Adaptive disturbance estimation and cancelation for ships under thruster saturation

This work addresses the problem of disturbance estimation and cancelation for ships with ocean disturbances and modeling uncertainties under thruster saturation effects. The ocean disturbances are expressed as the multiple sinusoidal disturbances with unknown frequencies, amplitudes, and phases. By means of a parametric exogenous system and a canonical model with unknown disturbances being inputs, the ocean disturbances are represented as the multivariate regression model with unavailable regressors and regression parameters. An observer is employed to provide the regressor estimation, such that the disturbance estimation and cancelation are converted to the adaptive control problem. The robust control term with the adaptive technique attenuates the modeling uncertainties. The thruster saturation effects are reduced using the state vectors from the auxiliary dynamic filter to online correct the control errors. The ship disturbance cancelation controller is derived via the adaptive backstepping. The closed‐loop tracking system is guaranteed to be uniformly ultimately stable and the ship's position and heading navigate along with desired trajectories. The proposed adaptive control scheme is validated by simulations with comparisons on a 1:70 scaled model ship CyberShip II in different cases.     

Design of Asymptotically Convergent Frequency Estimator Using Contraction Theory

The problem of estimating unknown frequencies of a sinusoidal signal simultaneously is a classical problem in signal and system theory. Many approaches and algorithms are proposed in literature to develop estimators for a measurable sinusoidal signal having multiple sinusoids with unknown amplitudes, frequencies and phases. In this work, an asymptotically convergent frequency estimator is given for estimation of n-unknown frequencies of a measurable sinusoidal signal. The contraction theory approach is adopted to show the asymptotic convergence of the proposed estimator in quite a simplified manner. Approach given here exploits the results of contraction theory related to semi-contracting systems. The nonlinear estimator based on dynamic system approach, guarantees global boundedness and convergence of the state and frequency estimation for all initial conditions and frequency values. It further ensures simultaneous globally convergent estimation of states and frequencies of a sinusoid involving multiple frequencies. Numerical simulations are presented for different combinations of frequencies to justify the claim.     

On Adaptive Output Feedback Controf Robotic Manipulators with Online Disturbance Estimation

The problem of disturbance estimation and compensation for adaptive output feedback type controllers are investigated. Specifically two adaptive output feedback controllers designed for robotic manipulators are extended to compensate external disturbances which are common in robotic applications with repetitive task. The uncertain disturbance term in the robot dynamics is modeled as a fixed term plus a combination of sinusoidal signals. The overall stability and convergence of the tracking error for both controllers is ensured via Lyapunov based analysis. Extensive simulation studies are presented to illustrate the feasibility of the proposed method.     

Adaptive maximum windowed likelihood multicomponent AM-FM signal decomposition

Considering a real signal as the sum of a number of sinusoidal signals in the presence of additive noise, maximum windowed likelihood (MWL) criterion is introduced and applied to construct an adaptive algorithm in order to estimate the amplitude and frequency of these components. The amplitudes, phases and frequencies are assumed to be slowly time varying. Employing MWL an adaptive algorithm is obtained in two steps. First, assuming some initial values for the frequency of each component, a closed form is derived to estimate the amplitudes. Then, the gradient of MWL is used to adaptively track the frequencies, using the latter values of amplitudes. The proposed algorithm has a parallel structure in which each branch estimates parameters of one of the components. The proposed multicomponent phase locked loop (MPLL) algorithm is implemented employing low complexity blocks. It is adjustable to be used in different conditions. The mean squared error of the algorithm is studied to analyze the effect of the window length and type and the step size. Simulations have been conducted to illustrate the efficiency and the performance of the algorithm in different conditions including: the effect of the initialization, the frequency resolution, for chirp components, for components during frequency crossover and for speech signals. Simulations illustrate that the method efficiently tracks slowly time-varying components of the signals such as voiced speech segments.     

