Fuzzy Control Model for Structural Health Monitoring of Civil Infrastructure Systems
Fuzzy Control Model for Structural Health Monitoring of Civil Infrastructure Systems作者机构：Department of Engineering Texas Southern University Houston Texas 77004 USA
出 版 物：《Journal of Control Science and Engineering》 (控制科学与工程（英文版）)
年 卷 期：2015年第3卷第1期
页 面：9-20页
学科分类：0711[理学-系统科学] 07[理学] 08[工学] 070105[理学-运筹学与控制论] 081101[工学-控制理论与控制工程] 071101[理学-系统理论] 0811[工学-控制科学与工程] 0701[理学-数学]
主 题：Structural health monitoring fuzzy control semi-Markov decision process wireless sensors civil infrastructuresystems.
摘 要：This paper presents a Fuzzy Control Model for SHM （Structural Health Monitoring） of civil infrastructure systems. Two important considerations of this model are （a） effective control of structural mechanism to prevent damage of civil infrastructure systems, and （b） energy-efficient data transmissions. Fuzzy Logic is incorporated into the model to provide （a） capability for handling imprecision and non-statistical uncertainty associated with structural monitoring, and （b） framework for effective control of the mechanism of civil infrastructure systems. Moreover, wireless smart sensors are deployed in the model to measure dynamic response of civil infrastructure systems to structural excitation. The operation of these wireless smart sensors is characterized as discounted SMDP （Semi-Markov Decision Process） consisting of two states, namely： sensing/processing and transmitting/receiving. The objective of the SMDP-based measurement scheme is to choose policy that offers optimal energy-efficient transmission of measured value of vibration-based dynamic response. Depending on the net magnitude of measured dynamic responses to excitation signals, data may （or may not） be transmitted to the Fuzzy control segment for appropriate control of the mechanism of civil infrastructure systems. The efficacy of this model is tested via numerical analysis, which is implemented in MATLAB software. It is shown that this model can provide energy-efficient structural health monitoring and effective control of civil infrastructure systems.
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