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。     

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.     

高速高精运动平台模型参数最小二乘辨识研究

针对高速高精运动控制对象模型参数辨识的问题,对辨识对象模型、最小二乘辨识算法和滤波器等内容进行了研究,提出了一种基于滤波器的最小二乘线性回归方程的辨识算法,即加入一个稳定的二阶传递函数,对系统输入输出数据进行了滤波处理,使辨识算法在噪声环境下能够减小失真且运行稳定.仿真与实验结果表明,最小二乘在有噪声的闭环运动控制系统中的辨识结果不收敛且失真,而加入滤波器的最小二乘算法能显著提高控制系统的稳定性及精确度,且满足其高速高精的要求.     

An approach to design controllers for MIMO fractional-order plants based on parameter optimization algorithm

The parameter optimization method for multivariable systems is extended to the controller design problems for multiple input multiple output (MIMO) square fractional-order plants. The algorithm can be applied to search for the optimal parameters of integer-order controllers for fractional-order plants with or without time delays. Two examples are given to present the controller design procedures for MIMO fractional-order systems. Simulation studies show that the integer-order controllers designed are robust to plant gain variations.     

Function projective synchronization between integer-order and stochastic fractional-order nonlinear systems

In this paper, the function projective synchronization between integer-order and stochastic fractional-order nonlinear systems is investigated. Firstly, according to the stability theory of fractional-order systems and tracking control, a controller is designed. At the same time, based on the orthogonal polynomial approximation, the method of transforming stochastic error system into an equivalent deterministic system is given. Thus, the stability of the stochastic error system can be analyzed through its equivalent deterministic one. Finally, to demonstrate the effectiveness of the proposed scheme, the function projective synchronization between integer-order Lorenz system and stochastic fractional-order Chen system is studied.     

基于调制函数法的线性连续动力学系统参数模型估计

提出了构造单分辨和多分辨高斯调制函数的新思路。基于数字积分原理,推导了调制积分滤波器的结构,得到直接以线性连续系统模型参数表示的等价辨识模型。利用离散模型辨识的研究成果,建立了连续动力学系统模型参数直接估计的最小二乘法和辅助变量法。研究了调制滤波器参数与辨识精度的关系,并以此得到调制函数参数的设计依据。成功辨识了某轧机液压AGC压力闭环系统的连续动力学参数模型,验证了方法的正确性。     

Control of a DC motor using algebraic derivative estimation with real time experiments

This paper presents an experimental control scheme for DC motors which combines an overlapping implementation of the algebraic derivative estimation method and a disturbance estimator based on the aforementioned algebraic derivative method. The methodology only requires the measurement of the angular position of the motor and the voltage input to the motor. The main advantages of the proposed approach are: it is independent of the motor’s initial conditions, the methodology is robust to Coulomb friction effects, it does not require any statistical knowledge of the noises that corrupt the data, the derivative estimation process does not require initial conditions or dependence between the system input and output, and the algorithm is computed on-line and in real time. The effectiveness of the proposed controller has been verified by means of computer simulations and it has also been experimentally implemented on a laboratory prototype with excellent results in both, stabilization and trajectory tracking tasks.     

MIMO随机加正弦振动试验J-阻抗复合控制算法

以多输入多输出(multiple-input multiple-output,简称MIMO)随机加正弦混合试验控制系统中信号分离方法、控制策略及试验为研究对象,提出了针对混合型振动试验的分离控制策略,采用相关积分法分离混合信号中的正弦信号与随机信号成分。推导了MIMO线性随机振动系统的反馈控制方程,提出了控制目标针对性更强的Jacobi控制算法。分析了多点正弦振动试验中存在的过修正问题,基于压缩因子修正提出阻抗控制方法,并将其与Jacobi算法共同应用于混合试验系统。以悬臂梁为试验对象,开展J-阻抗复合控制算法在两输入两输出随机加正弦混合试验系统中应用验证。结果表明,算法可以有效地抑制超标谱线,并将结果控制在容差带内,为混合振动试验控制提供有力的理论支撑。     

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.     

