用体积参数控制法计算SMA初试沥青用量

用体积法设计SMA沥青混合料配合比,可以用体积率控制参数集料间隙率VMA、压实混合料空隙率VV计算单位体积沥青混合料中有效沥青质量Mbe和组合集料质量Ms,用组合集料表观相对密度和毛体积相对密度计算单位质量集料的孔隙体积率,用集料孔隙吸收胶浆（沥青和矿粉的混合物）假设法计算集料吸收沥青质量Mba,Mbe与Mba之和与单位体积沥青混合料质量（Ms＋Mbe＋Mba）之比即为沥青用量Pb。计算结果与经验方法及以前常用经验公式计算值基本一致。更精确的沥青用量计算应考虑纤维稳定剂在VMA中所占的体积率和集料孔隙吸入的矿粉质量。

基于非参数合成控制法的自贸政策引资动态效应——以上海自贸试验区为例

非参数合成控制法是一种新颖的政策评估方法,已受到国内外学者的关注。本文以上海自贸试验区为案例,利用该方法实证研究了自贸政策的引资动态效应。非参数合成控制法的估计结果显示,2013-2015年间,自贸试验区政策让上海市外商直接投资存量累积增加2052.6亿元,平均每年的溢出额为684.2亿元,年均溢出率约为14.2%;上海市外商直接投资流量累积增加1330.6亿元,平均每年的溢出额为443.5亿,年均溢出率约为116.2%。上海自贸政策引资动态效应显示,外商在政策试点初期直接投资规模较小,在政策试点后期直接投资规模不断增大,外资对中国设立自贸试验区反应谨慎。合成控制法和双重差分法等一系列稳健性检验表明,自贸试验区政策对地区吸引外资具有正向溢出效应,实证结论具有稳健性。

汽车覆盖件模具数控加工过切问题的研究

对汽车覆盖件模具数控加工中产生加工过切问题的原因的分析表明,模具加工过切是由于编程不当造成的。提出了参数控制法、重新生成曲面法、定义加工区域法等方法来解决加工过切问题。介绍了在CAD/CAM软件系统中解决加工过切的新方法。

细晶铸造真空炉的研制

北京航空材料研究院研究制造了我国第一台细晶铸造真空炉，该炉可用控制参数法和铸型搅动法生产细晶铸件。

基于“绿色通信”理念的自适应载波同步系统方案

针对当前载波同步算法在低信噪比下存在的开销大和复杂度高的问题,提出了一种基于"绿色通信"理念的自适应载波同步系统设计方法。首先利用控制参数法使最佳性能方案向次最佳性能方案转化,然后在满足较小信噪比损失的前提下比较各方案并给出具有开销小和复杂度低的方案。仿真结果表明相比最佳性能方案,次最佳性能方案的导频开销和复杂度分别可降17%和38%,因而非常符合"绿色通信"的理念。

带经济器的空气源热泵系统研究综述

为了解决热泵系统无法在低温工况下工作的问题,国内外学者提出了在空气源热泵系统中增加一个经济器,引入强化补气(EVI)技术。采用闪发器前节流的热泵系统可以实现更佳的制热效果与可靠运行;涡旋压缩机结构简单且容积较小,广泛应用于小型户式空气源热泵机组的研究;采用改变环境温度的实验方法研究系统的中间补气量,发现不同环境温度下,均存在一个最优补气量且数值均不同;采取控制参数法、划分系统切换区域研究经济器的控制策略;采用微元控制体分析法等建立数学模型进行系统仿真,研究仿真误差因素;将经济器应用到中高温工况下的热泵系统与单级吸收式系统,其应用效果都比较良好。对经济器的控制策略将是研究重点,除湿工况下经济器的应用将作为今后研究工作方向之一。

Fractional order PID control for steer-by-wire system of emergency rescue vehicle based on genetic algorithm

