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Based on Parzen Window estimation and Renyi \\ 's dynamic random entropy of distributed control system output

Author: HanZhiPing
Tutor: YangChengZhi
School: Kunming University of Science and Technology
Course: Systems Engineering
Keywords: Probability density function (PDF) Parzen window estimate Renyi's entropy Randomly distributed control Parameter correction
CLC: TP13
Type: Master's thesis
Year: 2009
Downloads: 43
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Abstract


Stochastic system control is the control theory and applications important and fundamental issues. The traditional idea of ??stochastic control system controls the output of the random system statistics such as the mean and variance characteristics, mainly applicable to a Gaussian random process. In recent years, the control system of the probability density function (PDF) become a new stochastic system control method. In this paper, a random distribution of controlled stochastic systems that control the general shape of the output PDF, this control main advantage is the ability to solve the problem of non-Gaussian system control, while the Gaussian system control is one of a kind special form, so the more general . In this paper, a new performance index creation, control algorithms and application examples in-depth study, involving dynamic stochastic systems of many basic issues, including dynamic stochastic system origin, background, significance, modeling, control, systems analysis, etc. and so on. In this paper, the main research work are: (1) is introduced into the Parzen window to Renyi's entropy function, obtaining a new performance index function, the use of partial differential equations partial derivative of the performance index, the gradient correction principle according to the system , modified PID parameters, while making the minimum entropy value, to obtain a new control algorithms. To verify the feasibility of the algorithm, using the simulation will be described. Simulation of two situations: the system exists in the Gaussian and non-Gaussian interference signal interference signals. When there are small amplitude Gaussian interference signal can still use the traditional PID controller for control purposes, but the use of the control algorithm presented in this paper can be optimized controller parameters, can get better control effect. When there is significant value Gaussian interference signals, the traditional PID control performance is relatively poor, and even can not control, while the use of this thesis, the control algorithm to achieve control purposes. When there are non-Gaussian interference signal, the same, the traditional PID control performance is relatively poor, and even can not control, and this paper by rib proposed control algorithm can realize control purposes. In order to fully explain the simulation results, we have come to the system output tracking a given graph, entropy curves, parameter correction and output distribution map three-dimensional map, obtained through the analysis: basic tracking system output signal can be given signal, entropy as parameters constantly revised, becoming smaller and smaller, and stabilized output distribution to achieve results in line with expectations. (2) application of the control algorithm mentioned in this article to an industrial furnace furnace temperature control system to verify the usefulness of this algorithm. Mainly studied the temperature distribution in the furnace chamber, when the system is non-Gaussian interference signal exists, because the furnace temperature distribution can be output in a non-Gaussian PDF that the application of the control algorithm, such that the output tracking given. Similarly, from the analysis of a given output tracking, entropy curve correction curve parameters, and output three-dimensional map, we can see, this paper proposed a new control algorithm has good practicability.

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CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Automatic control theory
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