精密力源多维模糊控制的探讨

针对比对式测力机源系统力值自动调节中存在参数变化的变速扰动环节和滞后量变化的滞后环节,从而给自动调节带来很大难度的问题,采用多维模糊模型进行预测和采用多维模糊控制作为调节的算法。有效地消除了扰动和滞后的影响,实现了高精度的力值调节控制。     

Solutions of Multi-dimensional Hyperbolic Systems of Conservation Laws by Square Entropy Condition Satisfying Discontinuous Galerkin Method

In this paper, we study formally high-order accurate discontinuous Galerkin methods on general arbitrary grid for multi-dimensional hyperbolic systems of conservation laws [Cockburn, B., and Shu, C.-W. (1989, Math. Comput. 52, 411–435, 1998, J. Comput. Phys. 141, 199–224); Cockburn et al. (1989, J. Comput. Phys. 84, 90–113; 1990, Math. Comput. 54, 545–581). We extend the notion of E-flux [Osher (1985) SIAM J. Numer. Anal. 22, 947–961] from scalar to system, and found that after flux splitting upwind flux [Cockburn et al. (1989) J. Comput. Phys. 84, 90–113] is a Riemann solver free E-flux for systems. Therefore, we are able to show that the discontinuous Galerkin methods satisfy a cell entropy inequality for square entropy (in semidiscrete sense) if the multi-dimensional systems are symmetric. Similar result [Jiang and Shu (1994) Math. Comput. 62, 531–538] was obtained for scalar equations in multi-dimensions. We also developed a second-order finite difference version of the discontinuous Galerkin methods. Numerical experiments have been obtained with excellent results.      

Treatment of skewed multi-dimensional training data to facilitate the task of engineering neural models

Successful application of neural network models relies heavily on problem-dependent internal parameters. As the theory does not facilitate the choice of the optimal parameters of neural models, these can solely be obtained through a tedious trial-and-error process. The process requires performing multiple training simulations with various network parameters, until satisfactory performance criteria of a neural model are met. In literature, it has been shown that neural models are not consistently good in prediction under highly skewed data. Consequently, the cost of engineering neural models rises in such circumstance to seek for appropriate internal parameters. In this paper the aim is to show that a recently proposed treatment of highly skewed data eases the task of practitioners in engineering neural network models to meet satisfactory performance criteria. As the applications of neural models grows dramatically in diverse engineering domains, the understanding of the treatment show indispensable practical values.     

The load-balanced multi-dimensional bin-packing problem

The bin-packing problem is one of the most investigated and applicable combinatorial optimization problems. In this paper we consider its multi-dimensional version with the practical extension of load balancing, i.e. to find the packing requiring the minimum number of bins while ensuring that the average center of mass of the loaded bins falls as close as possible to an ideal point, for instance, the center of the bin. We formally describe the problem using mixed-integer linear programming models, from the simple case where we want to optimally balance a set of items already assigned to a single bin, to the general balanced bin-packing problem. Given the difficulty for standard solvers to deal even with small size instances, a multi-level local search heuristic is presented. The algorithm takes advantage of the Fekete–Schepers representation of feasible packings in terms of particular classes of interval graphs, and iteratively improves the load balancing of a bin-packing solution using different search levels. The first level explores the space of transitive orientations of the complement graphs associated with the packing, the second modifies the structure itself of the interval graphs, the third exchanges items between bins repacking proper n-tuples of weakly balanced bins. Computational experiments show very promising results on a set of 3D bin-packing instances from the literature.     

蝇蛆分离用多维振动筛运动学分析及仿真

针对蝇蛆养殖行业中,蛆料分离技术的落后、机械化程度低、自动化程度低等缺陷,提出了一种蝇蛆分离用1T2R并联式振动筛,能够实现沿z轴的平移、绕x轴的转动和绕y轴的转动,可以高效地实现蛆料的分离。首先对该机构进行运动学建模,并且给出了运动学的正解和反解,将建立的运动学数学模型导入Matlab中,得到理论运动曲线;并且在Pro/E中建立该振动筛的虚拟样机模型,利用Mech/Pro给虚拟样机添加运动副并导入到ADAMS软件中,添加驱动后得到仿真运动曲线。结果显示仿真曲线与理论曲线完全一致,从而验证运动学数学模型的正确性。     

A new discretization of space for the solution of multi-dimensional population balance equations

In this work, a novel radial grid is combined with the framework of minimal internal consistency of discretized equations of Chakraborty and Kumar [2007. A new framework for solution of multidimensional population balance equations. Chemical Engineering Science 62, 4112-4125] to solve n-dimensional population balance equations (PBEs) with preservation of (n+1) instead of 2ⁿ properties required in direct extension of the 1-d fixed pivot technique of Kumar and Ramkrishna [1996a. On the solutions of population balance equation by discretization-I. A fixed pivot technique. Chemical Engineering Science 51, 1311-1332]. The radial grids for the solution of 2-d PBEs are obtained by intersecting arbitrarily spaced radial lines with arcs of arbitrarily increasing radii. The quadrilaterals obtained thus are divided into triangles to represent a non-pivot particle in 2-d space through three surrounding pivots by preserving three properties, the number and the two masses of the species that constitute the newly formed particle. Such a grid combines the ease of generating and handling a structured grid with the effectiveness of the framework of minimal internal consistency. A new quantitative measure to supplement visual comparison of two solutions is also introduced. The comparison of numerical and analytical solutions of 2-d PBEs for a number of uniform and selectively refined radial grids shows that the quality of solution obtained with radial grids is substantially better than that obtained with the direct extension of the 1-d fixed pivot technique to higher dimensions for both size independent and size dependent aggregation kernels. The framework of Chakraborty and Kumar combined with the proposed 2-d radial grid, which offers flexibility and achieves both reduced numerical dispersion and the ease of implementation, appears as an effective extension of the widely used 1-d fixed pivot technique to solve 2-d PBEs.     

A multi-dimensional fuzzy decision support strategy

Based on the theory of fuzzy pattern recognition and fuzzy optimization, this paper presents a kind of multi-dimensional fuzzy decision support strategy for multi-objective and multi-layer fuzzy decision support systems. Compared with conventional strategies of fuzzy optimization that just considers the relative membership u_j of decision j of down layer unit systems, this strategy also takes the relative bad membership u_j^b=1−u_j as the input of up layer unit systems. Besides, unlike conventional strategies of fuzzy optimization, this strategy can provide multi-dimensional information to the decision-maker. With these advantages, this strategy founds a new theoretical basis for the multi-dimensional decision making of large systems.     

二维阻尼／无阻尼谐波的状态空间复合描述与参数估计

本文提出了二维阻尼／无阻尼谐波的一种状态空间复合描述方法。在此基础上，通过了辨识状态间模型的参数获得了二维谐波的参数估计，这种新的估计方法既实现了分维处理，又避免了配对问题，仿真结果表明了该方法的有效性。