A significant number and range of challenges besetting sustainability can be traced to the actions and inter actions of multiple autonomous agents(people mostly)and the entities they create(e.g.,institutions,policies,...A significant number and range of challenges besetting sustainability can be traced to the actions and inter actions of multiple autonomous agents(people mostly)and the entities they create(e.g.,institutions,policies,social network)in the corresponding social-environmental systems(SES).To address these challenges,we need to understand decisions made and actions taken by agents,the outcomes of their actions,including the feedbacks on the corresponding agents and environment.The science of complex adaptive systems-complex adaptive sys tems(CAS)science-has a significant potential to handle such challenges.We address the advantages of CAS science for sustainability by identifying the key elements and challenges in sustainability science,the generic features of CAS,and the key advances and challenges in modeling CAS.Artificial intelligence and data science combined with agent-based modeling promise to improve understanding of agents’behaviors,detect SES struc tures,and formulate SES mechanisms.展开更多
This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergen...This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergence in social systems.By integrating mathematical models,agent-based modeling,network dynamic analysis,and hybrid modeling approaches,the study applies CAS theory to case studies in economic markets,political decision-making,and social interactions.The experimental results demonstrate that local interactions among individual agents can give rise to complex global phenomena,such as market fluctuations,opinion polarization,and sudden outbreaks of social movements.This framework not only provides a more robust explanation for the nonlinear dynamics and abrupt transitions that traditional models often fail to capture,but also offers valuable decision-support tools for public policy formulation,social governance,and risk management.Emphasizing the importance of interdisciplinary approaches,this work outlines future research directions in high-performance computing,artificial intelligence,and real-time data integration to further advance the theoretical and practical applications of CAS in the social sciences.展开更多
In rural life,everything is connected to everything else.Seen as a complex adaptive system,the ＂rural＂ in most regions of the world has evolved over many centuries and is well known to have endured invasive predatio...In rural life,everything is connected to everything else.Seen as a complex adaptive system,the ＂rural＂ in most regions of the world has evolved over many centuries and is well known to have endured invasive predations and conflicts and to have adapted to changing conditions,both physical and human,many times.Such changes are recorded in the culture and in the landscapes which have continuously evolved and which characterize rural places today.These features of contemporary rural life-economy,culture and landscape-are the key elements of rural systems.Interestingly,they have also become the elements that attract tourists to rural areas.This theoretical paper,starts from the position that the rural world as a whole is complex and that systems adjust in the face of uncertainty,and a type of dynamism that is generated externally in the form of shocks and stresses.Complex Adaptive Systems theory provides an excellent opportunity to examine living systems such as Globally Important Agricultural Heritage Systems （GIAHS） in China that can provide new perspectives on resilience and self-organizing capabilities of the system.The paper suggests that adopting such approaches in contemporary research will produce new insights of whole systems and stem the tide of mainstream scientific research that reduces systems to their component parts and studies them with micro-techniques,while mostly failing to reintegrate the component parts back into the system as a whole.By reviewing this approach in relation to GIAHS and by introducing tourism into the rural village system,as a perturbation,we can create new ways to understand the effects of rural development interventions in ancient landscapes such as those which cover many parts of rural China today.展开更多
Complex adaptive systems （cas） - systems that involve many components that adapt or learn as they interact - are at the heart of important contemporary problems. The study of cas poses unique challenges： Some of ou...Complex adaptive systems （cas） - systems that involve many components that adapt or learn as they interact - are at the heart of important contemporary problems. The study of cas poses unique challenges： Some of our most powerful muthemutical tools, particularly methods involivng fixed points, attractors, and the like, are of limited help in understanding the development of cas. This paper suggests ways to modify research methods and tools, with an emphasis on the role of computer-based models, to increase our understanding of cas.展开更多
