星型算子理论的发展及其应用

介绍了近年来星型算子理论特别是w-算子理论的发展和其对环与模范畴的刻划的重要作用.其中包括了星型算子理论关注的一些热点问题,经典环模范畴理论在星型算子之下产生的相关表现形式与研究进展,理想的乘法系的局部化方法,Milnor方图在环结构理论及其维数理论中的作用.

范畴的广义局部化

通过范畴的两个乘法系定义了右分式的一个等价关系,由此引入以原范畴对象为对象,右分式等价类为态射的范畴的广义局部化概念.最后证明加法范畴的广义局部化范畴仍然是加法范畴.

Approach to estimation of vehicle-road longitudinal friction coefficient

According to the road adaptive requirements for the vehicle longitudinal safety assistant system an estimation method of the road longitudinal friction coefficient is proposed.The method can simultaneously be applied to both the high and the low slip ratio conditions. Based on the simplified magic formula tire model the road longitudinal friction coefficient is preliminarily estimated by the recursive least squares method.The estimated friction coefficient and the tires model parameters are considered as extended states. The extended Kalman filter algorithm is employed to filter out the noise and adaptively adjust the tire model parameters. Then the final road longitudinal friction coefficient is accurately and robustly estimated. The Carsim simulation results show that the proposed method is better than the conventional algorithm. The road longitudinal friction coefficient can be quickly and accurately estimated under both the high and the low slip ratio conditions.The error is less than 0.1 and the response time is less than 2 s which meets the requirements of the vehicle longitudinal safety assistant system.

Parameter identification and pressure control of dynamic system in shield tunneling using least squares method

An estimation approach using least squares method was presented for identificationof model parameters of pressure control in shield tunneling.The state equation ofthe pressure control system for shield tunneling was analytically derived based on themass equilibrium principle that the entry mass of the pressure chamber from cutting headwas equal to excluding mass from the screw conveyor.The randomly observed noise wasnumerically simulated and mixed to simulated observation values of system responses.The numerical simulation shows that the state equation of the pressure control system forshield tunneling is reasonable and the proposed estimation approach is effective even ifthe random observation noise exists.The robustness of the controlling procedure is validatedby numerical simulation results.

Multiplicative Stochastic Resonance for a Linear System Driven by O-U Noise

In the paper, we study a linear system driven by O-U noise and give a method which is different from the one stated in Europhys. Lett. 40 （1997） 117. We find the same phenomenon of multiplicative stochastic resonance for the response of the system to the signal as the one found in Europhys. Left. 40 （1997） 117. The merit of our method is that it prevents the complex formulas when making sum from n = 0 to n →∞ as in Europhys. Lett. 40 （1997） 117, which leads to the approximate results of the figures.

Nonlinear decoupling controller design based on least squares support vector regression

Support Vector Machines (SVMs) have been widely used in pattern recognition and have also drawn considerable interest in control areas. Based on a method of least squares SVM (LS-SVM) for multivariate function estimation, a generalized inverse system is developed for the linearization and decoupling control of a general nonlinear continuous system. The approach of inverse modelling via LS-SVM and parameters optimization using the Bayesian evidence framework is discussed in detail. In this paper, complex high-order nonlinear system is decoupled into a number of pseudo-linear Single Input Single Output (SISO) subsystems with linear dynamic components. The poles of pseudo-linear subsystems can be configured to desired positions. The proposed method provides an effective alternative to the controller design of plants whose accurate mathematical model is un- known or state variables are difficult or impossible to measure. Simulation results showed the efficacy of the method.

Multiplicative perturbations of C-regularized resolvent families

This paper presents two new theorems for multiplicative perturbations of C-regularized resolvent families, which generalize the previous related ones for the resolvent families.

A Decentralized Parallel One-Pass Fixed-Interval Deconvolution Algorithm for Multisensor Systems with Multiplicative Noises

A decentralized parallel one-pass deconvolution algorithm for multisensor systems with multiplicative noises is proposed. Comparing with the conventional deconvolution algorithm, it avoids the computational overload and the high storage requirement. The algorithm is optimal in the sense of linear minimum-variance. The simulation results illustrate the validity of the proposed algorithm.