基于指数窗截取递推最小二乘法的齿轮啮合刚度辨识算法研究

齿轮在机械传动系统中有着广泛应用,由于齿轮啮合过程中参与啮合的轮齿对数周期变化,因此,齿轮啮合刚度为时变参数,在啮合时会产生啮合振动。当齿轮副出现齿根裂纹时,啮合刚度会减小,齿轮啮合产生的系统振动响应也发生改变,通过振动响应辨识齿轮啮合刚度能够监测齿轮副的健康状态。针对齿轮啮合刚度的时变特征,提出了基于指数窗截取递推最小二乘(Exponential window recursive least square,EWRLS)算法和振动信号瞬时频率的齿轮啮合刚度辨识方法。进行啮合刚度辨识时,EWRLS算法将输入、输出齿轮的转速曲线分别作为辨识输入信号和观测信号,使用指数窗函数进行数据截断,使用递推最小二乘算法估计系统参数。为了计算输入、输出齿轮的转速曲线,使用经验模态分解(Empirical mode decomposition,EMD)方法将振动信号分解为具有不同变化频率的本征模态函数(Intrinsic mode function,IMF),并根据IMF的平均频率重构输入、输出齿轮的特征信号。通过Hilbert变换计算特征信号的瞬时频率曲线,从而获得各齿轮的转速曲线。使用仿真和实测信号对算法进行验证,结果表明,EWRLS算法能够辨识齿轮副的时变啮合刚度。     

基于时域的分数阶PID预测函数励磁控制器

为了提高电力系统的稳定性,将分数阶PID算法与预测函数算法相结合,提出了一种新型的基于时域的分数阶PID预测函数励磁控制器的设计方法.该算法不仅具有分数阶PID静态误差小、上升速度快以及预测函数算法超调小、调节时间短的优点,还克服了分数阶PID调节时间长和预测函数算法静态误差大的缺点,同时还比预测函数算法多出了5个可调参数,设计更加灵活.研究结果表明该算法不仅能有效地解决机端电压偏移问题,还能有效地抑制电网低频振荡,为电力系统稳定性控制提供了一种新型有效的方法.     

柔性结构的多输入多输出运动系统辨识方法

柔性结构的多输入多输出(Multiple input multiple output,MIMO)运动系统的辨识方法是一个具有理论研究和工程应用价值的问题。随着运动系统结构设计、控制性能等要求不断提高,过去视为刚体的MIMO运动系统的柔性动力学特征将越来越显著,成为限制系统性能的重要因素。在辨识试验获得频域非参数模型基础上,提出一种柔性结构的MIMO运动系统辨识方法,基于正交多项式的总体参数曲线拟合得到同分母的MIMO传递函数矩阵,利用模态叠加原理以及奇异值分解(Singular value decomposition,SVD)原理得到系统的状态空间模型。此方法被应用于光刻机工件台这一典型的带有柔性动力学特征的MIMO运动系统。获得的MIMO状态空间模型具有频域辨识模型同等的辨识精度,证明了提出的辨识方法的有效性。所获得的模型满足用于综合控制设计的要求。     

Incorporation of fractional-order dynamics into an existing PI/PID DC motor control loop

The problem of changing the dynamics of an existing DC motor control system without the need of making internal changes is considered in the paper. In particular, this paper presents a method for incorporating fractional-order dynamics in an existing DC motor control system with internal PI or PID controller, through the addition of an external controller into the system and by tapping its original input and output signals. Experimental results based on the control of a real test plant from MATLAB/Simulink environment are presented, indicating the validity of the proposed approach.     

基于闭环自适应辨识的速度环PI参数自整定

针对永磁同步电机伺服系统速度环比例积分（PI）参数整定过程中需要反复调节、效率低等问题,提出了一种基于闭环自适应卡尔曼滤波（AKF）系统辨识的伺服系统速度环PI参数自整定方法。首先根据输入信号激励速度闭环系统,分析不同频率激励作用下闭环辨识序列的信噪比与实际输出,然后引入AKF算法辨识闭环被控对象的离散模型,最后通过遗传算法仿真搜索最优速度环PI参数。仿真与实验结果表明：该算法能有效抑制量测噪声等扰动对系统辨识精度的影响,辨识结果能够反映实际系统的动态输入输出特性,优化后的速度环具有优良的响应性能和较高的精度,便于实际工业应用。     

