先进控制技术在波浪发电系统中的应用

由于波浪储量丰富,具有随机性,如何控制波能转换系统捕获最大波能和控制并网电能质量成为波浪发电的核心问题。简述了波能转换装置实现最大波能捕获的方法,综述了滑模变结构控制、自适应控制、最优控制、智能算法、模糊控制、无源控制在控制最大波能捕获以及改善电能质量方面的研究成果。并提出未来的控制算法应是多种先进控制算法相结合。     

局部阴影下光伏阵列MPPT算法的研究

针对局部阴影状态下光伏阵列P-U特性曲线多峰值的问题,提出了一种基于搜索-计算-判断的三步法全局最大功率点跟踪(GMPPT)策略。该方法使用改进型扰动观察法反向搜索第一个峰值点,利用计算和判断减小搜索区域,将多峰值间接转化为单峰值搜索,解决了搜索过程中陷入局部极值的问题。通过建立3种阴影状态下的模型,将该方法与现有最大功率点跟踪(MPPT)算法进行仿真对比,并建立相应的试验进行验证。仿真及试验结果表明,该方法在有、无阴影状态下均能稳定实现GMPPT,有效地提高了系统的跟踪精度和跟踪速度。     

晶化机制与激活能的晶化速率参比法确定

本文根据修正的Kissinger公式提出一种确定非晶材料晶化机制与激活能的最大晶化速率参比法。以Ar_(70)Cu_(30)非晶合金为例,研究了晶化机制与激活能及其与压力的关系。     

V形件弯曲凹模最小深度的确定

该文指出了目前广泛使用的经验查表法确定V形件弯曲凹模深度的不合理性，分析了凹模斜壁的作用及其与圆角半径的相互关系，提出了凹模最小的深度的概念和计算公式。     

均相催化水合法合成乙二醇动力学研究

在反应温度为45～75℃,NY 健化剂浓度为0.093mol/L,水比为6～10的反应条件下,对均相催化水合法合成乙二醇动力学进行了研究。测定了反应速率常数及反应过程中溶液 pH 值的变化。依据实验结果,提出了反应机理,建立了反应动力学方程,并利用 Levenberg-Marquardt 方法回归了动力学参数。研究结果表明:在 NY 催化剂存在下,均相催化水合法合成乙二醇反应对环氧乙烷浓度是一级反应,其表观活化能为71113.8 J/mol 和指前因子3.05×10~9 min~(-1)。相对直接水合法而言,NY 催化剂降低了反应的活化能,大大提高了反应速度。     

抗水合氧化铝载体研究进展

氧化铝系载体用于含水或有水生成的催化过程时，均会发生再水合现象，从而造成催化剂强度的下降，并导致其比表面积大幅下降，使催化剂不可逆失活。镁铝尖晶石的抗水合性远高于氧化铝系载体，是一种很好的催化剂载体。综述了氧化铝系载体的再水合现象、改进载体抗水合性能的方法以及镁铝尖晶石粉体和载体的制备方法及改进措施。     

Estimation in Random Coefficient Autoregressive Models

Abstract. We propose the quasi‐maximum likelihood method to estimate the parameters of an RCA(1) process, i.e. a random coefficient autoregressive time series of order 1. The strong consistency and the asymptotic normality of the estimators are derived under optimal conditions.     

ON THE UNIMODALITY OF THE EXACT LIKELIHOOD FUNCTION FOR NORMAL AR(2) SERIES

Abstract. For stationary second-order autoregressive normal processes, the conjecture of uniqueness of the solution of the exact likelihood equations is examined. A sufficient condition for uniqueness is given; this condition is satisfied with very high probability if the number of observations is not extremely small. Moreover, it is shown that not more than two maxima may exist. Examples of data which actually produce a likelihood function with two local maxima are given.     

Electrochemical characteristics for redox systems at nano-honeycomb diamond

Electrochemical characteristics for several redox systems at diamond films with highly ordered nanometer-scale cylindrical pores (‘nano-honeycombs’) were examined with cyclic voltammetry (CV) and electrochemical impedance measurements. The cyclic voltammetric anodic-cathodic peak separations for these nano-honeycomb electrodes were in the same range as those for polished polycrystalline diamond films, indicating that the involvement of the oxygen-terminated surface of the nano-pore walls, which should give rise to large peak separations for certain redox couples was only slight. Moreover, the peak currents in the CV were not enhanced to the extent expected on the basis of the roughness factors of the nano-honeycomb films. Ac impedance plots results indicated the existence of a concentration gradient of the reactant in the nano-pores, which is in agreement with theoretical predictions for charge transfer reactions in porous electrodes. The average concentration of the reactant (Fe^2+/3+) inside the nano-pores was a factor of ca. 80 lower than that in the bulk electrolyte. The results of the impedance analysis also indicated an increase in the reaction resistances with decreasing pore diameters.     

SOME PROPERTIES OF THE MAXIMUM LIKELIHOOD ESTIMATOR IN THE SIMULTANEOUS SWITCHING AUTOREGRESSIVE MODEL

Abstract. The simultaneous switching autoregressive (SSAR) model proposed by Kunitomo and Sato (A non-linearity in economic time series and disequilibrium econometric models. In Theory and Application of Mathematical Statistics (ed. A. Takemura). Tokyo:University of Tokyo Press (in Japanese), 1994; Asymmetry in economic time series and simultaneous switching autoregressive model. Struct. Change Econ. Dyn. , forthcoming (1994).) is a Markovian non-linear time series model. We investigate the finite sample as well as the asymptotic properties of the least squares estimator and the maximum likelihood (ML) estimator. Due to a specific simultaneity involved in the SSAR model, the least squares estimator is badly biased. However, the ML estimator under the assumption of Gaussian disturbances gives reasonable estimates.