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Linearized Controller Design for the Output Probability Density Functions of Non-Gaussian Stochastic Systems 被引量:1
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作者 Pousga Kabore Husam Baki 《International Journal of Automation and computing》 EI 2005年第1期67-74,共8页
This paper presents a linearized approach for the controller design of the shape of output probability density functions for general stochastic systems. A square root approximation to an output probability density fun... This paper presents a linearized approach for the controller design of the shape of output probability density functions for general stochastic systems. A square root approximation to an output probability density function is realized by a set of B-spline functions. This generally produces a nonlinear state space model for the weights of the B-spline approximation. A linearized model is therefore obtained and embedded into a performance function that measures the tracking error of the output probability density function with respect to a given distribution. By using this performance function as a Lyapunov function for the closed loop system, a feedback control input has been obtained which guarantees closed loop stability and realizes perfect tracking. The algorithm described in this paper has been tested on a simulated example and desired results have been achieved. 展开更多
关键词 Dynamic stochastic systems probability density function B splines neural networks Lyapunov stability theory
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Data Driven Fault Diagnosis and Fault Tolerant Control: Some Advances and Possible New Directions 被引量:44
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作者 WANG Hong CHAI Tian-You +1 位作者 DING Jin-Liang BROWN Martin 《自动化学报》 EI CSCD 北大核心 2009年第6期739-747,共9页
关键词 自动化系统 数据分析 容错控制 故障诊断系统
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Multi-step Predictive Control of a PDF-shaping Problem 被引量:4
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作者 王宏 张金芳 岳红 《自动化学报》 EI CSCD 北大核心 2005年第2期274-279,共6页
A predictive control strategy is proposed for the shaping of the output probability density function (PDF) of linear stochastic systems. The B-spline neural network is used to set up the output PDF model and therefore... A predictive control strategy is proposed for the shaping of the output probability density function (PDF) of linear stochastic systems. The B-spline neural network is used to set up the output PDF model and therefore converts the PDF-shaping into the control of B-spline weights vector. The Diophantine equation is then introduced to formulate the predictive PDF model, based on which a moving-horizon control algorithm is developed so as to realize the predictive PDF tracking performance. 展开更多
关键词 多步预测控制 概率密度函数 PDF 随机分配控制
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Design of a fault diagnosis scheme for a class of singular nonlinear systems 被引量:3
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作者 Lina YAO Hong WANG 《控制理论与应用(英文版)》 EI 2008年第2期122-126,共5页
A new fault detection and diagnosis approach is developed in this paper for a class of singular nonlinear systems via the use of adaptive updating rules. Both detection and diagnostic observers are established, where ... A new fault detection and diagnosis approach is developed in this paper for a class of singular nonlinear systems via the use of adaptive updating rules. Both detection and diagnostic observers are established, where Lyapunov stability theory is used to obtain the required adaptive tuning rules for the estimation of the process faults. This has led to stable observation error systems for both fault detection and diagnosis. A simulated numerical example is included to demonstrate the use of the proposed approach and encouraging results have been obtained. 展开更多
关键词 Fault detection Fault diagnosis SINGULAR Nonlinear systems Adaptive update rules
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