本文關(guān)鍵詞： 智能家居 照明系統(tǒng) 數(shù)據(jù)融合 模糊控制 神經(jīng)網(wǎng)絡(luò)　出處：《河北工業(yè)大學(xué)》2014年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：智能家居作為一個(gè)迅速崛起的新型行業(yè)，，它擁有巨大的市場(chǎng)前景和令人驚訝的發(fā)展?jié)摿Γ?1世紀(jì)最具投資價(jià)值的新銳項(xiàng)目。 現(xiàn)有的智能家居控制系統(tǒng)的控制器的控制模式只能按預(yù)設(shè)的控制規(guī)則和方式單一“機(jī)械式”的以自動(dòng)化方式反復(fù)運(yùn)行，周?chē)h(huán)境變化時(shí)，系統(tǒng)就會(huì)失控，人性化服務(wù)較差。照明系統(tǒng)作為智能家居組成部分，對(duì)智能家居的整體研究有重大意義，筆者研究學(xué)習(xí)了模糊控制和神經(jīng)網(wǎng)絡(luò)控制算法后，提出了一個(gè)擁有自我學(xué)習(xí)、自我分析判斷、自我預(yù)測(cè)功能的智能家居照明控制方式，基于模糊數(shù)學(xué)理論對(duì)控制方式進(jìn)行建模研制設(shè)計(jì)研究，將照明系統(tǒng)人性化智能化不再是遐想。 以智能家居照明系統(tǒng)為研究對(duì)象，引入多傳感器數(shù)據(jù)融合技術(shù)，對(duì)傳感器的特征層進(jìn)行融合，利用實(shí)時(shí)數(shù)據(jù)，在一定規(guī)則下進(jìn)行數(shù)據(jù)的分析處理，獲取被控制對(duì)象一致性的特征數(shù)據(jù)，來(lái)完成控制任務(wù)。對(duì)照明控制系統(tǒng)的整體框架進(jìn)行了構(gòu)造，根據(jù)智能家居室內(nèi)特點(diǎn)，對(duì)光環(huán)境進(jìn)行了分析和場(chǎng)景設(shè)置。將模糊控制和神經(jīng)網(wǎng)絡(luò)控制技術(shù)嵌入到照明系統(tǒng)的控制算法進(jìn)行研究，對(duì)各自算法進(jìn)行了公式分析推導(dǎo)，利用神經(jīng)網(wǎng)絡(luò)的自學(xué)習(xí)能力對(duì)光環(huán)境樣本數(shù)據(jù)進(jìn)行訓(xùn)練，來(lái)調(diào)整模糊控制推理系統(tǒng)的模糊規(guī)則和隸屬度函數(shù)的參數(shù)，最終確定了基于Mamdani推理的BP神經(jīng)網(wǎng)絡(luò)控制方式，并運(yùn)用模糊神經(jīng)網(wǎng)絡(luò)在Matlab中進(jìn)行建模與仿真訓(xùn)練，使控制系統(tǒng)具有了自我學(xué)習(xí)、自我判斷、自我預(yù)測(cè)的功能，實(shí)現(xiàn)智能家居照明系統(tǒng)的智能化、人性化服務(wù)功能。研制設(shè)計(jì)完成了基于STM32為智能家居照明系統(tǒng)的智能控制中心研制設(shè)計(jì)，為了降低設(shè)備功耗和研制設(shè)計(jì)成本，無(wú)線信息采集和傳輸模塊以2.4G技術(shù)為背景，采用CC2530作為主控芯片對(duì)智能控制節(jié)點(diǎn)研制設(shè)計(jì)，通過(guò)MDK進(jìn)行程序代碼的編程與仿真。對(duì)調(diào)光電路、人體感應(yīng)電路及測(cè)光強(qiáng)弱電路進(jìn)行了硬件研制設(shè)計(jì)。軟件設(shè)計(jì)引用了IEEE.802.15提出的Z-stack協(xié)議棧無(wú)線通訊程序設(shè)計(jì)，完成了無(wú)線燈光節(jié)點(diǎn)與主控制器之間的通信，實(shí)現(xiàn)了多任務(wù)的實(shí)時(shí)性。
[Abstract]:Smart home as a rapidly rising new industry, it has a huge market prospects and surprising development potential, is the most valuable new investment project in 21th century. The control mode of the controller of the existing intelligent home control system can only be operated repeatedly by a single "mechanical" mode according to the preset control rules and modes. When the surrounding environment changes, the system will lose control. As a part of smart home, lighting system is of great significance to the whole research of smart home. After studying fuzzy control and neural network control algorithm, the author puts forward a self-learning system. Self-analysis and judgment, self-prediction function of intelligent home lighting control mode, based on fuzzy mathematics theory to model the design and design of the control mode, lighting system is no longer artificial intelligent daydream. Taking the intelligent home lighting system as the research object, the multi-sensor data fusion technology is introduced to fuse the characteristic layer of the sensor, and the real-time data is used to analyze and process the data under certain rules. In order to complete the control task, the whole frame of the lighting control system is constructed, and according to the indoor characteristics of the intelligent home, the characteristic data of the controlled object are obtained to complete the control task. The fuzzy control and neural network control technology are embedded into the control algorithm of lighting system, and the formulas of their respective algorithms are analyzed and deduced. The self-learning ability of neural network is used to train the light environment sample data to adjust the fuzzy rules of fuzzy control inference system and the parameters of membership function. Finally, the control mode of BP neural network based on Mamdani reasoning is determined. Using fuzzy neural network to model and simulate in Matlab, the control system has the functions of self-learning, self-judgment and self-prediction, so that the intelligent lighting system of intelligent home can be realized. The design of intelligent control center based on STM32 is completed. In order to reduce device power consumption and design cost, wireless information acquisition and transmission module is based on 2.4G technology. The intelligent control node is developed with CC2530 as the main control chip, and the program code is programmed and simulated by MDK. The hardware design of human induction circuit and the circuit of measuring intensity and intensity are carried out. The software design uses the design of wireless communication program of Z-stack protocol stack proposed by IEEE.802.15 to complete the communication between the wireless light node and the main controller. Multi-task real-time is realized.
【學(xué)位授予單位】：河北工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TU855;TM923.0