Absorption Spectroscopy of （8,1） Band in d^3△-a^3П System of CS Radical

The CS radical was generated by discharging the mixture gas of CS2 and Helium. The Doppler limited spectra of CS were recorded in the region of 12350-12950 cm^-1 using optical heterodyne concentration modulation absorption spectroscopy. Three hundred and twenty-six lines were recorded and assigned to the d^3△-a^3П （8,1） band, in which eighty-three transitions were first observed. A set of improved molecular constants for the d^3△（v=8） and a^3П（v=1） levels were determined by a non-linear least-squares fitting of all the lines to the effective Hamiltonian.

Consistency and Asymptotic Property of a Weighted Least Squares Method for Networked Control Systems

In this paper, we study the problems related to parameter estimation of a single-input and single-output networked control system, which contains possible network-induced delays and packet dropout in both of sensor-to-controller path and controller-to-actuator path. A weighted least squares(WLS) method is designed to estimate the parameters of plant, which could overcome the data uncertainty problem caused by delays and dropout. This WLS method is proved to be consistent and has a good asymptotic property. Simulation examples are given to validate the results.

Mixed-Weights Least-Squares Stable Predictive Control Algorithm with Soft and Hard Constraints

Mixed-weight least-squares (MWLS) predictive control algorithm, compared with quadratic programming (QP) method, has the advantages of reducing the computer burden, quick calculation speed and dealing with the case in which the optimization is infeasible. But it can only deal with soft constraints. In order to deal with hard constraints and guarantee feasibility, an improved algorithm is proposed by recalculating the setpoint according to the hard constraints before calculating the manipulated variable and MWLS algorithm is used to satisfy the requirement of soft constraints for the system with the input constraints and output constraints. The algorithm can not only guarantee stability of the system and zero steady state error, but also satisfy the hard constraints of input and output variables. The simulation results show the improved algorithm is feasible and effective.

A novel Q-based online model updating strategy and its application in statistical process control for rubber mixing

To overcome the large time-delay in measuring the hardness of mixed rubber, rheological parameters were used to predict the hardness. A novel Q-based model updating strategy was proposed as a universal platform to track time-varying properties. Using a few selected support samples to update the model, the strategy could dramat- ically save the storage cost and overcome the adverse influence of low signal-to-noise ratio samples. Moreover, it could be applied to any statistical process monitoring system without drastic changes to them, which is practical for industrial practices. As examples, the Q-based strategy was integrated with three popular algorithms （partial least squares （PIE）, recursive PIE （RPLS）, and kernel PIE （KPIE）） to form novel regression ones, QPLS, QRPIE and QKPLS, respectively. The applications for predicting mixed rubber hardness on a large-scale tire plant in east China prove the theoretical considerations.

Modeling for Orientation Deviation of Workpiece and Analysis of Machining Accuracy

The machining accuracy of workpiece is influenced by its orientation deviation, which is caused by the fixture-workpiece error. Based on the spatial coordinate theory, the orientation deviation of workpiece is measured by using an on-machine verification system, which can take into account the errors resulting from fixture manufacturing, installation and adjustment, location and clamping of workpiece. According to the least square method, the model of orientation deviation is built to determine the relationship between the theoretical and actual coordinate systems. The influence of orientation deviation on machining accuracy is quantified, and it is shown that the orientation deviation only affects the dimensional precision and position precision, rather than shape precision. In the experiment, the compensation processing of realtime errors was conducted, and the perpendicularity and inclination errors of the tetragonal part were reduced by 38.46% and 47.06%, respectively.

System identification of channel roughness for Mid-Route Project of South-to-North Water Diversion

This paper presents a new method for the system identification of the channel roughness for the water diversion projects. According to the principle of hydraulics,the function relationship among channel roughness n, roughness height k s and hydraulic radius R is established,and then a linear model is deduced by means of the mathematical transformation to make use of the least square method for identification. Finally,based on the prototype observation data from the South-to-North Water Diversion Project and considering the influence of channel lengths,cross-section shapes and bottom slopes,etc,a universal formula is obtained for calculation of channel roughness by the system identification.

