination of the maximum values of absolute dynamic error.An assessment of the impact of the uncertainties associated with the estimated parameters on the value of absolute error is discussed in the last section of this paper.The numerical calculations were executed in the MathCad14 program.