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| 1 | A New Safety Assessment Method Based on Belief Rule Base With Attribute Reliability显示文摘Safety assessment is one of important aspects in health management.In safety assessment for practical systems,three problems exist:lack of observation information,high system complexity and environment interference.Belief rule base with attribute reliability(BRB-r)is an expert system that provides a useful way for dealing with these three problems.In BRB-r,once the input information is unreliable,the reliability of belief rule is influenced,which further influences the accuracy of its output belief degree.On the other hand,when many system characteristics exist,the belief rule combination will explode in BRB-r,and the BRB-r based safety assessment model becomes too complicated to be applied.Thus,in this paper,to balance the complexity and accuracy of the safety assessment model,a new safety assessment model based on BRB-r with considering belief rule reliability is developed for the first time.In the developed model,a new calculation method of the belief rule reliability is proposed with considering both attribute reliability and global ignorance.Moreover,to reduce the influence of uncertainty of expert knowledge,an optimization model for the developed safety assessment model is constructed.A case study of safety assessment of liquefied natural gas(LNG)storage tank is conducted to illustrate the effectiveness of the new developed model. | Zhichao Feng Wei He Zhijie Zhou Xiaojun Ban Changhua Hu Xiaoxia Han | 2021 | IEEE/CAA Journal of Automatica Sinica2021，8，11： | 6 |
| 2 | Stability analysis of the simplest Takagi-Sugeno fuzzy control system using popov criterion 显示文摘 | BAN Xiaojun GAO Xiaozhi HUANG Xianlin | 2007 | International Journal of Innovative Computing Information and Control2007，3，5： | 1 |
| 3 | L2- Stability analysis of proportional Takagi-Sugeno fuzzy controller based control systems 显示文摘 | BAN Xiaojun GAO Xiaozhi HUANG XianLin | 2010 | Intelligent Automation and Soft Computing2010，6，1： | 1 |
| 4 | Stability analysis of the simplest Ta-kagi-Sugeno fuzzy control system using circle criterions显示文摘 | Ban Xiaojun Gao X Z Huang Xianlin | | 0，，20： | 1 |
| 5 | Stability analysis of the simplest Takagi-Sugeno fuzzy control system using Popov criterion显示文摘 | Ban Xiaojun Gao X Z Huang Xianlin | | 0，，05： | 1 |
| 6 | Stability analysis of the simplest Takagi-Sugeno fuzzy control system using circle criterion 显示文摘 | BAN Xiaojun GAO Xiaozhi HUANG Xianlin | 2007 | Information Sciences2007，177，20： | 1 |
| 7 | Analysis of one dimensional and two dimensional fuzzy controllers显示文摘The analytical structures and the correspondin g mathematical properties of the one dimensional and two dimensional fuzzy control lers are first investigated in detail. The nature of these two kinds of fuzzy co ntrollers is next probed from the perspective of control engineering. For the on e dimensional fuzzy controller, it is concluded that this controller is a combin ation of a saturation element and a nonlinear proportional controller, and the s ystem that employs the one dimensional fuzzy controller is the combination of an open-loop control system and a closed-loop control system. For the latter cas e, it is concluded that it is a hybrid controller, which comprises the saturatio n part, zero-output part, nonlinear derivative part, nonlinear proportional par t, as well as nonlinear proportional-derivative part, and the two dimensional f uzzy controller-based control system is a loop-varying system with varying num ber of control loops. | Ban Xiaojun Gao Xiaozhi Huang Xianlin Wu Tianbao | 2006 | Journal of Systems Engineering and Electronics2006，17，2： | 0 |
| 8 | Sensor Fault Diagnosis and Tolerant Control Based on Belief Rule Base for Complex System显示文摘This paper develops a new fault diagnosis and tolerant control framework of sensor failure(SFDTC)for complex system such as rockets and missiles.The new framework aims to solve two problems:The lack of data and the multiple uncertainty of knowledge.In the SFDTC framework,two parts exist:The fault diagnosis model and the output reconstruction model.These two parts of the new framework are constructed based on the new developed belief rule base with power set(BRB-PS).The multiple uncertainty of knowledge can be addressed by the local ignorance and global ignorance in the new developed BRB-PS model.Then,the stability of the developed framework is proved by the output error of the BRB-PS model.For complex system,the sensor state is determined by many factors and experts cannot provide accurate knowledge.The multiple uncertain knowledge will reduce the performance of the initial SDFTC framework.Therefore,in the SFDTC framework,to handle the influence of the uncertainty of expert knowledge and improve the framework performance,a new optimization model with two optimization goals is developed to ensure the smallest output uncertainty and the highest accuracy simultaneously.A case study is conducted to illustrate the effectiveness of the developed framework. | FENG Zhichao ZHOU Zhijie BAN Xiaojun HU Changhua ZHANG Xiaobo | 2023 | Journal of Systems Science & Complexity2023，36，3： | 0 |
| 9 | Stability analysis of the simplest Takagi-Sugeno fuzzy control system using circle criterion显示文摘A frequency-domain-based sufficient condition is derived to guarantee the globally asymptotic stability of the simplest Takagi-Sugeno (T-S) fuzzy control system by using the circle criterion. The analysis is performed in the frequency domain, and hence the condition is of great significance when the frequency-response method, which is widely used in the linear control theory and practice, is employed to synthesize the simplest T-S fuzzy controller. Besides, this sufficient condition is featured by a graphical interpretation, which makes the condition straightforward to be used. Comparisons are drawn between the performance of the simplest T-S fuzzy controller and that of the linear compensator. Two numerical examples are presented to demonstrate how this sufficient condition can be applied to both stable and unstable plants. | Lu Hongqian Huang Xianlin Gao X. Z. Ban Xiaojun Yin Hang | 2007 | Journal of Systems Engineering and Electronics2007，18，2： | 0 |
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