With the rapid growth in the availability of digital health-related data,there is a great demand for the utilization of intelligent information systems within the healthcare sector.These systems can manage and manipul...With the rapid growth in the availability of digital health-related data,there is a great demand for the utilization of intelligent information systems within the healthcare sector.These systems can manage and manipulate this massive amount of health-related data and encourage different decision-making tasks.They can also provide various sustainable health services such as medical error reduction,diagnosis acceleration,and clinical services quality improvement.The intensive care unit(ICU)is one of the most important hospital units.However,there are limited rooms and resources in most hospitals.During times of seasonal diseases and pandemics,ICUs face high admission demand.In line with this increasing number of admissions,determining health risk levels has become an essential and imperative task.It creates a heightened demand for the implementation of an expert decision support system,enabling doctors to accurately and swiftly determine the risk level of patients.Therefore,this study proposes a fuzzy logic inference system built on domain-specific knowledge graphs,as a proof-of-concept,for tackling this healthcare-related issue.The system employs a combination of two sets of fuzzy input parameters to classify health risk levels of new admissions to hospitals.The proposed system implemented utilizes MATLAB Fuzzy Logic Toolbox via several experiments showing the validity of the proposed system.展开更多
A lot of experimental methods have been brought forth to assess the dynamic character of the arc welding power source, but up to now, this issue has not been solved very well. In this paper, based on the fuzzy logic r...A lot of experimental methods have been brought forth to assess the dynamic character of the arc welding power source, but up to now, this issue has not been solved very well. In this paper, based on the fuzzy logic reasoning method, a dynamic character assessing model for the arc welding power source was established and used to analyze the dynamic character of the welding power source. Three different types of welding machine have been tested, and the characteristic information of the electrical signals such as re-striking arc voltage, low welding current and so on of the welding process were extracted accurately by using a self-developed welding dynamic arc wavelet analyzer. The experimental results indicate that this model can be used as a new assessing method for the dynamic character of the arc welding power source.展开更多
Fuzzy description logics are considered as the logical infrastructure of fuzzy knowledge representation on the semantic Web. To deal with fuzzy and dynamic knowledge on the semantic Web and its applications, a new fuz...Fuzzy description logics are considered as the logical infrastructure of fuzzy knowledge representation on the semantic Web. To deal with fuzzy and dynamic knowledge on the semantic Web and its applications, a new fuzzy extension of Attribute Language with Complement based on dynamic fuzzy logic called the dynamic fuzzy description logic (DFALC) is presented. The syntax and semantics of DFALC are formally defined, and the forms of axioms and assertions are specified. The DFALC provides more reasonable logic foundation for the semantic Web, and overcomes the insufficiency of using fuzzy description logic FALC to act as logical foundation for the semantic Web. The extended DFALC is more expressive than the existing fuzzy description logics and present more fuzzy information on the semantic Web.展开更多
In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear funct...In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear functions by only one fuzzy logic system. The approximation capability of this model is proved and the model is implemented to solve the problem that too many approximators are used in the controller design of uncertain nonlinear systems. The shortage of "explosion of complexity" in backstepping design procedure is overcome by using the proposed dynamic surface control method. It is proved by constructing appropriate Lyapunov candidates that all signals of closed-loop systems are semi-globally uniformly ultimate bounded. Also, this novel controller stabilizes the states of uncertain nonlinear systems faster than the adaptive sliding mode controller (SMC). Two simulation examples are provided to illustrate the effectiveness of the control approach proposed in this paper.展开更多