Aiming at dealing with the difficulty for traditional emergency rescue vehicle(ECV)to enter into limited rescue scenes,the electro-hydraulic steer-by-wire(SBW)system is introduced to achieve the multi-mode steering of the ECV.The overall structure and mathematical model of the SBW system are described at length.The fractional order proportional-integral-derivative(FOPID)controller based on fractional calculus theory is designed to control the steering cylinder’s movement in SBW system.The anti-windup problem is considered in the FOPID controller design to reduce the bad influence of saturation.Five parameters of the FOPID controller are optimized using the genetic algorithm by maximizing the fitness function which involves integral of time by absolute value error(ITAE),peak overshoot,as well as settling time.The time-domain simulations are implemented to identify the performance of the raised FOPID controller.The simulation results indicate the presented FOPID controller possesses more effective control properties than classical proportional-integral-derivative(PID)controller on the part of transient response,tracking capability and robustness.

具有内生变量的部分线性模型研究

在线性模型中变量内生性的处理已经有了许多很成熟的方法,但在非参数模型中变量内生性的处理则要困难得多。直接运用工具变量来处理非参数模型中变量的内生性将会遇到所谓的"病态回归问题",从而无法得到函数的一致估计。为此,文章提出采用非参数控制函数法来解决部分线性模型中的变量内生性问题,并且还推导了估计量的一致性和大样本性质。通过数值模拟计算,对比了非参数控制函数法和传统控制函数法在处理部分线性模型中变量内生性的效果,结果显示,非参数控制函数法在拟合优度上的表现优于传统的控制函数法。在实证部分的研究发现,家庭背景对考生的高考成绩有显著的正效应。特别对于低收入家庭而言,家庭收入的增长能够使得孩子的高考成绩有较大的提高。

IMC-PID tuning method based on sensitivity specification for process with time-delay

To overcome the deficiencies addressed in the conventional PID control and improve the dynamic performance and robustness of the system, a simple design and parameters tuning approach of internal model control-PID （IMC-PID） controller was proposed for the first order plus time-delay （FOPTD） process and the second order plus time-delay （SOPTD） process. By approximating the time-delay term of the process model with the first-order Taylor series, the expressions for IMC-PID controller parameters were derived, and they had only one adjustable parameter 2 which was directly related to the dynamic performance and robustness of the system. Moreover, an analytical approach of selecting 2 was given based on the maximum sensitivity Ms. Then, the robust tuning of the system could be achieved according to the value of Ms. In addition, the proposed method could be extended to the integrator plus time-delay （IPTD） process and the first order delay integrating （FODI） process. Simulation studies were carried out on various processes with time-delay, and the results show that the proposed method could provide a better dynamic performance of both the set-point tracking and disturbance rejection and robustness against parameters perturbation.

Chemical process dynamic optimization based on hybrid differential evolution algorithm integrated with Alopex

To solve dynamic optimization problem of chemical process (CPDOP), a hybrid differential evolution algorithm, which is integrated with Alopex and named as Alopex-DE, was proposed. In Alopex-DE, each original individual has its own symbiotic individual, which consists of control parameters. Differential evolution operator is applied for the original individuals to search the global optimization solution. Alopex algorithm is used to co-evolve the symbiotic individuals during the original individual evolution and enhance the fitness of the original individuals. Thus, control parameters are self-adaptively adjusted by Alopex to obtain the real-time optimum values for the original population. To illustrate the whole performance of Alopex-DE, several varietal DEs were applied to optimize 13 benchmark functions. The results show that the whole performance of Alopex-DE is the best. Further, Alopex-DE was applied to solve 4 typical CPDOPs, and the effect of the discrete time degree on the optimization solution was analyzed. The satisfactory result is obtained.

