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在简单介绍高程系统的基础上,对影响GPS高程精度的几何水准联测误差、卫星分布不对称、星历误差、多路径误差等因素逐一进行了分析,并提出了相应的改进措施。同时,还对高程拟合使用的稳健估计方法进行了探讨。 相似文献
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本文研究了离散LQ调节器系统鲁棒稳定性问题,稳定的不确定参数是通过考虑参数摄动的方向而求得的,这种方法比现有文献提供的结果具有更好的稳定范围。 相似文献
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A genetic algorithm for the optimisation of assembly sequences 总被引:6,自引:0,他引:6
This paper describes a Genetic Algorithm (GA) designed to optimise the Assembly Sequence Planning Problem (ASPP), an extremely diverse, large scale and highly constrained combinatorial problem. The modelling of the ASPP problem, which has to be able to encode any industrial-size product with realistic constraints, and the GA have been designed to accommodate any type of assembly plan and component. A number of specific modelling issues necessary for understanding the manner in which the algorithm works and how it relates to real-life problems, are succinctly presented, as they have to be taken into account/adapted/solved prior to Solving and Optimising (S/O) the problem. The GA has a classical structure but modified genetic operators, to avoid the combinatorial explosion. It works only with feasible assembly sequences and has the ability to search the entire solution space of full-scale, unabridged problems of industrial size. A case study illustrates the application of the proposed GA for a 25-components product. 相似文献
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Waste-to-energy based greenhouse heating: exploring viability conditions through optimisation models
An optimisation approach is proposed in order to assess the technical and economic feasibility of a renewable-energy-based greenhouse in North-Eastern Italy. A floor heating system that can exploit a low-temperature heat flow coming from the condenser of a waste-to-energy plant is chosen for the greenhouse and designed developing a non-linear optimisation model, solved by a genetic algorithm. In order to determine under what conditions the combination of a floor-heating-based greenhouse with a waste-to-energy plant can be profitable, a mixed integer optimisation model is introduced to allow selection of the minimum cost fuel solution as a function of different design variables of the greenhouse, such as indoor temperature settings and floor area. The ranges within which the renewable energy solution can lead to significant savings in comparison to traditional fossil fuel are identified both from the point of view of costs and of environmental impact. Furthermore, the sales prices for waste heat that would make investment in the renewable energy solution attractive for potential entrepreneurs are given. 相似文献
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Berlin Wu 《Computational Economics》1994,7(1):37-53
In this paper, the methods of time series for nonlinearity are briefly surveyed, with particular attention paid to a new test design based on a neural network specification. The proposed integrated expert system contains two main components: an identification environment and a robust forecasting design. The identification environment can be viewed as a integrated dynamic design in which cognitive capabilities arise as a direct consequence of their self-organizational properties. The integrated framework used for discussing the similarities and differences in the nonlinear time series behavior is presented. Moreover, its performance in prediction proves to be superior than the former work. For the investigation of robust forecasting, we perform a simulation study to demonstrate the applicability and the forecasting performance. 相似文献
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传统基于干扰噪声协方差矩阵(interference-plus-noise covariance matrix,INCM)重构的鲁棒自适应波束形成(robust adaptive beamformer,RAB)算法在多种样本数据协方差矩阵误差和信号导向向量误差的失配环境中具有较强的鲁棒性,但目前主流的INCM重构法都是对信号和干扰的导向向量通过建立凸优化模型来估计,这带来了很高的计算复杂度。为了解决这个问题,提出了一种低复杂度的基于INCM重构的RAB算法。该算法首先将干扰信号的导向向量分解为对应标称项和误差项的和,然后通过一种子空间方法估计得到误差项的单位向量。接下来对一个Capon空间谱功率最大问题进行求解,得到误差项的模值,以此得到重构的INCM。同时利用Capon空间谱中残差噪声的存在,使用交替投影法估计得到期望信号的导向向量,最后得到所提算法的权重向量。仿真实验表明所提算法在多种误差环境下具有较强鲁棒性的同时,还具有较低的计算复杂度。 相似文献
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This paper addresses the problem of designing robust tracking control for a class of uncertain wheeled mobile robots actuated by brushed direct current motors. This class of electrically‐driven mechanical systems consists of the robot kinematics, the robot dynamics, and the wheel actuator dynamics. Via the backstepping technique, an intelligent robust tracking control scheme that integrates a kinematic controller and an adaptive neural network‐based (or fuzzy‐based) controller is developed such that all of the states and signals of the closed‐loop system are bounded and the tracking error can be made as small as possible. Two adaptive approximation systems are constructed to learn the behaviors of unknown mechanical and electrical dynamics. The effects of both the approximation errors and the unmodeled time‐varying perturbations in the input and virtual‐input weighting matrices are counteracted by suitably tuning the control gains. Consequently, the robust control scheme developed here can be employed to handle a broader class of electrically‐driven wheeled mobile robots in the presence of high‐degree time‐varying uncertainties. Finally, a simulation example is given to demonstrate the effectiveness of the developed control scheme. 相似文献