In this paper, an adaptive dynamic control scheme based on a fuzzy neural network is presented, that presents utilizes both feed-forward and feedback controller elements. The former of the two elements comprises a neu...In this paper, an adaptive dynamic control scheme based on a fuzzy neural network is presented, that presents utilizes both feed-forward and feedback controller elements. The former of the two elements comprises a neural network with both identification and control role, and the latter is a fuzzy neural algorithm, which is introduced to provide additional control enhancement. The feedforward controller provides only coarse control, whereas the feedback controller can generate on-line conditional proposition rule automatically to improve the overall control action. These properties make the design very versatile and applicable to a range of industrial applications.展开更多
Ecological demonstration area (EDA) is an authorized nomination, which should be assessed from several aspects, including ecological, social, environmental, economic ones and so on. It is difficult to advance an exact...Ecological demonstration area (EDA) is an authorized nomination, which should be assessed from several aspects, including ecological, social, environmental, economic ones and so on. It is difficult to advance an exact developing level index of EDA due to its indicator system’s complexity and disequilibrium. In this paper, a framework of indicators was set to evaluate, monitor and examine the comprehensive level of ecological demonstration area (EDA). Fuzzy logic method was used to develop the fuzzy comprehensive evaluation model (FCEM), which could quantitatively reveal the developing degree of EDA. Huiji District of Zhengzhou, Henan Province, one of the 9th group of national EDAs, was taken as a study case. The framework of FCEM for the integrated system included six subsystems, which were social, economic, ecological, rural, urban and accessorial description ones. The research would be valuable in the comprehensive quantitative evaluation of EDA and would work as a guide in the construction practices of Huiji ecological demonstration area.展开更多
In this paper we are presenting an intelligent method for controlling population size in evolutionary algorithms. The method uses Mediative Fuzzy Logic for modeling knowledge from experts about what should be the beha...In this paper we are presenting an intelligent method for controlling population size in evolutionary algorithms. The method uses Mediative Fuzzy Logic for modeling knowledge from experts about what should be the behavior of population size through generations based on the fitness variance and the number of generations that the algorithm is being stuck. Since, it is common that this kind of knowledge expertise can be susceptible to disagreement in a minor or a major part. We selected Mediative Fuzzy Logic (MFL) as a fuzzy method to achieve the inference. MFL is a novelty fuzzy inference method that can handle imperfect knowledge in a broader way than traditional fuzzy logic does.展开更多
Fault diagnostics is important for safe operation of nuclear power plants(NPPs). In recent years, data-driven approaches have been proposed and implemented to tackle the problem, e.g., neural networks, fuzzy and neuro...Fault diagnostics is important for safe operation of nuclear power plants(NPPs). In recent years, data-driven approaches have been proposed and implemented to tackle the problem, e.g., neural networks, fuzzy and neurofuzzy approaches, support vector machine, K-nearest neighbor classifiers and inference methodologies. Among these methods, dynamic uncertain causality graph(DUCG)has been proved effective in many practical cases. However, the causal graph construction behind the DUCG is complicate and, in many cases, results redundant on the symptoms needed to correctly classify the fault. In this paper, we propose a method to simplify causal graph construction in an automatic way. The method consists in transforming the expert knowledge-based DCUG into a fuzzy decision tree(FDT) by extracting from the DUCG a fuzzy rule base that resumes the used symptoms at the basis of the FDT. Genetic algorithm(GA) is, then, used for the optimization of the FDT, by performing a wrapper search around the FDT: the set of symptoms selected during the iterative search are taken as the best set of symptoms for the diagnosis of the faults that can occur in the system. The effectiveness of the approach is shown with respect to a DUCG model initially built to diagnose 23 faults originally using 262 symptoms of Unit-1 in the Ningde NPP of the China Guangdong Nuclear Power Corporation. The results show that the FDT, with GA-optimized symptoms and diagnosis strategy, can drive the construction of DUCG and lower the computational burden without loss of accuracy in diagnosis.展开更多
Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while kee...Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while keeping the overall population size constant. The simulation results of function optimization show that with the proposed algorithm, the phenomenon of premature convergence can be overcome effectively, and a satisfying optimization result is obtained.展开更多
