An enhanced linear Kalman filter (EnLKF) algorithm for parameter estimation of nonlinear rational models

In this study, an enhanced Kalman Filter formulation for linear in the parameters models with inherent correlated errors is proposed to build up a new framework for nonlinear rational model parameter estimation. The mechanism of linear Kalman filter (LKF) with point data processing is adopted to develop a new recursive algorithm. The novelty of the enhanced linear Kalman filter (EnLKF in short and distinguished from extended Kalman filter (EKF)) is that it is not formulated from the routes of extended Kalman Filters (to approximate nonlinear models by linear approximation around operating points through Taylor expansion) and also it includes LKF as its subset while linear models have no correlated errors in regressor terms. No matter linear or nonlinear models in representing a system from measured data, it is very common to have correlated errors between measurement noise and regression terms, the EnLKF provides a general solution for unbiased model parameter estimation without extra cost to convert model structure. The associated convergence is analysed to provide a quantitative indicator for applications and reference for further research. Three simulated examples are selected to bench-test the performance of the algorithm. In addition, the style of conducting numerical simulation studies provides a user-friendly step by step procedure for the readers/users with interest in their ad hoc applications. It should be noted that this approach is fundamentally different from those using linearisation to approximate nonlinear models and then conduct state/parameter estimate.     

Asymptotic behaviours and stability of zero dynamics in nonlinear discrete-time systems using Taylor approach and multirate input

It is well known that the existence of unstable sampled zero dynamics is recognised as a major barrier in many control problems. When the usual digital control with zero-order hold (ZOH) or fractional-order hold (FROH) input is used, unstable sampled zero dynamics inevitably appear in the discrete-time model even though the continuous-time system with relative degree more than or equal to three is of minimum phase. In this paper, we show how an approximate sampled-data model can be obtained for nonlinear systems by the use of multirate input and hold such as a generalised sample hold function (GSHF) in order that discrete zero dynamics of the resulting model can be arbitrarily placed. Furthermore, the properties of sampled zero dynamics are studied and the conditions for ensuring the stability of sampling zero dynamics of the desired model are derived. The results presented here generalise well-known notion of sampling zero dynamics from the linear case to nonlinear systems, and GSHF can provide some advantages over ZOH or FROH in terms of stability of discrete system zero dynamics.     

Experimental sensorless control for IPMSM by using integral backstepping strategy and adaptive high gain observer

In this paper a robust sensorless control for an Interior Permanent Magnet Synchronous Motor (IPMSM) is designed. The proposed control strategy uses a backstepping controller, whose robustness is improved by using integral actions added at each step of the original algorithm, and by a Maximum-Torque-Per-Ampere strategy (MTPA) to improve its energy efficient operation. Furthermore, to implement this controller in the framework of the mechanical sensorless control from the only measurements of the currents and voltages, an adaptive interconnected high gain observer is developed for estimating the rotor speed, the position and the load torque. Moreover, sufficient conditions are given to ensure the practical stability of the Observer-Controller system even if bounded uncertainties occur. Finally, the performance and the effectiveness of the designed method are tested experimentally throw a significant benchmark including different speed references and with significant robustness tests. A comparative evaluation of the computational effort of our scheme with respect to classical motor control is given.     

Modeling and robust control of a twin wind turbines structure

The control of a new structure of twin wind turbines (TWT) is presented in this paper. This new concept includes two identical wind turbines ridden on the same tower, which can pivot face the wind with no additional actuator. The motion of the arms carrying the TWT is free. The control law based on sliding mode controller is designed to track the maximum power, by controlling the rotor speed of the TWT and the yaw rotation but without yaw actuator. Finally, performances of the proposed control strategy are compared to standard proportional integral controller, for several scenarios (time varying direction or magnitude of the wind, error on the inertia of the system, …).     

