基于PLC的拉丝机张力控制系统研究

本文介绍了现在已经广泛使用的拉丝机张力控制的关键计算公式以及控制流程 ,利用PLC的高速输出通道 ,将采集来的转速脉冲信号转化为线速度 ,对收线速度与拉丝速度进行比较 。

汽车用细丝径油淬火55SiCr弹簧钢丝的感应回火工艺研究

为得到适配细丝径油淬火弹簧钢丝的感应回火工艺,满足国家绿色发展理念,研究收线速度和感应回火温度对直径5.4 mm油淬火55SSiCr弹簧钢丝微观组织和性能的影响,采用金相显微镜、扫描电子显微镜、微机控制电子万能试验机等对钢丝的微观组织、力学性能进行测试。结果发现:存在一个较优的感应回火工艺,收线速度、感应加热功率、回火温度分别为5 m/min、4.44 kW和460℃,可使钢丝回火后的组织分布均匀、片层间距致密,针状形貌明显、马氏体特征基本消失,综合力学性能优异。感应回火后弹簧钢丝的抗拉强度为1864 MPa,位于国标中限,屈强比、面缩率分别为0.92和54%,远超国标要求,平均维氏硬度为528 HV,且分布均匀。

Superlinear Convergence of a Smooth Approximation Method for Mathematical Programs with Nonlinear Complementarity Constraints

Mathematical programs with complementarity constraints(MPCC) is an important subclass of MPEC.It is a natural way to solve MPCC by constructing a suitable approximation of the primal problem.In this paper,we propose a new smoothing method for MPCC by using the aggregation technique.A new SQP algorithm for solving the MPCC problem is presented.At each iteration,the master direction is computed by solving a quadratic program,and the revised direction for avoiding the Maratos effect is generated by an explicit formula.As the non-degeneracy condition holds and the smoothing parameter tends to zero,the proposed SQP algorithm converges globally to an S-stationary point of the MPEC problem,its convergence rate is superlinear.Some preliminary numerical results are reported.

Recent Progress on RF Superconductivity and ERL

RF superconducting cavities can work in CW mode or long pulse mode.RF superconducting technology is widely used in particle accelerators.The development of RF superconductivity is limited by the material,surface treatment and installation.SRF technology is improved greatly after dozens of years'researches.Lots of techniques and experiences have been accumulated by running superconducting accelerators.In recent years,researches and developments have been carried out for future large scientific project.New cavity shape and superconducting cavities made of large grain niobium are the hot frontiers in SRF field.Energy Recovery Linacs have been developed in recent years.ERLs has many advantages such as high efficiency,energy saving,good stability,low radiation level,etc.ERLs are more and more used in advanced light sources and free electron laser facilities.

A Dwindling Filter Algorithm with a Modified Subproblem for Nonlinear Inequality Constrained Optimization

The authors propose a dwindling filter algorithm with Zhou's modified subproblem for nonlinear inequality constrained optimization.The feasibility restoration phase,which is always used in the traditional filter method,is not needed.Under mild conditions,global convergence and local superlinear convergence rates are obtained.Numerical results demonstrate that the new algorithm is effective.

A CLASS OF REVISED BROYDEN ALGORITHMS

In this paper, we discuss the convergence of the Broyden algorithms withrevised search direction. Under some inexact line searches, we prove that the algorithms areglobally convergent for continuously differentiable functions and the rate of convergence of thealgorithms is one-step superlinear and n-step second-order for uniformly convex objective functions.

Sieve M-estimator for a semi-functional linear model

We propose sieve M-estimator for a semi-functional linear model in which the scalar response is explained by a linear operator of functional predictor and smooth functions of some real-valued random variables.Spline estimators of the functional coefficient and the smooth functions are considered,and by selecting appropriate knot numbers the optimal convergence rate and the asymptotic normality can be obtained under some mild conditions.Some simulation results and a real data example are presented to illustrate the performance of our estimation method.

Partial functional linear quantile regression

This paper studies estimation in partial functional linear quantile regression in which the dependent variable is related to both a vector of finite length and a function-valued random variable as predictor variables. The slope function is estimated by the functional principal component basis. The asymptotic distribution of the estimator of the vector of slope parameters is derived and the global convergence rate of the quantile estimator of unknown slope function is established under suitable norm. It is showed that this rate is optirnal in a minimax sense under some smoothness assumptions on the covariance kernel of the covariate and the slope function. The convergence rate of the mean squared prediction error for the proposed estimators is also established. Finite sample properties of our procedures are studied through Monte Carlo simulations. A real data example about Berkeley growth data is used to illustrate our proposed methodology.

A FILTER SECANT METHOD WITH NONMONOTONE LINE SEARCH FOR EQUALITY CONSTRAINED OPTIMIZATION

This paper proposes a filter secant method with nonmonotone line search for non-linearequality constrained optimization.The Hessian of the Lagrangian is approximated using the BFGSsecant update.This new method has more flexibility for the acceptance of the trial step and requires lesscomputational costs compared with the monotone one.The global and local convergence of the proposedmethod are given under some reasonable conditions.Further,two-step Q-superlinear convergence rateis established by introducing second order correction step.The numerical experiments are reported toshow the effectiveness of the proposed algorithm.

A LINE SEARCH FILTER INEXACT SQP METHOD FOR NONLINEAR EQUALITY CONSTRAINED OPTIMIZATION

This paper proposes an inexact SQP method in association with line search filter technique for solving nonlinear equality constrained optimization. For large-scale applications, it is expensive to get an exact search direction, and hence the authors use an inexact method that finds an approximate solution satisfying some appropriate conditions. The global convergence of the proposed algorithm is established by using line search filter technique. The second-order correction step is used to overcome the Maratos effect, while the line search filter inexact SQP method has q-superlinear local convergence rate. Finally, the results of numerical experiments indicate that the proposed method is efficient for the given test problems.

Reaching a stochastic consensus in the noisy networks of linear MIMO agents:Dynamic output-feedback and convergence rate

This paper addresses the leader-following consensus problem of linear multi-agent systems(MASs) with communication noise. Each agent's dynamical behavior is described by a linear multi-input and multi-output(MIMO) system, and the agent's full state is assumed to be unavailable. To deal with this challenge, a state observer is constructed to estimate the agent's full state. A dynamic output-feedback based protocol that is based on the estimated state is proposed. To mitigate the effect of communication noise, noise-attenuation gains are also introduced into the proposed protocol. In this study, each agent is allowed to have its own noise-attenuation gain. It is shown that the proposed protocol can solve the mean square leader-following consensus problem of a linear MIMO MAS. Moreover, if all noise-attenuation gains are of Q(t-β), where b∈(0,1), the convergence rate of the MAS can be quantitatively analyzed. It turns out that all followers' states converge to the leader's state in the mean square sense at a rate of O(t-β).

Regularization Method and Immune Genetic Algorithm for Inverse Problems of Ship Maneuvering

Ship maneuverability, in the field of ship engineering, is often predicted by maneuvering motion group （MMG） mathematical model. Then it is necessary to determine hydrodynamic coefficients and interaction force coefficients of the model. Based on the data of free running model test, the problem for obtaining these coefficients is called inverse one. For the inverse problem, ill-posedness is inherent, nonlinearity and great computation happen, and the computation is also insensitive, unstable and time-consuming. In the paper, a regularization method is introduced to solve ill-posed problem and genetic algorithm is used for nonlinear motion of ship maneuvering. In addition, the immunity is applied to solve the prematurity, to promote the global searching ability and to increase the converging speed. The combination of regularization method and immune genetic algorithm（RIGA） applied in MMG mathematical model, showed rapid converging speed and good stability.