The adaptive systems theory to be presented in this paper consists of two closely related parts: adaptive estimation (or filtering, prediction) and adaptive control of dynamical systems. Both adaptive estimation and c...The adaptive systems theory to be presented in this paper consists of two closely related parts: adaptive estimation (or filtering, prediction) and adaptive control of dynamical systems. Both adaptive estimation and control are nonlinear mappings of the on-line observed signals of dynamical systems, where the main features are the uncertain-ties in both the system's structure and external disturbances, and the non-stationarity and dependency of the system signals. Thus, a key difficulty in establishing a mathematical theory of adaptive systems lies in how to deal with complicated nonlinear stochastic dynamical systems which describe the adaptation processes. In this paper, we will illustrate some of the basic concepts, methods and results through some simple examples. The following fundamental questions will be discussed: How much information is needed for estimation? How to deal with uncertainty by adaptation? How to analyze an adaptive system? What are the convergence or tracking performances of adaptation? How to find the proper rate of adaptation in some sense? We will also explore the following more fundamental questions: How much uncertainty can be dealt with by adaptation ? What are the limitations of adaptation ? How does the performance of adaptation depend on the prior information ? We will partially answer these questions by finding some 'critical values' and establishing some 'Impossibility Theorems' for the capability of adaptation, for several basic classes of nonlinear dynamical control systems with either parametric or nonparametric uncertainties.展开更多
The design and application of morphing systems are ongoing issues compelling the aviation industry.The Clean Sky-program represents the most significant aeronautical research ever launched in Europe on advanced techno...The design and application of morphing systems are ongoing issues compelling the aviation industry.The Clean Sky-program represents the most significant aeronautical research ever launched in Europe on advanced technologies for greening next-generation aircraft.The primary purpose of the program is to develop new concepts aimed at decreasing the effects of aviation on the environment,increasing reliability,and promoting eco-friendly mobility.These ambitions are pursued through research on enabling technologies fostering noise and gas emissions reduction,mainly by improving aircraft aerodynamic performances.Within the Clean Sky framework,a multimodal morphing flap device was designed based on tight industrial requirements and tailored for large civil aircraft applications.The flap is deployed in one unique setting,and its cross section is morphed differently in take-off and landing to get the necessary extra lift for the specific flight phase.Moreover,during the cruise,the tip of the flap is deflected for load control and induced drag reduction.Before manufacturing the first flap prototype,a high-speed(Ma=0.3),large-scale test campaign(geometric scale factor 1:3)was deemed necessary to validate the performance improvements brought by this novel system at the aircraft level.On the other hand,the geometrical scaling of the flap prototype was considered impracticable due to the unscalability of the embedded mechanisms and actuators for shape transition.Therefore,a new architecture was conceived for the flap model to comply with the scaled dimensions requirements,withstand the relevant loads expected during the wind tunnel tests and emulate the shape transition capabilities of the true-scale flap.Simplified strategies were developed to effectively morph the model during wind tunnel tests while ensuring the robustness of each morphed configuration and maintaining adequate stiffness levels to prevent undesirable deviations from the intended aerodynamic shapes.Additionally,a simplified design was conceived for the flap-wing interface,allowing for quick adjustments of the flap setting and enabling load transmission paths like those arising between the full-scale flap and the wing.The design process followed for the definition of this challenging wind tunnel model has been addressed in this work,covering the definition of the conceptual layout,the numerical evaluation of the most severe loads expected during the test,and the verification of the structural layout by means of advanced finite element analyses.展开更多
Traditional e-commerce recommendation systems often struggle with dynamic user preferences and a vast array of products,leading to suboptimal user experiences.To address this,our study presents a Personalized Adaptive...Traditional e-commerce recommendation systems often struggle with dynamic user preferences and a vast array of products,leading to suboptimal user experiences.To address this,our study presents a Personalized Adaptive Multi-Product Recommendation System(PAMR)leveraging transfer learning and Bi-GRU(Bidirectional Gated Recurrent Units).Using a large dataset of user reviews from Amazon and Flipkart,we employ transfer learning with pre-trained models(AlexNet,GoogleNet,ResNet-50)to extract high-level attributes from product data,ensuring effective feature representation even with limited data.Bi-GRU captures both spatial and sequential dependencies in user-item interactions.The innovation of this study lies in the innovative feature fusion technique that combines the strengths of multiple transfer learning models,and the integration of an attention mechanism within the Bi-GRU framework to prioritize relevant features.Our approach addresses the classic recommendation systems that often face challenges such as cold start along with data sparsity difficulties,by utilizing robust user and item representations.The model demonstrated an accuracy of up to 96.9%,with precision and an F1-score of 96.2%and 96.97%,respectively,on the Amazon dataset,significantly outperforming the baselines and marking a considerable advancement over traditional configurations.This study highlights the effectiveness of combining transfer learning with Bi-GRU for scalable and adaptive recommendation systems,providing a versatile solution for real-world applications.展开更多