This paper proposes a new neural fuzzy inference system that mainly consists of four parts. The first part is about how to use neural network to express the relation within a fuzzy rule. The second part is the simplif...This paper proposes a new neural fuzzy inference system that mainly consists of four parts. The first part is about how to use neural network to express the relation within a fuzzy rule. The second part is the simplification of the first part, and experiments show that these simplifications work. On the contrary to the second part, the third part is the enhancement of the first part and it can be used when the first part cannot work very well in the fuzzy inference algorithm, which would be introduced in the fourth part. Finally, the fourth part "neural fuzzy inference algorithm" is been introduced. It can inference the new membership function of the output based on previous fuzzy rules. The accuracy of the fuzzy inference algorithm is dependent on neural network generalization ability. Even if the generalization ability of the neural network we used is good, we still get inaccurate results since the new coming rule may not be related to any of the previous rules. Experiments show this algorithm is successful in situations which satisfy these conditions.展开更多
In recent years, a rapid decrease in the cost of various energy storage technologies and their integration into grid becomes a reality with the advent of smart grid. The Dynamic Voltage Restorer (DVR) is a custom powe...In recent years, a rapid decrease in the cost of various energy storage technologies and their integration into grid becomes a reality with the advent of smart grid. The Dynamic Voltage Restorer (DVR) is a custom power device that has an excellent dynamic capability used to provide voltage sag, swell compensation in distribution systems. Among the energy storage devices, Ultra-Capacitors (UCAP) have ideal characteristics such as high power and low energy density essential for the compensation of voltage sag and swell, which require high power for short interval of time. This paper presents an integration of rechargeable UCAP with DVR. This UCAP-DVR presents a modular, flexible system configuration that will have an active power capability and also provide deep, extended mitigation for power quality problems. The DVR is integrated into UCAP via bidirectional DC-DC converter which supports a rigid dc-link voltage for DVR and also helps in compensating temporary voltage sag and swell. FUZZY LOGIC Controller is used to enhance the performance of UCAP-DVR. The simulation model for the proposed system has been developed in MAT-LAB and the performance over conventional DVR is compared with the results obtained.展开更多
Considering the characters of dynamic topology and the imprecise state information in mobile ad hoc network,we propose a Fuzzy Logic QoS Dynamic Source Routing(FLQDSR)algorithm based on Dynamic Source Routing(DSR)prot...Considering the characters of dynamic topology and the imprecise state information in mobile ad hoc network,we propose a Fuzzy Logic QoS Dynamic Source Routing(FLQDSR)algorithm based on Dynamic Source Routing(DSR)protocol while adopting fuzzy logic to select the appropriate QoS routing in multiple paths which are searched in parallel.This scheme considers not only the bandwidth and end-to-end delay of routing,but also the cost of the path.On the otherhand the merit of using fuzzy logic is that it can be implemented by hardware.This makes the realization of the schemeeasier and faster.However our algorithm is based on DSR,the maximal hop count should be less than 10,i.e.,the scaleof mobile ad hoc network should not be very large.Simulation results show that FLQDSR can tolerate a high degree of in-formation imprecision by adding the fuzzy logic module which integrates the QoS requirements of application and the rout-ing QoS parameters to determine the most qualified one in every node.展开更多
This paper addresses issues related to nonlinear robust output feedback controller design for a nonlinear model of airbreathing hypersonic vehicle. The control objective is to realize robust tracking of velocity and a...This paper addresses issues related to nonlinear robust output feedback controller design for a nonlinear model of airbreathing hypersonic vehicle. The control objective is to realize robust tracking of velocity and altitude in the presence of immeasurable states, uncertainties and varying flight conditions.A novel reduced order fuzzy observer is proposed to estimate the immeasurable states. Based on the information of observer and the measured states, a new robust output feedback controller combining dynamic surface theory and fuzzy logic system is proposed for airbreathing hypersonic vehicle. The closedloop system is proved to be semi-globally uniformly ultimately bounded(SUUB), and the tracking error can be made small enough by choosing proper gains of the controller, filter and observer. Simulation results from the full nonlinear vehicle model illustrate the effectiveness and good performance of the proposed control scheme.展开更多