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 王愛(ài)英,陳仲林,郭平;人工神經(jīng)網(wǎng)絡(luò)用于室內(nèi)照明設(shè)計(jì)[J];四川建筑科學(xué)研究;2000年02期

2 丁正洋;馬小軍;張藝陽(yáng);張健;;基于ZigBee及遺傳神經(jīng)網(wǎng)絡(luò)的隧道照明控制系統(tǒng)[J];電氣應(yīng)用;2011年18期

3 祝世虎;董朝陽(yáng);張金鵬;陳宗基;;基于神經(jīng)網(wǎng)絡(luò)與專(zhuān)家系統(tǒng)的智能決策支持系統(tǒng)[J];電光與控制;2006年01期

4 快思聰;;國(guó)外經(jīng)典智能家居[J];數(shù)字社區(qū)&智能家居;2008年10期

5 簡(jiǎn)小剛;賈鴻盛;石來(lái)德;;多傳感器信息融合技術(shù)的研究進(jìn)展[J];中國(guó)工程機(jī)械學(xué)報(bào);2009年02期

6 曹勝男;劉理云;賀小華;;一種簡(jiǎn)易光控照明電路的設(shè)計(jì)[J];甘肅聯(lián)合大學(xué)學(xué)報(bào)(自然科學(xué)版);2009年01期

7 吳孜祺;;中國(guó)智能家居市場(chǎng)一覽[J];日用電器;2011年07期

8 符紅霞;;ZigBee技術(shù)在家庭智能照明系統(tǒng)中的應(yīng)用[J];工業(yè)控制計(jì)算機(jī);2013年07期

9 ;建筑節(jié)能智能化控制系統(tǒng)[J];數(shù)字社區(qū)&智能家居;2008年10期

10 劉海英,張池平;基于多傳感器信息融合技術(shù)[J];佳木斯大學(xué)學(xué)報(bào)(自然科學(xué)版);2004年01期

本文編號(hào)：1520026