A New Tuning Method for Two-Degree-of-Freedom Internal Model Control under Parametric Uncertainty

Internal model control （IMC） yields very good performance for set point tracking, but gives sluggish response for disturbance rejection problem. A two-degree-of-freedom IMC （2DOF-IMC） has been developed to overcome the weakness. However, the setting of parameter becomes a complicated matter if there is an uncertainty model. The present study proposes a new tuning method for the controller. The proposed tuning method consists of three steps. Firstly, the worst case of the model uncertainty is determined. Secondly, the parameter of set point con- troller using maximum peak （Mp） criteria is specified, and finally, the parameter of the disturbance rejection con- troller using gain margin （GM） criteria is obtained. The proposed method is denoted as Mp-GM tuning method. The effectiveness of Mp-GM tuning method has evaluated and compared with IMC-controller tuning program （IMCTUNE） as bench mark. The evaluation and comparison have been done through the simulation on a number of first order plus dead time （FOPDT） and higher order processes. The FOPDT process tested includes processes with controllability ratio in the range 0.7 to 2.5. The higher processes include second order with underdarnped and third order with nonminimum phase processes. Although the two of higher order processes are considered as difficult processes, the proposed Mp-GM tuning method are able to obtain the good controller parameter even under process uncertainties.

Optimal non-fragile controller realization algorithm and application to control problems

To reduce the fragility encountered in controller implementation, which is a measure of extent to describe small perturbations in controller parameters caused by rounding-off errors or component tolerances, and keep the system stability and performance, approaches of weighted eigenvalue sensitivity and stability radii comparison were used for computation and reduction of controller fragility. An algorithm has been derived for the efficient reduction of controller fragility, which used eigenstructure decomposition to obtain the suboptimal solution. The algorithm was tested for different control problems through reducing their fragility by a large margin. Different canonical forms were analyzed for fragility, including controllable canonical form, observable canonical form, modal canonical form, balanced realization and optimal (non-fragile) form. Different realizations were implemented through C language Matlab EXecutable (CMEX) S-function discrete state space block. Double precision calculations were performed. Open and closed loop controller realizations were compared with simulink state space (optimal) block. Results of comparison indicate that the optimal non-fragile controller realization shows better results both in open loop and closed loop realization.

Fuzzy controller based on chaos optimal design and its application

In order to overcome difficulty of tuning parameters of fuzzy controller, a chaos optimal design method based on annealing strategy is proposed. First, apply the chaotic variables to search for parameters of fuzzy contro-(ller,) and transform the optimal variables into chaotic variables by carrier-wave method. Making use of the intrinsic stochastic property and ergodicity of chaos movement to escape from the local minimum and direct optimization searching within global range, an approximate global optimal solution is obtained. Then, the chaos local searching and optimization based on annealing strategy are cited, the parameters are optimized again within the limits of the approximate global optimal solution, the optimization is realized by means of combination of global and partial chaos searching, which can converge quickly to global optimal value. Finally, the third order system and discrete nonlinear system are simulated and compared with traditional method of fuzzy control. The results show that the new chaos optimal design method is superior to fuzzy control method, and that the control results are of high precision, with no overshoot and fast response.

Robust parametric approach for tracking control of an air-breathing hypersonic cruise vehicle

To realize the stabilization and the tracking of flight control for an air-breathing hypersonic cruise vehicle, the linearization of the longitudinal model under trimmed cruise condition is processed firstly. Furthermore, the flight control problem is formulated as a robust model tracking control problem. And then, based on the robust parametric approach, eigenstructure assignment and reference model tracking theory, a parametric optimization method for robust controller design is presented. The simulation results show the effectiveness of the proposed approach.

Hybrid Improved Self-adaptive Differential Evolution and Nelder-Mead Simplex Method for Solving Constrained Real-Parameters

In this paper, a new hybrid algorithm based on exploration power of a new improvement self-adaptive strategy for controlling parameters in DE （differential evolution） algorithm and exploitation capability of Nelder-Mead simplex method is presented （HISADE-NMS）. The DE has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters as number of particles （NP）, scaling factor （F） and crossover control （CR）, which are kept fixed throughout the entire evolutionary process. However, these control parameters are very sensitive to the setting of the control parameters based on their experiments. The value of control parameters depends on the characteristics of each objective function, therefore, we have to tune their value in each problem that mean it will take too long time to perform. In the new manner, we present a new version of the DE algorithm for obtaining self-adaptive control parameter settings. Some modifications are imposed on DE to improve its capability and efficiency while being hybridized with Nelder-Mead simplex method. To valid the robustness of new hybrid algorithm, we apply it to solve some examples of structural optimization constraints.

