一类不确定非线性系统的状态参考自适应滑模控制

针对一类非匹配不确定非线性系统。基于状态参考自适应控制算法和滑模控制策略。提出了状态参考自适应反演滑模控制方案，实现了不确定非线性系统的鲁棒输出跟踪。与现有的控制器设计相比，大大降低了控制系统阶次，允许系统存在非参数化的不确定性和未知扰动，增强了控制系统鲁棒性。仿真算例证明了理论研究成果的正确性和鲁棒性。     

基于Matlab无刷电动机模型参考自适应控制的研究与实现

本文在分析无刷电动机数学模型的基础上,建立了控制系统的仿真模型,提出了直流无刷电机调速系统模型参考自适应控制的新方法.在双闭环调速系统中,电流环采用电流滞环控制,转速环采用间接参考模型自适应控制,控制器参数估算采用最小二乘算法.仿真结果表明:这种新型的间接模型参考自适应控制方法响应快、无超调、鲁棒性强、抗干扰能力好,较传统PI控制具有更好的动、静态特性.     

Subjective Probability Intervals: How to Reduce Overconfidence by Interval Evaluation.

Format dependence implies that assessment of the same subjective probability distribution produces different conclusions about over- or underconfidence depending on the assessment format. In 2 experiments, the authors demonstrate that the overconfidence bias that occurs when participants produce intervals for an uncertain quantity is almost abolished when they evaluate the probability that the same intervals include the quantity. The authors successfully apply a method for adaptive adjustment of probability intervals as a debiasing tool and discuss a tentative explanation in terms of a naive sampling model. According to this view, people report their experiences accurately, but they are naive in that they treat both sample proportion and sample dispersion as unbiased estimators, yielding small bias in probability evaluation but strong bias in interval production. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于参数辨识的一种动态补偿数字滤波器

提出了一种能明显改善系统动态性能的动态补偿数字滤波器。分析了动态补偿数字滤波器的基本原理。为了使动态补偿滤波器始终工作在最佳参数状态下,且更具有通用性,结合参数辨识,利用基于Householder变换的自适应最小二乘法对传感器的动态性能进行在线补偿,其特点是数值稳定性好、估计精度高。试验表明:对动态品质较差的双孔悬臂梁式压力传感器进行在线补偿,可以使其动态性能得以较好的改善。     

一种基于VirtualClock的自适应成比例带宽分配算法

该文提出了一种基于VirtualClock算法的自适应成比例带宽分配算法(ProportionalAdaptiveBandwidthAllo-cationAlgorithmBasedonVirtualClock,PABVC)。该算法将所有的业务流分为绑定流和非绑定流,并根据不同流的配置加以调度,从而实现了绑定带宽同时自适应成比例分配带宽的目的。由于算法的各个部分相关性较弱,所以在保留算法框架和核心部分算法的基础上,可以灵活地加以组合,实现不同的算法变种。最后,该文分析了PABVC算法的优缺点,并且提出了今后的研究重点。     

Superior step-size theorem and its application——Parallel variable step-size LMS filters algorithm

In several branches of adaptive filtering algorithms, the least mean square (LMS) algorithm is widely applied in many areas because of its low computational cost, good numerical stability and other features[1]. However, the contradiction between faster convergence and smaller steady-state mean squared error (MSE) affects its performance considerably. Step-size, as the key to the problem, can but offer only one choice of the two demands. Therefore, many variable step-size algorithms were prop…     

Constraint-based performance comparison of multi-dimensional interconnection networks with deterministic and adaptive routing strategies

Several studies have examined the relative performance merits of the torus and hypercube taking into account the channel bandwidth constraints imposed by implementation technology. While the torus has been shown to outperform the hypercube under the constant wiring density constraint, the opposite conclusion has been reached when the constant pin-out constraint is considered. However, all these studies have assumed deterministic routing and have not taken into account the internal hardware cost of routers. This paper re-examines the performance merits of the torus and hypercube using both fully-adaptive and deterministic routing strategies. Moreover, it uses a new cost model which takes into account the internal hardware cost of routers.     

Nonlinear adaptive control for bioreactors with unknown kinetics

We consider a control problem for a single bioreaction occurring in a continuous and well-mixed bioreactor, assuming that the bioreaction's kinetics is not represented by a validated model. We develop a nonlinear controller and prove the global asymptotic stability of the closed-loop system towards the equilibrium corresponding to the set point. Since this control law needs the knowledge of some parameters, we derive an adaptive version of the nonlinear controller and prove again the global asymptotic stability of the closed-loop system. Finally, we show the relevance of our approach on a real-life wastewater treatment plant.     

神经网络自适应控制的研究进展及展望

关于人工神经网络与自适应结合的研究，近年来已成为智能控制学科的热点之一。自适应具有强鲁棒性，神经网络则具有自学习功能和良好的容错能力，神经网络自适应控制由于较好地结合了二者的优点而具有强大的优势。本文系统地综述了神经网络自适应控制的进展，讨论了神经网络自适应的主要模型和算法，并就其存在的一些问题、应用与发展趋势进行了探讨。     

Simple characterisation of a deformable mirror inside a high numerical aperture microscope using phase diversity

We present a simple and versatile scheme for characterising amplitude and phase modulation by an active element, such as a deformable mirror, in the pupil plane of a high NA microscope. By placing a mirror in the vicinity of the focal plane of the objective and recording images of the reflected focal spot on a camera, we show that reliable measurements of the influence function of the mirror actuators in the pupil plane of the objective can be obtained using an iterative electric field retrieval algorithm. Compared to direct wavefront sensors, the proposed method allows characterisation for a variety of objectives with different NA and pupil sizes without modification of the setup, requires minimal space inside the microscope, and can be used with pulsed sources such as used for multiphoton microscopy. In order to validate our method, we compare our data to the results obtained with a Shack-Hartmann wavefront sensor, and show that comparable precision is achieved.