自适应Kalman滤波修复六维力传感器下E膜模型误差

为减小动载环境下,噪声信号对六维力传感器测量精度的影响,同时解决因传感器的简化模型误差较大,导致标准Kalman滤波无法获取最优估计的问题,提出一种双因子自适应Kalman滤波算法。算法根据正弦激励力响应和应变之间的关系,建立了下E型膜有色噪声增广状态模型。在标准Kalman滤波的基础上,分析了两种模型误差对滤波效果的影响,采用实时调整状态预测在滤波估计中权重的策略,给出了自适应Kalman滤波准则及递推公式。基于正交性原理和最小二乘法准则,利用三段函数模型构造了双重自适应因子。仿真实例表明,与标准Kalman滤波与强跟踪滤波相比,所提算法具有更好的估计精度和稳定性,能够有效地控制模型误差的影响,从而提高六维力传感器的测量精度。     

An adaptive and computationally efficient algorithm for parameters estimation of superimposed exponential signals with observations missing randomly

In this paper, we consider the parameters estimation of a model of superimposed exponential signals in multiplicative and additive noise when some observations are missing randomly. The least squares estimators (LSEs) and asymptotic Cramer–Rao low bound (ACRLB) for the considered model are studied and the asymptotic distributions of the LSEs for parameters of frequencies, phases and amplitudes of the considered model are also derived and obtained. An adaptive and computationally efficient iterative algorithm is proposed to estimate the frequencies of the considered model. It can be seen that the iterative algorithm works quite well in terms of biases and mean squared errors and the refined estimators by three iterations are observed to be asymptotically unbiased and consistent. The statistics for iteration are designed to change adaptively according to different missing distributions of time points so as to keep the estimators of frequencies to be asymptotically unbiased. Moreover, the proposed estimators attain the same convergence rate and asymptotic distribution as those of LSEs which are used to obtain the confident intervals and coverage probabilities of the frequencies for finite sample. Since the iterative algorithm needs only three iterations to work, it saves much computation time. So the proposed estimators are LSEs equivalent while avoid the heavy computation cost of LSEs. Finally, several simulation experiments are performed to verify the effectiveness of the proposed algorithm. To examine the robustness of the proposed algorithm, we also test the algorithm on the dual tone multi-frequency (DTMF) signal with observations missing in block and symmetric α-stable (SaS) noise condition, as well as on sinusoidal frequency modulated signals.     

一种自适应鲁棒伺服系统的设计

针对存在变频率正弦扰动的直流伺服系统,提出一种用微处理机实现的自适应鲁棒控制器设计方法.数字仿真结果表明,该系统抑制变频率正弦扰动效果显著.     

Stability analysis of periodic orbit of an adaptive notch filter for frequency estimation of a periodic signal

Online frequency estimation of a sinusoidal signal is a classical problem and has many practical applications. Recently an adaptive notch filter (ANF) with global convergence property has been developed for frequency estimation of a pure sinusoidal signal. This paper addresses a modified ANF structure that can estimate the fundamental frequency of any periodic signal including pure sinusoidal signals. To prove the stability of the modified ANF, the paper introduces a new theorem that shows for any periodic signal, there exists a locally asymptotically stable periodic orbit of this ANF by which the frequency estimation becomes feasible. This alternative stability proof is simple and uses widely known mathematical tools, and therefore alleviates the problem complexity even when the input signal is a pure sinusoidal signal. A further contribution of this paper is obtaining a necessary and sufficient condition in terms of design parameters for local asymptotical stability of the modified ANF. This condition, obtained from the numerical study of Floquet multipliers of a linear time-varying periodic system, provides a strict stability region in the modified ANF design parameters space.     

基于瞬时幅值的光伏系统电流传感器微小故障检测及估计

电流传感器是光伏系统中用于系统控制和状态监测的重要元件,然而受运行环境影响,电流传感器易出现性能退化,影响系统运行安全.为了准确检测和估计出电流传感器微小故障,提出基于瞬时幅值的传感器微小故障检测和估计方法.首先,建立基于瞬时幅值的电流传感器微小故障模型,利用Hilbert变换(HT)估计相电流瞬时幅值将测量的三相正弦电流转换为相互独立的三维直流信号分量;其次,利用快速移动窗主成分分析(FWMPCA)对三维直流信号组成的数据矩阵进行特征提取,获得主元和残差子空间向量的概率密度分布函数;然后,利用Kullback-Leibler(KL)距离定量度量实际运行数据相对于无故障运行数据的微小变化,在此基础上,设置故障检测阈值,构建故障幅值估计模型,实现电流传感器微小故障检测和估计;最后,利用RT-LAB实验平台验证所提方法的有效性.     