This paper presents an observer based dynamic fuzzy logic system (DFLS) scheme for a class of unknown single-input single-output (SISO) nonlinear dynamic systems with external disturbances. The proposed approach d...This paper presents an observer based dynamic fuzzy logic system (DFLS) scheme for a class of unknown single-input single-output (SISO) nonlinear dynamic systems with external disturbances. The proposed approach does not need the availability of the state variables. Within this scheme, the DFLS is employed to identify the unknown nonlinear dynamic system. The control law and parameter adaptation laws of the DFLS are derived based on Lyapunov synthesis approach. The control law is robustfied in H∞ sense to attenuate external disturbance, model uncertainties, and fuzzy approximation errors. It is shown that under appropriate assumptions, it guarantees the boundedness of all the signals in the closed-loop system and the asymptotic convergence to zero of tracking errors. The proposed method is applied to an inverted pendulum system to verify the effectiveness of the proposed algorithms.展开更多
Without the geometry of light and logic of photon,observer-observability forms a paradox in modern science,truthequilibrium finds no unification,and mind-light-matter unity is unreachable in spacetime.Subsequently,qua...Without the geometry of light and logic of photon,observer-observability forms a paradox in modern science,truthequilibrium finds no unification,and mind-light-matter unity is unreachable in spacetime.Subsequently,quantum mechanics has been shrouded with mysteries preventing itself from reaching definable causality for a general purpose analytical quantum computing paradigm.Ground-0 Axioms are introduced as an equilibrium-based,dynamic,bipolar set-theoretic unification of the first principles of science and the second law of thermodynamics.Related literatures are critically reviewed to justify the self-evident nature of Ground-0 Axioms.A historical misinterpretation by the founding fathers of quantum mechanics is identified and corrected.That disproves spacetime geometries(including but not limited to Euclidean and Hilbert spaces)as the geometries of light and truth-based logics(including but not limited to bra-ket quantum logic)as the logics of photon.Backed with logically definable causality and Dirac 3-polarizer experiment,bipolar quantum geometry(BQG)and bipolar dynamic logic(BDL)are identified as the geometry of light and the logic of photon,respectively,and wave-particle complementarity is shown less fundamental than bipolar complementarity.As a result,Ground-0 Axioms lead to a geometrical and logical illumination of the quantum and classical worlds as well as the physical and mental worlds.With logical resolutions to the EPR and Schr?dinger’s cat paradoxes,an analytical quantum computing paradigm named quantum intelligence(QI)is introduced.It is shown that QI makes mind-light-matter unity and quantum-digital compatibility logically reachable for quantumneuro-fuzzy AI-machinery with groundbreaking applications.It is contended that Ground-0 Axioms open a new era of science and philosophy—the era of mind-light-matter unity in which humanlevel white-box AI&QI is logically prompted to join Einstein’s grand unification to foster major scientific advances.展开更多
基金funded by the Deanship of Scientific Research at Umm Al-Qura University,Makkah,Kingdom of Saudi Arabia.Under Grant Code:22UQU4281755DSR05.
文摘With the rapid growth in the availability of digital health-related data,there is a great demand for the utilization of intelligent information systems within the healthcare sector.These systems can manage and manipulate this massive amount of health-related data and encourage different decision-making tasks.They can also provide various sustainable health services such as medical error reduction,diagnosis acceleration,and clinical services quality improvement.The intensive care unit(ICU)is one of the most important hospital units.However,there are limited rooms and resources in most hospitals.During times of seasonal diseases and pandemics,ICUs face high admission demand.In line with this increasing number of admissions,determining health risk levels has become an essential and imperative task.It creates a heightened demand for the implementation of an expert decision support system,enabling doctors to accurately and swiftly determine the risk level of patients.Therefore,this study proposes a fuzzy logic inference system built on domain-specific knowledge graphs,as a proof-of-concept,for tackling this healthcare-related issue.The system employs a combination of two sets of fuzzy input parameters to classify health risk levels of new admissions to hospitals.The proposed system implemented utilizes MATLAB Fuzzy Logic Toolbox via several experiments showing the validity of the proposed system.
