李洪兴
个性化签名
 姓名：李洪兴
 目前身份：
 担任导师情况：
 学位：

学术头衔：
博士生导师， 优秀教师/优秀教育工作者， 教育部“新世纪优秀人才支持计划”入选者
 职称：

学科领域：
运筹学
 研究兴趣：
李洪兴 中共党员。1953年7月生，先后毕业于南开大学数学系与北京师范大学数学系，获理学博士学位。1998年8月1999年8月在美国莱特大学作访问教授。现任北京师范大学数学系教授、博士生导师、北师大复杂系统智能控制实验室主任、北师大模糊系统研究中心主任、中国人工智能学会理事兼智能系统工程委员会副主任、国际一般系统学会中国分会模糊系统委员会副理事长、《系统工程学报》编委、《模糊系统与数学》编委，《纺织高校基础科学学报》编委，德国数学文摘评论员，IEEE会员。1985年被授予天津市劳动模范称号，1986年被国家科委和人事部批准为“国家级有突出贡献的中青年专家”。1997年入选“教育部跨世纪优秀人才培养计划”。2002年被教育部授予中国高等学校优秀骨干教师称号。2002年获教育部自然科学一等奖。获2003年度首都劳动奖章。

主页访问
3485

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成果阅读
172

成果数
10
【期刊论文】Variable universe stable adaptive fuzzy control of nonlinear system1
李洪兴， LI Hongxing， MIAO Zhihong and WANG Jiayin
，0001，（）：
1年11月30日
A kind of stable adaptive fuzzy control of nonlinear system is implemented based on variable universe method proposed firstly in [1]. First of all, the basic structure of variable universe adaptive fuzzy controllers is briefly introduced. Then the contractionexpansion factor which is a key tool of variable universe method is defined by means of integral regulation idea, and then a kind of adaptive fuzzy controllers is designed by using such contractionexpansion factor. The simulation on first order nonlinear system is done, as a result, its simulation effect is quite good in comparison with the corresponding result in [5, 6]. Secondly, it is proved that the variable universe adaptive fuzzy control is asymptotically stable by use of Lyapunov theory. The simulation on second order nonlinear system shows that its simulation effect is also quite good in comparison with the corresponding result in [5]. Besides, a useful tool, called symbolic factor, is proposed, which may be of universal significance. It can greatly reduce the setting time and enhance the robustness of the system.

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【期刊论文】Variable universe adaptive fuzzy control on the quadruple inverted pendulum1
李洪兴， LI Hongxing， MIAO Zhihong and WANG Jiayin
，0001，（）：
1年11月30日
This paper focuses on the control problem of the quadruple inverted pendulum by variable universe adaptive fuzzy control that is firstly proposed in [35]. First, the mathematical model on the quadruple inverted pendulum is described and its controllability is verified. Then, an efficient controller on the quadruple inverted pendulum is designed by using variable universe adaptive fuzzy control theory. At last, the simulation of the quadruple inverted pendulum is well shown in detail. Besides, the experiment results on the hardware systems, i.e., real object systems, on a single inverted pendulum, a double inverted pendulum and a triple inverted pendulum are briefly introduced.

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【期刊论文】Relationship Between Fuzzy Controllers and PID Controller1
李洪兴， Li Hongxing
，0001，（）：
1年11月30日
The internal relations between fuzzy controllers and PID controllers are rewealed. First, it is pointed out that a fuzzy controller with one input and one output is just a piecewise p controller. Then it is proved that a fuzzy controller with two inputs and one output is just a piecewise PD (or I) controller with interaction between P and D (or PI). At last, the conclusion that a fuzzy controller with three inputs and one output is just a piecewise PID controller with interacting among P, I and D is given. Moreover, a kind of difference scheme of fuzzy controllers is designed.

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【期刊论文】Outputback Fuzzy Logic Systems and Equivalence with Feedback Neural Networks1
李洪兴， Li Hongxing
，0001，（）：
1年11月30日
A new idea, outputback fuzzy logic systems, is proposed in the paper. It is proved that outputback fuzzy logic systems must be equivalent to feedback neural networks. After the notion of generalized fuzzy logic systems is defined, which contains at least a typical fuzzy logic systems and an outputback fuzzy logic systems, one important conclusion is drawn that generallzed fuzzy logic systems are almost equivalent to neural networks.