Leader‐following attitude consensus of multiple uncertain spacecraft systems subject to external disturbance

The attitude consensus problem of multiple rigid spacecraft systems is one of the key issues in spacecraft formation flying and has been extensively studied. In this paper, we further consider the leader‐following attitude consensus problem of multiple rigid uncertain spacecraft systems subject to a class of multi‐tone sinusoidal disturbances with arbitrarily unknown amplitudes, initial phases, frequencies, and constant biases. In contrast to the existing results, in order to achieve asymptotic reference tracking and disturbance rejection by smooth control, we have integrated the distributed observer approach with internal model and adaptive control techniques. Simulation results are shown to validate the effectiveness of the proposed control law. Copyright © 2016 John Wiley & Sons, Ltd.     

Global stabilization and disturbance suppression of a class of nonlinear systems with uncertain internal model

This paper deals with global stabilization and disturbance suppression of a class of nonlinear systems using output feedback. The disturbances generated from a unknown linear exosystem are completely compensated. The order of the exosystem is assumed known and the eigenvalues are distinct. No other assumptions are needed in the control design. This means that the proposed control design is able to completely compensate the disturbances without knowing their amplitudes, frequencies and phases, as long as the number of different frequency components in the disturbances is known. A new formulation of state estimation is introduced to ensure the global stabilization and complete disturbance suppression. Adaptive control technique is used to design an adaptive internal model based on a recently introduced formulation of unknown exosystems and the parameters in the adaptive internal model converge to the actual values, from which the unknown disturbance frequencies can be calculated. In the proposed control design, a number of control coefficients are made adaptive so that the result is global with respect to unknown frequencies in the disturbances.     

基于冗余小波变换的自适应运动估计与补偿算法研究*

为进一步提高运动估计和补偿的效果,提出了一种基于冗余离散小波变换（RDWT）的自适应运动估计算法。该算法提出了一种自适应块匹配和用于划分块运动状况的自适应阈值的计算方法;对静止块不进行估计,只对运动块采用自适应搜索起点预测方法和自适应阈值算法进行运动估计与补偿。实验结果表明,该方法能在保持较高峰值信噪比的情况下提高运动估计效率,且重建图像主观质量很好,较现有RDWT域运动估计算法有明显优势。     

归一化频率自适应梳状滤波器的稳定性分析

采用多个归一化频率估计器并联形成梳状滤波器, 以跟踪和检测平稳概周期信号各正弦成分的未知频率和未知幅值. 滤波器包括相互耦合的状态估计和频率估计两个非线性微分方程. 运用慢积分流形实现两个微分方程之间的解耦, 获得关于多个频率估计值的概周期非线性动力系统, 再应用平均方法导出估计频率的非线性自治方程. 分析了自治系统的三种局部稳定性: 孤立平衡点的指数稳定性, 中心流形存在性与半稳定性以及结构扰动下的有界性. 说明幅值估计与信号跟随的收敛性和有界性. 给出滤波器参数对频率跟踪和幅值估计的暂态和稳态性能的影响. 算法实现了在给定频率区间而不是给定数值条件下的正弦分量及其幅值的准确跟随, 并且响应速度不受正弦分量幅值大小的影响. 通过仿真验证了算法的有效性.     

