Adaptive Type-2 fuzzy control possesses control performance better than the traditional adaptive fuzzy control.However,heavy computation burden obviously blocks the utilization of adaptive Type-2 fuzzy control in indu...Adaptive Type-2 fuzzy control possesses control performance better than the traditional adaptive fuzzy control.However,heavy computation burden obviously blocks the utilization of adaptive Type-2 fuzzy control in industrial application.By adopting novel piecewise fuzzy sets and center-average type-reduction,a simplified adaptive interval Type-2 fuzzy controller involving less computation is developed for practical industrial application.In the proposed controller,the inputs are divided into several subintervals and then two piecewise fuzzy sets are used for each subinterval.With the manner of piecewise fuzzy sets and a novel fuzzy rules inference engine,only part of fuzzy rules are simultaneously activated in one control loop,which exponentially decreases the computation and makes the controller appropriate in industrial application.The simulation and experimental study,involving the popular magnetic levitation platform,shows the predicted system with theoretical stability and good tracking performance.The analysis indicates that there is far less computation of the proposed controller than the traditional adaptive interval Type-2 fuzzy controller,especially when the number of fuzzy rules and fuzzy sets is large,and the controller still maintains good control performance as the traditional one.展开更多
A novel decentralized indirect adaptive output feedback fuzzy controller is developed for a class of large-scale uncertain nonlinear systems using error filtering.By the properly filtering of the observation error dyn...A novel decentralized indirect adaptive output feedback fuzzy controller is developed for a class of large-scale uncertain nonlinear systems using error filtering.By the properly filtering of the observation error dynamics,the strictly positive-real condition is guaranteed to hold such that the proposed output feedback and adaptation mechanisms are practicable in practice owing to the fact that its implementation does not require the observation error vector itself any more,which corrects the impracticable schemes in the previous literature involved.The presented control algorithm can ensure that all the signals of the closed-loop large-scale system keep uniformly ultimately bounded and that the tracking error converges to zero asymptotically.The decentralized output feedback fuzzy controller can be applied to address the longitudinal control problem of a string of vehicles within an automated highway system（AHS） and the effectiveness of the design procedure is supported by simulation results.展开更多
This paper is concerned with a fuzzy robust H∞ control problem via output feedbackfor a class of uncertain nonlinear systems. The uncertain nonlinear systemsare represented by fuzzy Takagi-Sugeno （T-S） model, and a...This paper is concerned with a fuzzy robust H∞ control problem via output feedbackfor a class of uncertain nonlinear systems. The uncertain nonlinear systemsare represented by fuzzy Takagi-Sugeno （T-S） model, and a fuzzy controller is designedbased on the state observer. A sufficient condition for the existence of fuzzycontroller is given in terms of the linear matrix inequalities （LMIs） and the adaptivelaw. Based on Lyapunov stability theorem, the proposed fuzzy control scheme suchthat the desired H∞performance is achieved in the sense that all the closed-loopsignals are uniformly ultimately bounded （UUB）. Simulation results indicate theeffectiveness of the developed control scheme. In this paper, a less conservativefuzzy tracking controller is proposed, where the matching condition and the upperbound are avoided. Comparing with the existing works, the dimension of the LMIsof this paper is reduced.展开更多
A novel group decision-making （GDM） method based on intuitionistic fuzzy sets （IFSs） is developed to evaluate the ergonomics of aircraft cockpit display and control system （ACDCS）. The GDM process with four step...A novel group decision-making （GDM） method based on intuitionistic fuzzy sets （IFSs） is developed to evaluate the ergonomics of aircraft cockpit display and control system （ACDCS）. The GDM process with four steps is discussed. Firstly, approaches are proposed to transform four types of common judgement representations into a unified expression by the form of the IFS, and the features of unifications are analyzed. Then, the aggregation operator called the IFSs weighted averaging （IFSWA） operator is taken to synthesize decision-makers’ （DMs’） preferences by the form of the IFS. In this operator, the DM’s reliability weights factors are determined based on the distance measure between their preferences. Finally, an improved score function is used to rank alternatives and to get the best one. An illustrative example proves the proposed method is effective to valuate the ergonomics of the ACDCS.展开更多
Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scal...Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-Ⅰ intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.展开更多
A constrained generalized predictive control （GPC） algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno （T-S） fuzzy model based on the fuzzy cluster algorithm and th...A constrained generalized predictive control （GPC） algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno （T-S） fuzzy model based on the fuzzy cluster algorithm and the orthogonalleast square method is constructed to approach the nonlinear system. Since its consequence is linear, it can divide the nonlinear system into a number of linear or nearly linear subsystems. For this T-S fuzzy model, a GPC algorithm with input constraints is presented. This strategy takes into account all the constraints of the control signal and its increment, and does not require the calculation of the Diophantine equations. So it needs only a small computer memory and the computational speed is high. The simulation results show a good performance for the nonlinear systems.展开更多