The problem of robust stabilization for nonlinear systems with partially known uncertainties is considered in this paper. The required information about uncertainties in the system is merely that the uncertainties are...The problem of robust stabilization for nonlinear systems with partially known uncertainties is considered in this paper. The required information about uncertainties in the system is merely that the uncertainties are bounded, but the upper bounds are incompletely known. This paper can be viewed as an extension of the work in reference [1]. To compensate the uncertainties, an adaptive robust controller based on Lyapunov method is proposed and the design algorithm is also suggested. Compared with some previous controllers which can only ensure ultimate uniform boundedness of the systems, the controller given in the paper can make sure that the obtained closed-loop system is asymptotically stable in the large. Simulations show that the method presented is available and effective.展开更多
This paper presents a robust adaptive state feedback control scheme for a class of parametric-strict-feedback nonlinear systems in the presence of time varying actuator failures. The designed adaptive controller compe...This paper presents a robust adaptive state feedback control scheme for a class of parametric-strict-feedback nonlinear systems in the presence of time varying actuator failures. The designed adaptive controller compensates a general class of actuator failures without any need for explicit fault detection. The parameters, times, and patterns of the considered failures are completely unknown. The proposed controller is constructed based on a backstepping design method. The global boundedness of all the closed-loop signals is guaranteed and the tracking error is proved to converge to a small neighborhood of the origin. The proposed approach is employed for a two-axis positioning stage system as well as an aircraft wing system. The simulation results show the correctness and effectiveness of the proposed robust adaptive actuator failure compensation approach.展开更多
An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy ...An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy is composed of a linear adaptive controller, a neural network(NN) based nonlinear adaptive controller and a switching mechanism. An incremental model is derived to represent the considered system and an improved robust adaptive law is chosen to update the parameters of the linear adaptive controller. A new performance criterion of the switching mechanism is designed to select the proper controller. Using this control scheme, all the signals in the system are proved to be bounded. Numerical examples verify the effectiveness of the proposed algorithm.展开更多
The synchronization of hyperchaotic Chen systems is considered. An adaptive synchronization approach and a cascade adaptive synchronization approach are presented to synchronize a drive system and a response system. B...The synchronization of hyperchaotic Chen systems is considered. An adaptive synchronization approach and a cascade adaptive synchronization approach are presented to synchronize a drive system and a response system. By utilizing an adaptive controller based on the dynamic compensation mechanism, exact knowledge of the systems is not necessarily required, and the synchronous speed is controllable by tuning the controller parameters. Sufficient conditions for the asymptotic stability of the two synchronization schemes are derived. Numerical simulation results demonstrate that the adaptive synchronization scheme with four control inputs and the cascade adaptive synchronization scheme with only one control signal are effective and feasible in chaos synchronization of hyperchaotic systems.展开更多
An adaptive fuzzy tracking control scheme is presented for a class of switched multi-input-multi-output (MIMO) nonlinear systems with disturbances under arbitrary switching. Adaptive fuzzy systems are employed to appr...An adaptive fuzzy tracking control scheme is presented for a class of switched multi-input-multi-output (MIMO) nonlinear systems with disturbances under arbitrary switching. Adaptive fuzzy systems are employed to approximate the unknown functions on line,and a systematic framework for adaptive fuzzy tracking controller design is given,where the dynamic surface control (DSC) approach is used to solve the problem of "explosion of complexity"in the backstepping design procedure. According to the common Lyapunov function theory,it is proved that the proposed controller can guarantee the boundedness of all signals in the closed loop system. Finally,the simulation results demonstrate the validity of the control approach.展开更多
Human consciousness is the most interesting and mysterious phenomenon in the world.In this paper, the results of the computational studying and simulation of the conscious behaviour,such as the learning of language an...Human consciousness is the most interesting and mysterious phenomenon in the world.In this paper, the results of the computational studying and simulation of the conscious behaviour,such as the learning of language and image patterns, traditional conditioning, association, imagination and dream, have been presented. Based on these results, an experimental conscious systemCONSCITRON, has been developed. Further discussion on development of adaptive conscioussystems is also provided.展开更多