Least Squares Fitting Based Fault Classification in Distribution Systems

Power systems are the largest and most complex human made systems, consisting of thousands of electrical sources, loads, transmission and distribution lines, power transformers, circuit breakers, etc. where faults always occurred. Faults can cause personnel and equipment safety problems, and can result in significant disruption to power supply and thus financial losses. In this paper we will present comprehensive mathematical suite to detect and classify fault dependent models of various types of power systems. This work will extract fault unique signatures by using polarization ellipse during the healthy condition and the polarization will be circular shape with radius equal the rated voltage of the system, but during the fault condition the polarization will be ellipse shape and the fault signature will be defined according the ellipse parameters major axis, minor axis, ellipticity and orientation angle, by using least squares criterion will define the ellipse parameters this system will identify and classify. This paper will be a milestone for extended paper based on the proposed mathematical modelling and applying it to identify, classify and localize with simulation model.

FMLSMETHODOFPARAMETERESTIMATIONANDITSAPPLICATIONTOHEAT┐EXCHANGERIDENTIFICATION

Using the inversion of the auto correlation function Toeplitz matrix of pseudo random binary sequence (PRBS) derived in this paper and the theorem of partitioned matrix inversion, a fast multistage least squares (FMLS) method is developed. Its performances are theoretically analyzed and digital simulation is made to compare FMLS with multistage least squares (MSLS), correlation least squares(COR LS) and LS for their computer speed and identification accuracy. Finally, FMLS is applied to identifying the heat excharger dynamics. It is shown that FMLS is a good and effective identification technique.

Observer-based hybrid control algorithm for semi-active suspension systems

In order to improve ride comfort and handling performance of the vehicle, an adaptive hybrid control algorithm is proposed for semi-active suspension systems. The virtues of sky-hook is combined with ground-hook control strategies and a more suitable compromise for the suspension systems is chosen. The hybrid coefficient is tuned according to the longitudinal and lateral acceleration so as to improve the vehicle stability especially in high speed conditions. Damping continuous adjustable absorber is used to continuously control the damping force so as to eliminate the damping force jerk instead of traditional on-off control policy. Based on suspension stroke measured by sensors, unscented Kalman filter is designed to estimate the suspension states in real-time for the realization of hybrid control, which improves the robustness of the control strategy and is adaptive to different types of road profiles. Finally, the proposed control algorithm is validated under the following two typical road profiles: half-sine speed bump road and the random road. The simulation results indicate that the hybrid control algorithm could offer a good coordination between ride comfort and handling of the vehicle.

Research on the File Encryption and Programming based on Matrix Transformation

Any linear transform matrix can be used to easily calculate a consistent form, and a plurality of conversion can be easily connected together by matrix multiplication. When performing file transfers, you can encrypt files matrix transformation. Article presents a matrix-based electronic document encryption and decryption algorithm, which relies on a special class of matrices combinatorial problems, the method to improve the security of electronic document system is feasible and effective, and finally give the source code and programming software.

Parameter Estimation with Constraints Based on Variational Method

The accuracy of parameter estimation is critical when digitally modeling a ship. A parameter estimation method with constraints was developed, based on the variational method. Performance functions and constraint equations in the variational method are constructed by analyzing input and output equations of the system. The problem of parameter estimation was transformed into a problem of least squares estimation. The parameter estimation equation was analyzed in order to get an optimized estimation of parameters based on the Lagrange multiplication operator. Simulation results showed that this method is better than the traditional least squares estimation, producing a higher precision when identifying parameters. It has very important practical value in areas of application such as system identification and parameter estimation.

BOUNDARY FEEDBACK STABILIZATION OF NONUNIFORM TIMOSHENKO BEAM WITH A TIPLOAD

The boundary stabilization problem of a Timoshenko beam attached with a mass at one end is studied. First, with linear boundary force feedback and moment control simultaneously at the end attached with the load, the energy corresponding to the closed loop system is proven to be exponentially convergent to zero as time t →∞. Then, some counterexamples are given to show that, in other casest the corresponding closed loop system is, in general, not stable asymtotically, let alone exponentially.