ln this paper, FEEC theory is studied. An economical space is a dynamic model for any scope of certain economy and market . ln an economical space, any point represents some economical area or entity and is assigned a...ln this paper, FEEC theory is studied. An economical space is a dynamic model for any scope of certain economy and market . ln an economical space, any point represents some economical area or entity and is assigned an variable economic condition Any subspace is assigned an variable economic evaluation. FEEC controller operates oz. economic evaluation and the public parts in economic condition. Any adjustment done by FEEC controller asks the point itself to improve other members to meet the requirements. ln this paper, the template for economic condition and economic evaluation is defined , and then the generic type of economical space and FEE. controller is also given.展开更多
A framework of knowledge representation of fuzzy language field and fuzzy language value structure is shown. Then the generalized cell automation that can synthetically process fuzzy indeterminacy and random indetermi...A framework of knowledge representation of fuzzy language field and fuzzy language value structure is shown. Then the generalized cell automation that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model are put forward. On this basis, the logic indeterminacy causal inductive automatic reasoning mechanism which is based on fuzzy state description is presented. At the end of this paper its application in the development of intelligent controller is discussed.展开更多
Fuzzy technology is a newly developed discipline based on fuzzy mathematics. In the recent years, it has been successfully applied into many areas, such as process control, diagnosis, evaluation, decision making and s...Fuzzy technology is a newly developed discipline based on fuzzy mathematics. In the recent years, it has been successfully applied into many areas, such as process control, diagnosis, evaluation, decision making and scheduling, especially in simulation where accurate mathematical models can not or very hard be established. In this paper, to meet the demands of fuzzy simulation, two fuzzy nets will first be presented, which are quite suitable for modeling the parallel or concurrent systems with fuzzy behavior. Then, a concept of active simulation will be introduced, in which the simulation model not only can show its fuzzy behavior, but also has a certain ability which can actively perform many very useful actions, such as automatic warning, realtime monitoring, simulation result checking, simulation model self-adapting, error recovery, simulating path tracing, system states inspecting and exception handling, by a unified approach while some specified events occur. The simulation model described by this powerful simulation modeling tool is concurrently driven by a network interpreter and an event monitor that all can be implemented by software or hardware. Besides, some interesting applications are given in the paper.展开更多
基金Project(51005253) supported by the National Natural Science Foundation of ChinaProject(2012ZX02702006-003) supported by the National Science and Technology Major Program of ChinaProject(JMTZ201101) supported by the Key Laboratory for Precision & Non-traditional Machining of Ministry of Education,Dalian University of Technology,China
文摘Adaptive Type-2 fuzzy control possesses control performance better than the traditional adaptive fuzzy control.However,heavy computation burden obviously blocks the utilization of adaptive Type-2 fuzzy control in industrial application.By adopting novel piecewise fuzzy sets and center-average type-reduction,a simplified adaptive interval Type-2 fuzzy controller involving less computation is developed for practical industrial application.In the proposed controller,the inputs are divided into several subintervals and then two piecewise fuzzy sets are used for each subinterval.With the manner of piecewise fuzzy sets and a novel fuzzy rules inference engine,only part of fuzzy rules are simultaneously activated in one control loop,which exponentially decreases the computation and makes the controller appropriate in industrial application.The simulation and experimental study,involving the popular magnetic levitation platform,shows the predicted system with theoretical stability and good tracking performance.The analysis indicates that there is far less computation of the proposed controller than the traditional adaptive interval Type-2 fuzzy controller,especially when the number of fuzzy rules and fuzzy sets is large,and the controller still maintains good control performance as the traditional one.
基金supported by the National Natural Science Foundation of China (6096400460864004+2 种基金50808025)the Fok Ying Tung Education Foundation (122013)the Scientific Research Fund of Hunan Provincial Education Department (08A003)
文摘A novel decentralized indirect adaptive output feedback fuzzy controller is developed for a class of large-scale uncertain nonlinear systems using error filtering.By the properly filtering of the observation error dynamics,the strictly positive-real condition is guaranteed to hold such that the proposed output feedback and adaptation mechanisms are practicable in practice owing to the fact that its implementation does not require the observation error vector itself any more,which corrects the impracticable schemes in the previous literature involved.The presented control algorithm can ensure that all the signals of the closed-loop large-scale system keep uniformly ultimately bounded and that the tracking error converges to zero asymptotically.The decentralized output feedback fuzzy controller can be applied to address the longitudinal control problem of a string of vehicles within an automated highway system（AHS） and the effectiveness of the design procedure is supported by simulation results.