聚吡咯机械传感器传感特性研究

针对聚吡咯在传感器方面的应用问题,对其作为机械传感器时的传感特性进行了研究,提出了一种在施加外部静态偏转的情况下,采集PPy机械传感器传感输出的微弱电信号的测量方法,并建立了具有屏蔽外界干扰功能的输出信号测量系统。对传感器施加由小变大和由大变小两组偏转位移,在屏蔽外界干扰的条件下依次测得了对应的传感输出信号,通过分析传感输出电压与输入偏转位移之间的关系,得到了完整的聚吡咯传感输出去/回程特性曲线方程。研究结果表明,该测量系统能够实现测量PPy机械传感器在静态偏转的状态下所输出的电压信号,且传感输出与输入变化规律基本一致;由得到的特性曲线方程可以发现,在其传感过程中存在非线性迟滞现象,该发现可以为聚吡咯用于制作机械传感器提供一定的实验依据和参考。     

A fast iterative recursive least squares algorithm for Wiener model identification of highly nonlinear systems

In this paper, an online identification algorithm is presented for nonlinear systems in the presence of output colored noise. The proposed method is based on extended recursive least squares (ERLS) algorithm, where the identified system is in polynomial Wiener form. To this end, an unknown intermediate signal is estimated by using an inner iterative algorithm. The iterative recursive algorithm adaptively modifies the vector of parameters of the presented Wiener model when the system parameters vary. In addition, to increase the robustness of the proposed method against variations, a robust RLS algorithm is applied to the model. Simulation results are provided to show the effectiveness of the proposed approach. Results confirm that the proposed method has fast convergence rate with robust characteristics, which increases the efficiency of the proposed model and identification approach. For instance, the FIT criterion will be achieved 92% in CSTR process where about 400 data is used.     

基于RBF神经网络的风力发电机组系统辨识研究

Aiming at the problems of difficult to establish the accurate mathematical model of wind power generation,identification of the wind turbine based on RBF neural network was presented. The dynamic process of the torque loop and the pitch loop was simulated,RBF neural network algorithm was adopted to identification the torque loop and the pitch loop. RBF basis function was adopted to form space. If the hidden layer RBF parameters was determined, the nonlinear mapping relation was determined. The output layer was the hidden layer nodes output linear weighted summation. The result indicate that identification of torque loop,the input is torque,the output is speed,the torque loop error rate is about 1 %. Identification of pitch loop,the input is pitch angle,the output is speed,the pitch loop eror rate is about 3%. The pitch loop is a very complicated nonlinear model,the model structure is influenced by many aspects,identification result error is bigger than the torque loop identification error,but the error rate is allowed. The algorithm has higher precision and efficiency. [ABSTRACT FROM AUTHOR]     

制粉系统球磨机的模型算法解耦控制

针对制粉系统球磨机的多变量强耦合特性，提出模型算法预测控制的解耦设计方法。将球磨机系统分解为三个多输入单输出系统，用模型算法控制原理设计控制器，通过求解三元一次矩阵方程组，实现了多步预测的解耦控制。对球磨机系统的仿真结果表明了所给算法的有效性。     

基于粒子群算法的机械平台自动升降轨迹控制方法

机械平台升降轨迹受到多个关节、连杆运动参量的影响,很难对其进行精准控制,因此提出基于粒子群算法的机械平台自动升降轨迹控制方法。分析机械平台结构与基本参数,构建机械平台升降轨迹模型,采用多项式插值方法插值处理机械平台升降轨迹,获得轨迹插值方程,确立升降轨迹控制函数。采用粒子群算法求解升降轨迹控制函数,算法输出结果即为升降轨迹最佳控制量,从而实现机械平台自动升降轨迹控制。实验结果表明,该方法获取最佳控制量迭代次数较少,升降轨迹控制效果较好,应用性能较佳。     

正交基函数多项式实时拟合 在轴角编码器测速中的应用

提出了一种基于正交基函数的多项式实时拟合方法,并应用于轴角编码器测速,解决了常规算法中拟合多项式阶数大于3阶时法方程组容易出现病态,进而使测速精度降低的问题。光电跟踪测量设备地面目标跟踪实验表明,该算法通过对拟合处理后的角度值进行微分运算得到角速率,能有效地降低编码器角度输出中随机误差对测速的影响。在典型实验条件下,与采用同阶拟合多项式的常规方法进行了比对,前者的测速误差标准偏差为0.013 43°/s,后者为0.028 15°/s,采用本算法提高了编码器的测速精度,适合在工程上应用。