New parameter tuning method of washout filter-aided controller for dynamic behavior adjustment

Stabilizing unstable operating points is an effective way to enhance process benefits and safety, which motivates the development for a variety of advanced control strategies. The washout filter-aided controller(WFC), originally used for electric power system and aircraft, has been introduced to adjust the dynamic behavior of chemical process. However, the parameter tuning method faces two major limitations: the dimension of operating variables must be equal to or greater than that of state variables and only one positive real eigenvalue exists in the open loop system. To overcome the two limitations, this paper proposes a new parameter tuning method, so that the WFC is applicable in most chemical processes. By solving a constrained optimization problem, the controller parameters are determined under the constraint that the reassignment of the eigenvalues of the unstable desired operating point can satisfy the stability condition. Thus parts of the equilibrium manifold including the desired operating point are stabilized without affecting the shape of the equilibrium manifold. Finally, the effectiveness of the WFC improved by the proposed parameter tuning method is illustrated through a case study for propanediol anaerobic fermentation.

各向异性Chaboche黏塑性本构方程隐式应力积分算法

针对各向异性Chaboche黏塑性本构方程,利用有效参数控制法推导了该方程的隐式积分算法,该算法把所有未知量都用同一个控制参数表示,并形成控制方程,从而把本构方程应力积分的问题转化成一个非线性控制方程的求解问题.该积分算法程序,与通用有限元软件Marc结合,通过单个单元对单向拉伸、循环、松弛的响应的实验数据进行了数值模拟,通过与显式算法对比,该隐式算法的稳定性和收敛性有所提高.构件的对比分析也表明隐式算法比显式算法具有较高的效率.

Research on Power Control of Wind Power Generation Based on Neural Network Adaptive Control

For the characteristics of wind power generation system is multivariable, nonlinear and random, in this paper the neural network PID adaptive control is adopted. The size of pitch angle is adjusted in time to improve the perfomance of power control. The PID parameters are corrected by the gradient descent method, and Radial Basis Functiion （RBF） neural network is used as the system identifier in this method. Sinlation results show that by using neural network adaptive PID controller the generator power control can inhibit effectively the speed and affect the output prover of generator. The dynamic performnce and robustness of the controlled system is good, and the peformance of wind power system is improved.

A novel current vector decomposition controller design for six-phase permanent magnet synchronous motor

The vector control algorithm based on vector space decomposition （VSD） transformation method has a more flexible control freedom, which can control the fundamental and harmonic subspace separately. To this end, a current vector decoupling control algorithm for six-phase permanent magnet synchronous motor （PMSM） is designed. Using the proposed synchronous rotating coordinate transformation matrix, the fundamental and harmonic components in d-q subspace are changed into direct current （DC） component, only using the traditional proportional integral （PI） controller can meet the non-static difference adjustment, and the controller parameter design method is given by employing intemal model principle. In addition, in order to remove the 5th and 7th harmonic components of stator current, the current PI controller parallel with resonant controller is employed in x-y subspace to realize the specific harmonic component compensation. Simulation results verify the effectiveness of current decoupling vector controller.

ADAPTIVE TRACKING OF A CLASS OF FIRST-ORDER SYSTEMS WITH BINARY-VALUED OBSERVATIONS AND FIXED THRESHOLDS

This paper considers the adaptive tracking problem for a class of first-order systems with binary-valued observations generated via fixed thresholds. A recursive projection algorithm is proposed for parameter estimation based on the statistical properties of the system noise. Then, an adaptive control law is designed via the certainty equivalence principle. By use of the conditional expectations of the innovation and output prediction with respect to the estimates, the closed-loop system is shown to be stable and asymptotically optimal. Meanwhile, the parameter estimate is proved to be both almost surely and mean square convergent, and the convergence rate of the estimation error is also obtained. A numerical example is given to demonstrate the efficiency of the adaptive control law.