Genetic algorithms based robust frequency estimation of sinusoidal signals with stationary errors

In this paper, we consider the fundamental problem of frequency estimation of multiple sinusoidal signals with stationary errors. We propose genetic algorithm and outlier-insensitive criterion function based technique for the frequency estimation problem. In the simulation studies and real life data analysis, it is observed that the proposed genetic algorithm based robust frequency estimators are able to resolve frequencies of the sinusoidal model with high degree of accuracy. Among the proposed methods, the genetic algorithm based least squares estimator, in the no-outlier scenario, provides efficient estimates, in the sense that their mean square errors attain the corresponding Cramér-Rao lower bounds. In the presence of outliers, the proposed robust methods perform quite well and seem to have a fairly high breakdown point with respect to level of outlier contamination. The proposed methods significantly do not depend on the initial guess values required for other iterative frequency estimation methods.     

基于匹配跟踪的感知梯度正弦建模方法

匹配跟踪作为一种自适应的信号分解算法,为语音和音频正弦建模提供了一个新的框架.分析了基于匹配跟踪的正弦建模过程以及感知加权匹配跟踪正弦建模算法,并在此基础上提出了感知梯度正弦建模方法.该方法结合匹配跟踪自适应的动态特征,利用心理声学模型计算当前合成信号的动态掩蔽阈值,以此为参考提取残差信号中感觉最明显的信号分量,从而最大限度地增加合成信号中的感知信息.在模型精度不高的情况下,该方法也能得到合成质量比较高的语音.实验表明,该方法更好地利用了人耳的听觉特性,建模结果更为合理、有效.客观的信噪比和主观试听测试都显示了所提出算法的合理性与优越性.     

Adaptive disturbance observer‐based control for stochastic systems with multiple heterogeneous disturbances

Antidisturbance control problem is discussed for stochastic systems with multiple heterogeneous disturbances, which include the white noise and the disturbance with unknown frequencies and amplitudes. An adaptive disturbance observer is designed to estimate the disturbance with unknown frequencies and amplitudes, based on which, an adaptive disturbance observer‐based control scheme is proposed by combining adaptive technique and linear matrix inequality method. It is proved that the closed‐loop system is asymptotically bounded in mean square when multiple heterogeneous disturbances exist simultaneously and that the equilibrium is globally asymptotically stable in probability as additive disturbance disappears. Finally, two simulation examples, including a wind turbine system, are given to show the effectiveness of the proposed scheme.     

基于自适应滤波器的时频分析

采用最小方差原则和梯度下降方法, 经过旋转变换, 获得频率参数和带宽参数可调的自适应二维线性正弦跟踪滤波器, 实现信号跟随与幅值估计. 把多个跟踪器并联, 形成带宽可调的多频点梳状滤波器, 得到多维线性常系数微分动力系统. 用不变原理证明梳状滤波器是一致渐近稳定的. 用拉普拉斯变换导出频率特性, 单正弦输入时为向量形式, 针对多正弦分量时为频率特性矩阵. 当输入信号所有正弦分量的频率都等于梳状滤波器频率参数时, 本算法能够同时准确跟随所有分量及其幅值. 分析了算法的频域格栅效应以及带宽参数对稳态精度的影响, 通过仿真说明了算法的有效性.     

Precision attitude regulation of uncertain flexible spacecraft

Consider the precision attitude regulation with vibration suppression for an uncertain and disturbed flexible spacecraft. The disturbance at issue is typically any finite superposition of sinusoidal signals with unknown frequencies and step signals of unknown amplitudes. First we show that the conventional mathematical model for flexible spacecrafts is transformable to a multi-input multi-output (MIMO) strict-feedback nonlinear normal form. Particularly it is strongly minimum-phase and has a well-defined uniform vector relative degree. Then it enables us to develop an adaptive internal model-based controller in the framework of adaptive output regulation to solve the problem. It is proved that asymptotic stability can be guaranteed for the attitude regulation task and the vibration of flexible appendages vanishes asymptotically. Hence, the present study explores a new idea for control of flexible spacecraft in virtue of its system structures.     

Adaptive observer of an unknown sinusoidal output disturbance for linear plants

A new algorithm is proposed to the design of an adaptive observer for an unknown sinusoidal disturbance that affects the output of a non-minimum phase linear control plant.