For the system with the fuzzy failure state, the effects of the input random variables and the fuzzy failure state on the fuzzy probability of failure for the structural system are studied, and the moment-independence...For the system with the fuzzy failure state, the effects of the input random variables and the fuzzy failure state on the fuzzy probability of failure for the structural system are studied, and the moment-independence global sensitivity analysis（GSA） model is proposed to quantitatively measure these effects. According to the fuzzy random theory, the fuzzy failure state is transformed into an equivalent new random variable for the system, and the complementary function of the membership function of the fuzzy failure state is defined as the cumulative distribution function（CDF） of the new random variable. After introducing the new random variable, the equivalent performance function of the original problem is built. The difference between the unconditional fuzzy probability of failure and conditional fuzzy probability of failure is defined as the moment-independent GSA index. In order to solve the proposed GSA index efficiently, the Kriging-based algorithm is developed to estimate the defined moment-independence GSA index. Two engineering examples are employed to verify the feasibility and rationality of the presented GSA model, and the advantages of the developed Kriging method are also illustrated.展开更多
This paper presents an evolution strategy to induce fuzzy finite-state automata from examples of fuzzy languages. The coding, fitness function of a generated automaton and corresponding mutation operators are given re...This paper presents an evolution strategy to induce fuzzy finite-state automata from examples of fuzzy languages. The coding, fitness function of a generated automaton and corresponding mutation operators are given respectively. The application example given at last shows the effectiveness of the proposed evolution strategy for automata induction.展开更多
Some concepts in Fuzzy Generalized Automata （FGA） are established. Then an important new algorithm which would calculate the minimal FGA is given. The new algorithm is composed of two parts： the first is called E-r...Some concepts in Fuzzy Generalized Automata （FGA） are established. Then an important new algorithm which would calculate the minimal FGA is given. The new algorithm is composed of two parts： the first is called E-reduction which contracts equivalent states, and the second is called RE-reduction which removes retrievable states. Finally an example is given to illuminate the algorithm of minimization.展开更多
At present, there has been an increasing interest in neuron-fuzzy systems, the combinations of artificial neural networks with fuzzy logic. In this paper, a definition of fuzzy finite state automata （FFA） is introdu...At present, there has been an increasing interest in neuron-fuzzy systems, the combinations of artificial neural networks with fuzzy logic. In this paper, a definition of fuzzy finite state automata （FFA） is introduced and fuzzy knowledge equivalence representations between neural networks, fuzzy systems and models of automata are discussed. Once the network has been trained, we develop a method to extract a representation of the FFA encoded in the recurrent neural network that recognizes the training rules.展开更多
This paper investigates an innovative predefined time output feedback adaptive fuzzy consensus control method for fractional-order nonlinear multi-agent systems(FONMASs).The controlled system includes unmeasurable sta...This paper investigates an innovative predefined time output feedback adaptive fuzzy consensus control method for fractional-order nonlinear multi-agent systems(FONMASs).The controlled system includes unmeasurable states and unknown nonlinear functions.The fuzzy state observer is built to evaluate unmeasurable state variables,unknown nonlinear functions are addressed through fuzzy logic system approximation.Combining with fractional-order dynamic surface control(DSC)and the theory of stability of predefined time,the control method is raised.By employing FODSC techniques,the computational explosion problem can be avoided.The stability of the closed-loop system is analyzed using the Lyapunov function,demonstrating that FONMAS achieves semi-global practical predefined time stability(SGPPTS).Eventually,the validity of the prescribed control strategy is verified by a simulation case.展开更多
基金supported by the National Natural Science Foundation of China(11702281)the Science Challenge Project(TZ2018007)the Technology Foundation Project of State Administration of Science,Technology and Industry for National Defence,PRC(JSZL2017212A001)
文摘For the system with the fuzzy failure state, the effects of the input random variables and the fuzzy failure state on the fuzzy probability of failure for the structural system are studied, and the moment-independence global sensitivity analysis（GSA） model is proposed to quantitatively measure these effects. According to the fuzzy random theory, the fuzzy failure state is transformed into an equivalent new random variable for the system, and the complementary function of the membership function of the fuzzy failure state is defined as the cumulative distribution function（CDF） of the new random variable. After introducing the new random variable, the equivalent performance function of the original problem is built. The difference between the unconditional fuzzy probability of failure and conditional fuzzy probability of failure is defined as the moment-independent GSA index. In order to solve the proposed GSA index efficiently, the Kriging-based algorithm is developed to estimate the defined moment-independence GSA index. Two engineering examples are employed to verify the feasibility and rationality of the presented GSA model, and the advantages of the developed Kriging method are also illustrated.
文摘This paper presents an evolution strategy to induce fuzzy finite-state automata from examples of fuzzy languages. The coding, fitness function of a generated automaton and corresponding mutation operators are given respectively. The application example given at last shows the effectiveness of the proposed evolution strategy for automata induction.
基金Supported by Supported by National Natural Science Foundation of China (No.60074014)
文摘Some concepts in Fuzzy Generalized Automata （FGA） are established. Then an important new algorithm which would calculate the minimal FGA is given. The new algorithm is composed of two parts： the first is called E-reduction which contracts equivalent states, and the second is called RE-reduction which removes retrievable states. Finally an example is given to illuminate the algorithm of minimization.
基金Youth Science and Technology Foundation of Sichuan (No. L080011YF021104)
文摘At present, there has been an increasing interest in neuron-fuzzy systems, the combinations of artificial neural networks with fuzzy logic. In this paper, a definition of fuzzy finite state automata （FFA） is introduced and fuzzy knowledge equivalence representations between neural networks, fuzzy systems and models of automata are discussed. Once the network has been trained, we develop a method to extract a representation of the FFA encoded in the recurrent neural network that recognizes the training rules.
基金funded in part by the National Natural Science Foundation of China under Grant Nos.62403226,62176111,and 62333004the Doctoral Research Initiation of Foundation of Liaoning Province,China under Grant No.2021-BS-260+5 种基金the general project of Liaoning Provincial Department of Education under Grant No.LIKZ0627Excellent Young Scientists Fund Program(Overseas)the“Xingliao Talent Plan”for young top talents under Grant No.XLYC22031882024 Fundamental Research Funding of the Educational Department of Liaoning Province under Grant No.LJZZ2224101540062024 Fundamental Research Funding of the Educational Department of Liaoning Province under Grant No.LJZZ2224101540012023 Education Department Basic Research Project(Youth Project)under Grant No.JYTQN2023225。
文摘This paper investigates an innovative predefined time output feedback adaptive fuzzy consensus control method for fractional-order nonlinear multi-agent systems(FONMASs).The controlled system includes unmeasurable states and unknown nonlinear functions.The fuzzy state observer is built to evaluate unmeasurable state variables,unknown nonlinear functions are addressed through fuzzy logic system approximation.Combining with fractional-order dynamic surface control(DSC)and the theory of stability of predefined time,the control method is raised.By employing FODSC techniques,the computational explosion problem can be avoided.The stability of the closed-loop system is analyzed using the Lyapunov function,demonstrating that FONMAS achieves semi-global practical predefined time stability(SGPPTS).Eventually,the validity of the prescribed control strategy is verified by a simulation case.
