In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new se...In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.展开更多
In many problems,to analyze the process/metabolism behavior,a mod-el of the system is identified.The main gap is the weakness of current methods vs.noisy environments.The primary objective of this study is to present a...In many problems,to analyze the process/metabolism behavior,a mod-el of the system is identified.The main gap is the weakness of current methods vs.noisy environments.The primary objective of this study is to present a more robust method against uncertainties.This paper proposes a new deep learning scheme for modeling and identification applications.The suggested approach is based on non-singleton type-3 fuzzy logic systems(NT3-FLSs)that can support measurement errors and high-level uncertainties.Besides the rule optimization,the antecedent parameters and the level of secondary memberships are also adjusted by the suggested square root cubature Kalmanfilter(SCKF).In the learn-ing algorithm,the presented NT3-FLSs are deeply learned,and their nonlinear structure is preserved.The designed scheme is applied for modeling carbon cap-ture and sequestration problem using real-world data sets.Through various ana-lyses and comparisons,the better efficiency of the proposed fuzzy modeling scheme is verified.The main advantages of the suggested approach include better resistance against uncertainties,deep learning,and good convergence.展开更多
Active control technology has been investigated and applied in numerous building structures and infrastructures since 1972 when it was firstly introduced into the civil engineering field by Professor JTP Yao.Now,half ...Active control technology has been investigated and applied in numerous building structures and infrastructures since 1972 when it was firstly introduced into the civil engineering field by Professor JTP Yao.Now,half a century has passed,a variety of control systems have been invented and implemented by researchers and engineers from all over the world.The recent years have witnessed remarkable research attempts and progress devoted to the development in this area based on modern control theory.However,there are still some unknown areas which are worthy of being explored in depth.One of such examples is the application of tuned mass dampers(TMD)to the flutter vibration control of long span bridges.Although applications of TMDs to bridges have been sighted in practice,their genuine effectiveness remains a serious question.The issues relating to how the coupled effect of TMD’s linear force being restricted by the rotational velocity of bridge’s deck during wind excitations which may eventually leads to flutter vibrations,remains unanswered.Such unusual phenomena and limitations were initially discovered and reported by the author sixteen years ago when investigating the barge ship crane hook’s swing motion control.In recent years,the author has invented the active rotary inertia driver(ARID)system which now has been granted patents in China,the US,Europe(including the UK,France,and Germany),Russia,Brazil,India,South Africa,Canada,Australia,Japan and Korean,etc.The ARID is an active control system which could exert direct control torque or moment to the target structures with rotational motions or vibrations natures,including and not limited to buildings,bridges or offshore platforms subjected to winds,earthquakes,and waves excitations.Furthermore,the ARID control system and its methodology can also be applicable to various mechanical systems including but not limited to cranes,vehicles,trains,ships,aircrafts,space crafts,satellites,and robotics.In this paper,the theory,modelling,comprehensive parametric analysis and case study of the ARID system for flutter vibration control of bridges will be discussed,as well as its promising applications in other various occasions.展开更多
基金This research is financially supported by the Ministry of Science and Technology of China(Grant No.2019YFE0112400)the Department of Science and Technology of Shandong Province(Grant No.2021CXGC011204).
文摘In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.
基金supported by the project of the National Social Science Fundation(21BJL052,20BJY020,20BJL127,19BJY090)the 2018 Fujian Social Science Planning Project(FJ2018B067)The Planning Fund Project of Humanities and Social Sciences Research of the Ministry of Education in 2019(19YJA790102),The grant has been received by Aoqi Xu.
文摘In many problems,to analyze the process/metabolism behavior,a mod-el of the system is identified.The main gap is the weakness of current methods vs.noisy environments.The primary objective of this study is to present a more robust method against uncertainties.This paper proposes a new deep learning scheme for modeling and identification applications.The suggested approach is based on non-singleton type-3 fuzzy logic systems(NT3-FLSs)that can support measurement errors and high-level uncertainties.Besides the rule optimization,the antecedent parameters and the level of secondary memberships are also adjusted by the suggested square root cubature Kalmanfilter(SCKF).In the learn-ing algorithm,the presented NT3-FLSs are deeply learned,and their nonlinear structure is preserved.The designed scheme is applied for modeling carbon cap-ture and sequestration problem using real-world data sets.Through various ana-lyses and comparisons,the better efficiency of the proposed fuzzy modeling scheme is verified.The main advantages of the suggested approach include better resistance against uncertainties,deep learning,and good convergence.
基金supported by the Ministry of Science and Technology of China (Grant No.2019YFE0112400)the Department of Science and Technology of Shandong Province (Grant No.2021CXGC011204)Liaoning Provincial Key Laboratory of Safety and Protection for Infrastructure Engineering。
文摘Active control technology has been investigated and applied in numerous building structures and infrastructures since 1972 when it was firstly introduced into the civil engineering field by Professor JTP Yao.Now,half a century has passed,a variety of control systems have been invented and implemented by researchers and engineers from all over the world.The recent years have witnessed remarkable research attempts and progress devoted to the development in this area based on modern control theory.However,there are still some unknown areas which are worthy of being explored in depth.One of such examples is the application of tuned mass dampers(TMD)to the flutter vibration control of long span bridges.Although applications of TMDs to bridges have been sighted in practice,their genuine effectiveness remains a serious question.The issues relating to how the coupled effect of TMD’s linear force being restricted by the rotational velocity of bridge’s deck during wind excitations which may eventually leads to flutter vibrations,remains unanswered.Such unusual phenomena and limitations were initially discovered and reported by the author sixteen years ago when investigating the barge ship crane hook’s swing motion control.In recent years,the author has invented the active rotary inertia driver(ARID)system which now has been granted patents in China,the US,Europe(including the UK,France,and Germany),Russia,Brazil,India,South Africa,Canada,Australia,Japan and Korean,etc.The ARID is an active control system which could exert direct control torque or moment to the target structures with rotational motions or vibrations natures,including and not limited to buildings,bridges or offshore platforms subjected to winds,earthquakes,and waves excitations.Furthermore,the ARID control system and its methodology can also be applicable to various mechanical systems including but not limited to cranes,vehicles,trains,ships,aircrafts,space crafts,satellites,and robotics.In this paper,the theory,modelling,comprehensive parametric analysis and case study of the ARID system for flutter vibration control of bridges will be discussed,as well as its promising applications in other various occasions.