Intelligent Adaptive Control(AC) has remarkable advantages in the control system design of aero-engine which has strong nonlinearity and uncertainty. Inspired by the Nonlinear Autoregressive Moving Average(NARMA)-L2 a...Intelligent Adaptive Control(AC) has remarkable advantages in the control system design of aero-engine which has strong nonlinearity and uncertainty. Inspired by the Nonlinear Autoregressive Moving Average(NARMA)-L2 adaptive control, a novel Nonlinear State Space Equation(NSSE) based Adaptive neural network Control(NSSE-AC) method is proposed for the turbo-shaft engine control system design. The proposed NSSE model is derived from a special neural network with an extra layer, and the rotor speed of the gas turbine is taken as the main state variable which makes the NSSE model be able to capture the system dynamic better than the NARMA-L2 model. A hybrid Recursive Least-Square and Levenberg-Marquardt(RLS-LM) algorithm is advanced to perform the online learning of the neural network, which further enhances both the accuracy of the NSSE model and the performance of the adaptive controller. The feedback correction is also utilized in the NSSE-AC system to eliminate the steady-state tracking error. Simulation results show that, compared with the NARMA-L2 model, the NSSE model of the turboshaft engine is more accurate. The maximum modeling error is decreased from 5.92% to 0.97%when the LM algorithm is introduced to optimize the neural network parameters. The NSSE-AC method can not only achieve a better main control loop performance than the traditional controller but also limit all the constraint parameters efficiently with quick and accurate switching responses even if component degradation exists. Thus, the effectiveness of the NSSE-AC method is validated.展开更多
The solving of dynamic matrix square root(DMSR)problems is frequently encountered in many scientific and engineering fields.Although the original zeroing neural network is powerful for solving the DMSR,it cannot vanis...The solving of dynamic matrix square root(DMSR)problems is frequently encountered in many scientific and engineering fields.Although the original zeroing neural network is powerful for solving the DMSR,it cannot vanish the influence of the noise perturbations,and its constant-coefficient design scheme cannot accelerate the convergence speed.Therefore,a noise-tolerate and adaptive coefficient zeroing neural network(NTACZNN)is raised to enhance the robust noise immunity performance and accelerate the conver-gence speed simultaneously.Then,the global convergence and robustness of the pro-posed NTACZNN are theoretically analysed under an ideal environment and noise-perturbed circumstances.Furthermore,some illustrative simulation examples are designed and performed in order to substantiate the efficacy and advantage of the NTACZNN for the DMSR problem solution.Compared with some existing ZNNs,the proposed NTACZNN possesses advanced performance in terms of noise tolerance,solution accuracy,and convergence rate.展开更多
This article provides a flexible-joint-manipulator,which incorporates with three means to make its mechanical arm come into compliant contact with the objects with a force kept within an acceptable range. At first,the...This article provides a flexible-joint-manipulator,which incorporates with three means to make its mechanical arm come into compliant contact with the objects with a force kept within an acceptable range. At first,the Cartesian impedance control law is introduced on the basis of virtual decomposition to realize the compliance control. Then,adaptive dynamic joint compensators on all joints are used to achieve more precise control. Finally,a Cartesian force-feedback path generation is developed for collision ...展开更多
A novel nonlinear adaptive control method is presented for a near-space hypersonic vehicle （NHV） in the presence of strong uncertainties and disturbances. The control law consists of the optimal generalized predicti...A novel nonlinear adaptive control method is presented for a near-space hypersonic vehicle （NHV） in the presence of strong uncertainties and disturbances. The control law consists of the optimal generalized predictive controller （OGPC） and the functional link network （FLN） direct adaptive law. OGPC is a continuous-time nonlinear predictive control law. The FLN adaptive law is used to offset the unknown uncertainties and disturbances in a flight through the online learning. The learning process does not need any offline training phase. The stability analyses of the NHV close-loop system are provided and it is proved that the system error and the weight learning error are uniformly ultimately hounded. Simulation results show the satisfactory performance of the con- troller for the attitude tracking.展开更多