基金This work is supported by Guangdong Natural Science Fund (04020100)
文摘A lot of experimental methods have been brought forth to assess the dynamic character of the arc welding power source, but up to now, this issue has not been solved very well. In this paper, based on the fuzzy logic reasoning method, a dynamic character assessing model for the arc welding power source was established and used to analyze the dynamic character of the welding power source. Three different types of welding machine have been tested, and the characteristic information of the electrical signals such as re-striking arc voltage, low welding current and so on of the welding process were extracted accurately by using a self-developed welding dynamic arc wavelet analyzer. The experimental results indicate that this model can be used as a new assessing method for the dynamic character of the arc welding power source.
基金the National Natural Science Foundation of China (60673092)Key Project of Ministry of Education of China (205059)+2 种基金the 2006 Jiangsu Sixth Talented-Personnel Research Program (06-E-037)The Project of Jiangsu Key Laboratory of Computer Information Processing Technologythe Higher Education Graduate Research Innovation Program of Jiangsu Province
文摘Fuzzy description logics are considered as the logical infrastructure of fuzzy knowledge representation on the semantic Web. To deal with fuzzy and dynamic knowledge on the semantic Web and its applications, a new fuzzy extension of Attribute Language with Complement based on dynamic fuzzy logic called the dynamic fuzzy description logic (DFALC) is presented. The syntax and semantics of DFALC are formally defined, and the forms of axioms and assertions are specified. The DFALC provides more reasonable logic foundation for the semantic Web, and overcomes the insufficiency of using fuzzy description logic FALC to act as logical foundation for the semantic Web. The extended DFALC is more expressive than the existing fuzzy description logics and present more fuzzy information on the semantic Web.
基金This work is supported by the National Hi-Tech Research and Development 863 Program of China (No 2002AA881030), the Nature Science Foundation of Jiangsu Province (No. BK2005027, No. BK2002040) and the 211 Foundation of Soochow University.
基金supported by National Natural Science Foundation of China (No. 60525303 and 60704009)Key Research Program of Hebei Education Department (No. ZD200908)
文摘In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear functions by only one fuzzy logic system. The approximation capability of this model is proved and the model is implemented to solve the problem that too many approximators are used in the controller design of uncertain nonlinear systems. The shortage of "explosion of complexity" in backstepping design procedure is overcome by using the proposed dynamic surface control method. It is proved by constructing appropriate Lyapunov candidates that all signals of closed-loop systems are semi-globally uniformly ultimate bounded. Also, this novel controller stabilizes the states of uncertain nonlinear systems faster than the adaptive sliding mode controller (SMC). Two simulation examples are provided to illustrate the effectiveness of the control approach proposed in this paper.
基金China Postdoctoral Science Foundation and Natural Science of Heibei Province!698004
文摘In this paper, an adaptive dynamic control scheme based on a fuzzy neural network is presented, that presents utilizes both feed-forward and feedback controller elements. The former of the two elements comprises a neural network with both identification and control role, and the latter is a fuzzy neural algorithm, which is introduced to provide additional control enhancement. The feedforward controller provides only coarse control, whereas the feedback controller can generate on-line conditional proposition rule automatically to improve the overall control action. These properties make the design very versatile and applicable to a range of industrial applications.
基金U nder the auspices of the M ajor State B asic R esearch D evelopm ent Program of C hina (973 Program ) (N o.2005C B 724205)
文摘Ecological demonstration area (EDA) is an authorized nomination, which should be assessed from several aspects, including ecological, social, environmental, economic ones and so on. It is difficult to advance an exact developing level index of EDA due to its indicator system’s complexity and disequilibrium. In this paper, a framework of indicators was set to evaluate, monitor and examine the comprehensive level of ecological demonstration area (EDA). Fuzzy logic method was used to develop the fuzzy comprehensive evaluation model (FCEM), which could quantitatively reveal the developing degree of EDA. Huiji District of Zhengzhou, Henan Province, one of the 9th group of national EDAs, was taken as a study case. The framework of FCEM for the integrated system included six subsystems, which were social, economic, ecological, rural, urban and accessorial description ones. The research would be valuable in the comprehensive quantitative evaluation of EDA and would work as a guide in the construction practices of Huiji ecological demonstration area.
