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排序方式: 共有373条查询结果,搜索用时 15 毫秒
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Paranagamage S.A.Peiris Shaahin Filizadeh Dharshana Muthumuni 《Journal of Modern Power System and Clean Energy》2024,12(2):584-596
Power converters and their interfacing networks are often treated as modular state-space blocks for small-signal stability studies in microgrids; they are interconnected by matching the input and output states of the network and converters. Virtual resistors have been widely used in existing models to generate a voltage for state-space models of the network that require voltage inputs. This paper accurately quantifies the adverse impacts of adding the virtual resistance and proposes an alternative method for network modelling that eliminates the requirement of the virtual resistor when interfacing converters with microgrids. The proposed nonlinear method allows initialization, time-domain simulations of the nonlinear model, and linearization and eigenvalue generation. A numerically linearized small-signal model is used to generate eigenvalues and is compared with the eigenvalues generated using the existing modelling method with virtual resistances. Deficiencies of the existing method and improvements offered by the proposed modelling method are clearly quantified. Electromagnetic transient(EMT) simulations using detailed switching models are used for validation of the proposed modelling method. 相似文献
3.
Piero Barone 《时间序列分析杂志》1987,8(2):125-130
Abstract. A method for generating finite independent realizations of a normal multivariate stationary ARMA( p, q ) process is proposed. It is based on an AR (1) representation of an ARMA( p, q ) process allowing for an exact generation of the initial values of the simulation algorithm. Input facilities are supplied in order to assure stationarity and invertibility of the considered process. 相似文献
4.
针对Simitsis[1,2]等人提出的ETL过程优化算法中存在不足之处,提出了改进的启发式搜索算法,实验证明改进后的算法较好地降低了实际执行的代价,解决了原算法的短视性。 相似文献
5.
针对工业生产过程中噪声往往为有色噪声的情况,提出一种改进的子空间辨识方法。传统的子空间辨识方法在系统存在有色噪声时辨识效果不佳,改进方法则采用变换系统模型形式来克服有色噪声对系统的影响,在辨识时直接利用变换系统模型后的数据得到系统较为准确的状态空间模型,实践证明,状态空间模型更适用于工业过程。连续搅拌反应釜(CSTR)系统是一类典型的工业生产系统,将子空间辨识方法应用于CSTR过程的仿真实验,通过比较改进前和改进后的系统预测误差,验证了所提方法的有效性。 相似文献
6.
为了进一步改善传统线性最优励磁控制中的动态性能和调节精度,基于同步发电机的派克模型推导出了供设计线性最优励磁控制规律用的单机无穷大系统的线性化状态空间方程。以该方程为基础,设计了一种同时以机端电压、有功功率、无功功率、角速度、功角作为反馈量的线性最优励磁控制器,将发电机功角、无功功率这两个与稳定性和品质密切相关的重要参量引入控制规律。同时,为了提高机端电压的调节精度,基于稳态调整与动态调节区分开来的思想,将积分调节引入励磁控制规律。通过Matlab进行算例仿真,结果表明所设计的励磁控制规律与传统规律相比,能够有效地提高电力系统在大、小扰动下的稳定性,同时在电压调节精度方面亦有所改善。 相似文献
7.
本文以现代控制理论为基础,引用线性控制系统的空间状态表达式来描述和探讨单个边界条件的确定问题。采用现有较为完善的空间离散方法-有限单元法或有限差分法,通过数值计算以获得较为准确的解。最后,由数值实验的例子来表明所采用方法的合理性和可靠性。 相似文献
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9.
Federico Bianchi Simone Formentin Luigi Piroddi 《International Journal of Adaptive Control and Signal Processing》2020,34(1):63-76
Kalman filtering for linear systems is known to provide the minimum variance estimation error, under the assumption that the model dynamics is known. While many system identification tools are available for computing the system matrices from experimental data, estimating the statistics of the output and process noises is still an open problem. Correlation-based approaches are very fast and sufficiently accurate, but there are typically restrictions on the number of noise covariance elements that can be estimated. On the other hand, maximum likelihood methods estimate all elements with high accuracy, but they are computationally expensive, and they require the use of external optimization solvers. In this paper, we propose an alternative solution, tailored for process noise covariance estimation and based on stochastic approximation and gradient-free optimization, that provides a good trade-off in terms of performance and computational load, and is also easy to implement. The effectiveness of the method as compared to the state of the art is shown on a number of recently proposed benchmark examples. 相似文献
10.
Michael Pauley Christopher Mclean Jonathan H. Manton 《International Journal of Adaptive Control and Signal Processing》2020,34(7):813-838
A class of discrete-time random processes arising in engineering and econometrics applications consists of a linear state-space model whose parameters are modulated by the state of a finite-state Markov chain. Typical filtering approaches are collapsing methods, which approximate filtered distributions by mixtures of Gaussians, each Gaussian corresponding to one possibility of the recent history of the Markov chain, and particle methods. This article presents an alternative approach to filtering these processes based on keeping track of the values of the underlying filtered density and its characteristic function on grids. We prove that it has favorable convergence properties under certain assumptions. On the other hand, as a grid method, it suffers from the curse of dimensionality, and so is only suitable for low-dimensional systems. We compare our method to collapsing filters and a particle filter with examples, and find that it can outperform them on 1- and 2-dimensional problems, but loses its speed advantage on 3-dimensional systems. Meanwhile, our method has a proven theoretical convergence rate that is probably not achieved by collapsing and particle methods. 相似文献