SARISTU was a big cooperation project granted by the European Commission,7th Framework Programme,carried out between 2011 and 2015.It dealt with smart aeronautic structures,both morphing and sensored;its main target w...SARISTU was a big cooperation project granted by the European Commission,7th Framework Programme,carried out between 2011 and 2015.It dealt with smart aeronautic structures,both morphing and sensored;its main target was to demonstrate the feasibility of designing,manufacturing and operating in representative environment,instrumented structures.Till now,it represents the major effort carried out within the European Union on the development of adaptive architectures for air systems.Inside that big activity,the realization of an Adaptive Trailing Edge Device(ATED)for wing camber adaptations aimed at compensating the weight reduction following the fuel consumption during cruise was addressed.It made the core of investigations target variable geometry aircraft components together with two other analyses concerning the development of shape-changing winglet and droop nose.ATED activities were conducted by the Italian Aerospace Research Centre(CIRA)in tight cooperation with the University of Napoli,"Federico II",who coordinated a group of 12 different partners from 8 different nations(France,Germany,Greece,the Netherlands,Israel,Spain,Turkey,and Italy).In this paper,an integral synthesis of that work is reported,with a focus on the definition and realization of the components of the presented device.The publication is in fact meant as the first part of a series that is aimed at overviewing the whole adaptive trailing edge development,till wind tunnel tests execution.Such a concise report is a critical and harmonized review of what have been performed by many colleagues spread all over Europe,all of which are duly recalled in the reported bibliography where the reader may access more detailed information and descriptions.In detail,the paper starts with a general introduction of the concept and its aims,to move to the specs definition immediately after.Then,it deals with a short but comprehensive description of the main ATED components:structural skeleton,skin,actuation and sensing systems.It is worth remarking that the paragraph dedicated to the body frame includes some discussion about aeroelastic assessment and manufacture,seen as complementation for a complete assessment of the design constraints.展开更多
Semi-active dampers are used in base-isolation to reduce the seismic response of civil engineering structures. In the present study, a new semi-active damping system using variable amplification will be investigated f...Semi-active dampers are used in base-isolation to reduce the seismic response of civil engineering structures. In the present study, a new semi-active damping system using variable amplification will be investigated for adaptive baseisolation. It uses a novel variable amplification device （VAD） connected in series with a passive damper. The VAD is capable of producing multiple amplification factors, each corresponding to a different amplification state. Forces from the damper are amplified to the structure according to the current amplification state, which is selected via a semi-active control algorithm specifically tailored to the system＇s tmique damping characteristics. To demonstrate the effectiveness of the VAD-damper system for adaptive base-isolation, numerical simulations are conducted for three and seven-story base-isolated buildings subject to both far and near-field ground motions. The results indicate that the system can achieve significant reductions in response compared to the base-isolated buildings with no damper. The proposed system is also found to perform well compared to a typical semi-active damper.展开更多
基金The National Science Foundation funded this research under the Dy-namics of Coupled Natural and Human Systems program(Grants No.DEB-1212183 and BCS-1826839)support from San Diego State University and Auburn University.
文摘A significant number and range of challenges besetting sustainability can be traced to the actions and inter actions of multiple autonomous agents(people mostly)and the entities they create(e.g.,institutions,policies,social network)in the corresponding social-environmental systems(SES).To address these challenges,we need to understand decisions made and actions taken by agents,the outcomes of their actions,including the feedbacks on the corresponding agents and environment.The science of complex adaptive systems-complex adaptive sys tems(CAS)science-has a significant potential to handle such challenges.We address the advantages of CAS science for sustainability by identifying the key elements and challenges in sustainability science,the generic features of CAS,and the key advances and challenges in modeling CAS.Artificial intelligence and data science combined with agent-based modeling promise to improve understanding of agents’behaviors,detect SES struc tures,and formulate SES mechanisms.
文摘This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergence in social systems.By integrating mathematical models,agent-based modeling,network dynamic analysis,and hybrid modeling approaches,the study applies CAS theory to case studies in economic markets,political decision-making,and social interactions.The experimental results demonstrate that local interactions among individual agents can give rise to complex global phenomena,such as market fluctuations,opinion polarization,and sudden outbreaks of social movements.This framework not only provides a more robust explanation for the nonlinear dynamics and abrupt transitions that traditional models often fail to capture,but also offers valuable decision-support tools for public policy formulation,social governance,and risk management.Emphasizing the importance of interdisciplinary approaches,this work outlines future research directions in high-performance computing,artificial intelligence,and real-time data integration to further advance the theoretical and practical applications of CAS in the social sciences.