文摘This paper is concerned with a fuzzy robust H∞ control problem via output feedbackfor a class of uncertain nonlinear systems. The uncertain nonlinear systemsare represented by fuzzy Takagi-Sugeno （T-S） model, and a fuzzy controller is designedbased on the state observer. A sufficient condition for the existence of fuzzycontroller is given in terms of the linear matrix inequalities （LMIs） and the adaptivelaw. Based on Lyapunov stability theorem, the proposed fuzzy control scheme suchthat the desired H∞performance is achieved in the sense that all the closed-loopsignals are uniformly ultimately bounded （UUB）. Simulation results indicate theeffectiveness of the developed control scheme. In this paper, a less conservativefuzzy tracking controller is proposed, where the matching condition and the upperbound are avoided. Comparing with the existing works, the dimension of the LMIsof this paper is reduced.
基金supported by the National Basic Research Program of China (973 Program) (2010CB734104)
文摘A novel group decision-making （GDM） method based on intuitionistic fuzzy sets （IFSs） is developed to evaluate the ergonomics of aircraft cockpit display and control system （ACDCS）. The GDM process with four steps is discussed. Firstly, approaches are proposed to transform four types of common judgement representations into a unified expression by the form of the IFS, and the features of unifications are analyzed. Then, the aggregation operator called the IFSs weighted averaging （IFSWA） operator is taken to synthesize decision-makers’ （DMs’） preferences by the form of the IFS. In this operator, the DM’s reliability weights factors are determined based on the distance measure between their preferences. Finally, an improved score function is used to rank alternatives and to get the best one. An illustrative example proves the proposed method is effective to valuate the ergonomics of the ACDCS.
基金Project(50275150) supported by the National Natural Science Foundation of ChinaProject(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of ChinaProject(05JJ40128) supported by the Natural Science Foundation of Hunan Province, China
文摘Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-Ⅰ intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.
基金This Project was supported by the National Natural Science Foundation of China (60374037 and 60574036)the Opening Project Foundation of National Lab of Industrial Control Technology (0708008).
文摘A constrained generalized predictive control （GPC） algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno （T-S） fuzzy model based on the fuzzy cluster algorithm and the orthogonalleast square method is constructed to approach the nonlinear system. Since its consequence is linear, it can divide the nonlinear system into a number of linear or nearly linear subsystems. For this T-S fuzzy model, a GPC algorithm with input constraints is presented. This strategy takes into account all the constraints of the control signal and its increment, and does not require the calculation of the Diophantine equations. So it needs only a small computer memory and the computational speed is high. The simulation results show a good performance for the nonlinear systems.
文摘ln this paper, FEEC theory is studied. An economical space is a dynamic model for any scope of certain economy and market . ln an economical space, any point represents some economical area or entity and is assigned an variable economic condition Any subspace is assigned an variable economic evaluation. FEEC controller operates oz. economic evaluation and the public parts in economic condition. Any adjustment done by FEEC controller asks the point itself to improve other members to meet the requirements. ln this paper, the template for economic condition and economic evaluation is defined , and then the generic type of economical space and FEE. controller is also given.
基金This project was supported by the National Natural Science Foundation of China (No. 69835001).
文摘A framework of knowledge representation of fuzzy language field and fuzzy language value structure is shown. Then the generalized cell automation that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model are put forward. On this basis, the logic indeterminacy causal inductive automatic reasoning mechanism which is based on fuzzy state description is presented. At the end of this paper its application in the development of intelligent controller is discussed.
文摘Fuzzy technology is a newly developed discipline based on fuzzy mathematics. In the recent years, it has been successfully applied into many areas, such as process control, diagnosis, evaluation, decision making and scheduling, especially in simulation where accurate mathematical models can not or very hard be established. In this paper, to meet the demands of fuzzy simulation, two fuzzy nets will first be presented, which are quite suitable for modeling the parallel or concurrent systems with fuzzy behavior. Then, a concept of active simulation will be introduced, in which the simulation model not only can show its fuzzy behavior, but also has a certain ability which can actively perform many very useful actions, such as automatic warning, realtime monitoring, simulation result checking, simulation model self-adapting, error recovery, simulating path tracing, system states inspecting and exception handling, by a unified approach while some specified events occur. The simulation model described by this powerful simulation modeling tool is concurrently driven by a network interpreter and an event monitor that all can be implemented by software or hardware. Besides, some interesting applications are given in the paper.