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【期刊论文】Modelling on Fuzzy Control Systems1
李洪兴， LI Hongxing， WANG Jiayin & MIAO Zhihong
，0001，（）：
1年11月30日
A kind of modeling for fuzzy control systems is first proposed bere, which is called modeling method based on fuzzy inference (MMFI), It should be regarded as the third modeling method that is different from two wellknown modelling methods, that is, the first modeling method, mechanism modeling method (MMM), and the second modelling method, system identification modeling method (SIMM). This method can, based on the interpolation mechanism on fuzzy logic system, transfer a group of fuzzy inference rules describing a practice system into a kind of nonlinear differential equation with variable coefficients, called HX equations, so that the mathematical model of the system can be obtained. This means that we solve the difficult problem of how to get a model represented as differential equations on a complicated or fuzzy control system.

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【期刊论文】Marginal Linearization Method in Modeling on Fuzzy Control Systems1
李洪兴， Li Hongxing， WANG Jiayin and MIAO Zhihong
，0001，（）：
1年11月30日
Marginal Iinearization method in modeling on fuzzy control systems is proposed in this paper, in order to deal with nonlinear model with variable coefficients. The method can turn a nonlinear model with variable coefficients into a linear model with variable coefficients by means of the way that the membership functions of the fuzzy sets in fuzzy partitions of the universes are changed from triangle waves into rectangle waves. However, the Iinearization models are incomplete in their forms because of their lacking some items. For Solving this problem, joint approximation by using linear models is introduced. The simulation results in this paper show that marginal linearization models are of higher approximation precision to their original nonlinear models.

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【期刊论文】Interpolation Mechansim of Fuzzy Control1
李洪兴， Li Hongxing
，0001，（）：
1年11月30日
The fuzzy control algorithms used commonly at present are all regarded as some interpolation functions, which is in essence equivalent to discrete response functions to be fitted. This means that fuzzy control method is similar to finite element method is mathematical physics, which is a kind of direct manner or numerical method in control systems.

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【期刊论文】Fuzzy controllers based on some fuzzy implication operators and their response functions1
李洪兴， LI Hongxing， PENG Jiayin， YOU Fei， ZENG Wenyi
，0001，（）：
1年11月30日
The fuzzy controllers constructed by 23 fuzzy implication operators based on CRI algorithm and their response functions are discussed. The conclusions show that the fuzzy controllers constructed by 9 fuzzy implication operators are universal approximators to continuous functions and can be used in practical fuzzy control systems. And these 9 fuzzy implication operators except for Einstein operator intersection are all the adjoint pairs of some fuzzy implication operators. Besides, there are other 3 fuzzy controllers formed by fuzzy implication operators being regarded approximately as fitted functions.

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【期刊论文】Adaptive Fuzzy Controllers Based on Variable Universe1
李洪兴， Li Hongxing
，0001，（）：
1年11月30日
Adaptive fuzzy controllers by means of variable universe are proposed based on interpolation forms of fuzzy control. First, monotonicity of control rules is defined, and it is proved that the monotonicity of interpolation funetions of fuzzy control is equivalent to the monotonicity of control rules. This means that there is not any contradiction among the control rules under the condition for the control rules being monotonic. Then structure of the contractionexpansion factor is discussed. At last, three models of adaptive fuzzy control based on wariable universe are given which are adaptive fuzzy control model with potential heredity, adaptive fuzzy control model with obvious heredity and adaptive fuzzy control model with successively obvious heredity.

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【期刊论文】A New Kind of Fuzzy Relation Equations Based on Inner Transformation1
李洪兴， HongXing Li， ZhiHong Miao， SongChol Han， JiaYin Wang
，0001，（）：
1年11月30日
This paper mainly deals with a new kind of fuzzy relation equations based on inner transformation. First, the inner projection of a fuzzy relation and the inner transformation by a fuzzy relation are introduced, and also what is a fuzzy relation equation based on inner transformation described. Second, the discriminative matrix and the discriminative vector are defined. On the basis of them, an approach of discriminating whether such a fuzzy relation equation has nonzero solution is obtained. At last, a procedure of solving such fuzzy relation equations is presented. The solution set of a fuzzy relation equation based on inner transformation is not closed with respect to join and meet operations, in general. This shows that the traditional methods being used solving ∨∧ composite fuzzy relation equations can not be applied into the study of this kind of fuzzy relation relation equations based on inner transformation.

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