文摘In this paper we are presenting an intelligent method for controlling population size in evolutionary algorithms. The method uses Mediative Fuzzy Logic for modeling knowledge from experts about what should be the behavior of population size through generations based on the fitness variance and the number of generations that the algorithm is being stuck. Since, it is common that this kind of knowledge expertise can be susceptible to disagreement in a minor or a major part. We selected Mediative Fuzzy Logic (MFL) as a fuzzy method to achieve the inference. MFL is a novelty fuzzy inference method that can handle imperfect knowledge in a broader way than traditional fuzzy logic does.
文摘Fault diagnostics is important for safe operation of nuclear power plants(NPPs). In recent years, data-driven approaches have been proposed and implemented to tackle the problem, e.g., neural networks, fuzzy and neurofuzzy approaches, support vector machine, K-nearest neighbor classifiers and inference methodologies. Among these methods, dynamic uncertain causality graph(DUCG)has been proved effective in many practical cases. However, the causal graph construction behind the DUCG is complicate and, in many cases, results redundant on the symptoms needed to correctly classify the fault. In this paper, we propose a method to simplify causal graph construction in an automatic way. The method consists in transforming the expert knowledge-based DCUG into a fuzzy decision tree(FDT) by extracting from the DUCG a fuzzy rule base that resumes the used symptoms at the basis of the FDT. Genetic algorithm(GA) is, then, used for the optimization of the FDT, by performing a wrapper search around the FDT: the set of symptoms selected during the iterative search are taken as the best set of symptoms for the diagnosis of the faults that can occur in the system. The effectiveness of the approach is shown with respect to a DUCG model initially built to diagnose 23 faults originally using 262 symptoms of Unit-1 in the Ningde NPP of the China Guangdong Nuclear Power Corporation. The results show that the FDT, with GA-optimized symptoms and diagnosis strategy, can drive the construction of DUCG and lower the computational burden without loss of accuracy in diagnosis.
基金Supported by Basic Research Foundation of National Defence (No. B0203-031)
文摘Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while keeping the overall population size constant. The simulation results of function optimization show that with the proposed algorithm, the phenomenon of premature convergence can be overcome effectively, and a satisfying optimization result is obtained.
文摘This paper proposes a new neural fuzzy inference system that mainly consists of four parts. The first part is about how to use neural network to express the relation within a fuzzy rule. The second part is the simplification of the first part, and experiments show that these simplifications work. On the contrary to the second part, the third part is the enhancement of the first part and it can be used when the first part cannot work very well in the fuzzy inference algorithm, which would be introduced in the fourth part. Finally, the fourth part "neural fuzzy inference algorithm" is been introduced. It can inference the new membership function of the output based on previous fuzzy rules. The accuracy of the fuzzy inference algorithm is dependent on neural network generalization ability. Even if the generalization ability of the neural network we used is good, we still get inaccurate results since the new coming rule may not be related to any of the previous rules. Experiments show this algorithm is successful in situations which satisfy these conditions.
文摘In recent years, a rapid decrease in the cost of various energy storage technologies and their integration into grid becomes a reality with the advent of smart grid. The Dynamic Voltage Restorer (DVR) is a custom power device that has an excellent dynamic capability used to provide voltage sag, swell compensation in distribution systems. Among the energy storage devices, Ultra-Capacitors (UCAP) have ideal characteristics such as high power and low energy density essential for the compensation of voltage sag and swell, which require high power for short interval of time. This paper presents an integration of rechargeable UCAP with DVR. This UCAP-DVR presents a modular, flexible system configuration that will have an active power capability and also provide deep, extended mitigation for power quality problems. The DVR is integrated into UCAP via bidirectional DC-DC converter which supports a rigid dc-link voltage for DVR and also helps in compensating temporary voltage sag and swell. FUZZY LOGIC Controller is used to enhance the performance of UCAP-DVR. The simulation model for the proposed system has been developed in MAT-LAB and the performance over conventional DVR is compared with the results obtained.