一种自适应的多类Boosting分类算法

许多实际问题涉及到多分类技术,该技术能有效地缩小用户与计算机之间的理解差异。在传统的多类Boosting方法中,多类损耗函数未必具有猜测背离性,并且多类弱学习器的结合被限制为线性的加权和。为了获得高精度的最终分类器,多类损耗函数应具有多类边缘极大化、贝叶斯一致性与猜测背离性。此外,弱学习器的缺点可能会限制线性分类器的性能,但它们的非线性结合可以提供较强的判别力。根据这两个观点,设计了一个自适应的多类Boosting分类器,即SOHPBoost算法。在每次迭代中,SOHPBoost算法能够利用向量加法或Hadamard乘积来集成最优的多类弱学习器。这个自适应的过程可以产生多类弱学习的Hadamard乘积向量和,进而挖掘出数据集的隐藏结构。实验结果表明,SOHPBoost算法可以产生较好的多分类性能。     

Estimation of Nonparametric Autoregressive Time Series Models Under Dynamical Constraints

Abstract. A method is introduced to estimate nonparametric autoregressive models under the additional constraint that its regression function has a stable cycle. It is based on a penalty approach that chooses a series expansion approximation taking into account both goodness‐of‐fit and fulfillment of the constraint. Consistency of the proposed estimator is obtained under general hypothesis. Feasibility and effective performance of the introduced method are studied through simulated examples and electro‐encephalographic data collected from a subject suffering from epilepsy.     

Volterra filter modeling of a nonlinear discrete-time system based on a ranked differential evolution algorithm

This paper presents a ranked differential evolution （RDE） algorithm for solving the identification problem of non- linear discrete-time systems based on a Volterra filter model. In the improved method, a scale factor, generated by combining a sine function and randomness, effectively keeps a balance between the global seareh and the local search. Also, the mutation operation is modified after ranking all candidate solutions of the population to help avoid the occurrence of premature convergence. Finally, two examples including a highly nonlinear discrete-time rational system and a real heat exchanger are used to evaluate the per- formance of the RDE algorithm and five other approaches. Numerical experiments and comparisons demonstrate that the RDE algorithm performs better than the other approaches in most cases.     

Dynamic analysis of harmonically excited non-linear system using multiple scales method

An analytical method is presented for evaluation of the steady state periodic behavior of nonlinear systems. This method is based on the substructure synthesis formulation and a MS (multiple scales) procedure, which is applied to the analysis of nonlinear responses. The proposed procedure reduces the size of large degrees-of-freedom problem in solving nonlinear equations. Feasibility and advantages of the proposed method are illustrated with the nonlinear rotating machine system as an example of large mechanical structure systems. In addition, its efficiency for nonlinear response prediction will be shown by comparison of other conventional methods.     

球面间隙大范围测量的建模与线性化研究

有源静电悬浮轴承通过检测电极与转子间构成的球面间隙电容以得到转子位移。在转子起支时，要能实现球面间隙的大范围线性测量，本文重点推导了球面电容与球面间隙的非线性关系，提出了采用软件非线性校正的方法实现球面间隙大规范测量的线性化，使转子位移的线性测量范围可以达到标称间隙的66％，满足了静电轴承起支过程的要求。     

Effects of oil inlet pressure and inlet position of axially grooved infinitely long journal bearings. Part II: Nonlinear instability analysis

This paper extends the analysis of Part I to investigate the influence of oil inlet pressure and its position on the dynamic characteristics of axially grooved journal bearings. Using the dynamic fluid force derived in Part I, the equations of motion are solved for the locus of the journal center. A trial-and-error method is used to identify the instability threshold speed for a given Sommerfeld number S. The effects of oil inlet pressure (in the range of ) and inlet position (in the range of 0Θ_i90°) on the instability threshold speed of a rotor-bearing system are investigated and discussed. It is shown that the instability threshold speed with oil inlet position Θ_i=0 decreases on increasing the oil inlet pressure from 0 to 1.0 while the influence of oil inlet position on the instability threshold speed depends on the steady state eccentricity ratio ε.