文摘Considering the characters of dynamic topology and the imprecise state information in mobile ad hoc network,we propose a Fuzzy Logic QoS Dynamic Source Routing(FLQDSR)algorithm based on Dynamic Source Routing(DSR)protocol while adopting fuzzy logic to select the appropriate QoS routing in multiple paths which are searched in parallel.This scheme considers not only the bandwidth and end-to-end delay of routing,but also the cost of the path.On the otherhand the merit of using fuzzy logic is that it can be implemented by hardware.This makes the realization of the schemeeasier and faster.However our algorithm is based on DSR,the maximal hop count should be less than 10,i.e.,the scaleof mobile ad hoc network should not be very large.Simulation results show that FLQDSR can tolerate a high degree of in-formation imprecision by adding the fuzzy logic module which integrates the QoS requirements of application and the rout-ing QoS parameters to determine the most qualified one in every node.
基金supported by Natural National Science Foundation of China(61273083,61374012)
文摘This paper addresses issues related to nonlinear robust output feedback controller design for a nonlinear model of airbreathing hypersonic vehicle. The control objective is to realize robust tracking of velocity and altitude in the presence of immeasurable states, uncertainties and varying flight conditions.A novel reduced order fuzzy observer is proposed to estimate the immeasurable states. Based on the information of observer and the measured states, a new robust output feedback controller combining dynamic surface theory and fuzzy logic system is proposed for airbreathing hypersonic vehicle. The closedloop system is proved to be semi-globally uniformly ultimately bounded(SUUB), and the tracking error can be made small enough by choosing proper gains of the controller, filter and observer. Simulation results from the full nonlinear vehicle model illustrate the effectiveness and good performance of the proposed control scheme.
文摘This paper presents an observer based dynamic fuzzy logic system (DFLS) scheme for a class of unknown single-input single-output (SISO) nonlinear dynamic systems with external disturbances. The proposed approach does not need the availability of the state variables. Within this scheme, the DFLS is employed to identify the unknown nonlinear dynamic system. The control law and parameter adaptation laws of the DFLS are derived based on Lyapunov synthesis approach. The control law is robustfied in H∞ sense to attenuate external disturbance, model uncertainties, and fuzzy approximation errors. It is shown that under appropriate assumptions, it guarantees the boundedness of all the signals in the closed-loop system and the asymptotic convergence to zero of tracking errors. The proposed method is applied to an inverted pendulum system to verify the effectiveness of the proposed algorithms.
文摘Without the geometry of light and logic of photon,observer-observability forms a paradox in modern science,truthequilibrium finds no unification,and mind-light-matter unity is unreachable in spacetime.Subsequently,quantum mechanics has been shrouded with mysteries preventing itself from reaching definable causality for a general purpose analytical quantum computing paradigm.Ground-0 Axioms are introduced as an equilibrium-based,dynamic,bipolar set-theoretic unification of the first principles of science and the second law of thermodynamics.Related literatures are critically reviewed to justify the self-evident nature of Ground-0 Axioms.A historical misinterpretation by the founding fathers of quantum mechanics is identified and corrected.That disproves spacetime geometries(including but not limited to Euclidean and Hilbert spaces)as the geometries of light and truth-based logics(including but not limited to bra-ket quantum logic)as the logics of photon.Backed with logically definable causality and Dirac 3-polarizer experiment,bipolar quantum geometry(BQG)and bipolar dynamic logic(BDL)are identified as the geometry of light and the logic of photon,respectively,and wave-particle complementarity is shown less fundamental than bipolar complementarity.As a result,Ground-0 Axioms lead to a geometrical and logical illumination of the quantum and classical worlds as well as the physical and mental worlds.With logical resolutions to the EPR and Schr?dinger’s cat paradoxes,an analytical quantum computing paradigm named quantum intelligence(QI)is introduced.It is shown that QI makes mind-light-matter unity and quantum-digital compatibility logically reachable for quantumneuro-fuzzy AI-machinery with groundbreaking applications.It is contended that Ground-0 Axioms open a new era of science and philosophy—the era of mind-light-matter unity in which humanlevel white-box AI&QI is logically prompted to join Einstein’s grand unification to foster major scientific advances.