基金Chinese Academy of Sciences Visiting Professorship for Senior International Scientists (Grant No.Y0S00100KD)
文摘In rural life,everything is connected to everything else.Seen as a complex adaptive system,the ＂rural＂ in most regions of the world has evolved over many centuries and is well known to have endured invasive predations and conflicts and to have adapted to changing conditions,both physical and human,many times.Such changes are recorded in the culture and in the landscapes which have continuously evolved and which characterize rural places today.These features of contemporary rural life-economy,culture and landscape-are the key elements of rural systems.Interestingly,they have also become the elements that attract tourists to rural areas.This theoretical paper,starts from the position that the rural world as a whole is complex and that systems adjust in the face of uncertainty,and a type of dynamism that is generated externally in the form of shocks and stresses.Complex Adaptive Systems theory provides an excellent opportunity to examine living systems such as Globally Important Agricultural Heritage Systems （GIAHS） in China that can provide new perspectives on resilience and self-organizing capabilities of the system.The paper suggests that adopting such approaches in contemporary research will produce new insights of whole systems and stem the tide of mainstream scientific research that reduces systems to their component parts and studies them with micro-techniques,while mostly failing to reintegrate the component parts back into the system as a whole.By reviewing this approach in relation to GIAHS and by introducing tourism into the rural village system,as a perturbation,we can create new ways to understand the effects of rural development interventions in ancient landscapes such as those which cover many parts of rural China today.
文摘Complex adaptive systems （cas） - systems that involve many components that adapt or learn as they interact - are at the heart of important contemporary problems. The study of cas poses unique challenges： Some of our most powerful muthemutical tools, particularly methods involivng fixed points, attractors, and the like, are of limited help in understanding the development of cas. This paper suggests ways to modify research methods and tools, with an emphasis on the role of computer-based models, to increase our understanding of cas.
基金This work is supported by the National Natural Science Foundation of China and the National Key Project of China.This paper is based on the presentation at the International Symposium on"Intervention and Adaptation in Complex Systems"held in Beijing from
文摘The adaptive systems theory to be presented in this paper consists of two closely related parts: adaptive estimation (or filtering, prediction) and adaptive control of dynamical systems. Both adaptive estimation and control are nonlinear mappings of the on-line observed signals of dynamical systems, where the main features are the uncertain-ties in both the system's structure and external disturbances, and the non-stationarity and dependency of the system signals. Thus, a key difficulty in establishing a mathematical theory of adaptive systems lies in how to deal with complicated nonlinear stochastic dynamical systems which describe the adaptation processes. In this paper, we will illustrate some of the basic concepts, methods and results through some simple examples. The following fundamental questions will be discussed: How much information is needed for estimation? How to deal with uncertainty by adaptation? How to analyze an adaptive system? What are the convergence or tracking performances of adaptation? How to find the proper rate of adaptation in some sense? We will also explore the following more fundamental questions: How much uncertainty can be dealt with by adaptation ? What are the limitations of adaptation ? How does the performance of adaptation depend on the prior information ? We will partially answer these questions by finding some 'critical values' and establishing some 'Impossibility Theorems' for the capability of adaptation, for several basic classes of nonlinear dynamical control systems with either parametric or nonparametric uncertainties.
基金carried out in the framework of AIRGREEN2 Project,which gratefully received funding from the Clean Sky 2 Joint Undertaking,under the European’s Union Horizon 2020 Research and Innovation Program,Grant Agreement(No.807089—REG GAM 4822018—H2020-IBA-CS2-GAMS-2017)funded by TUBITAK 2214-A-International Research Fellowship Programme for Ph.D.Students。
文摘The design and application of morphing systems are ongoing issues compelling the aviation industry.The Clean Sky-program represents the most significant aeronautical research ever launched in Europe on advanced technologies for greening next-generation aircraft.The primary purpose of the program is to develop new concepts aimed at decreasing the effects of aviation on the environment,increasing reliability,and promoting eco-friendly mobility.These ambitions are pursued through research on enabling technologies fostering noise and gas emissions reduction,mainly by improving aircraft aerodynamic performances.Within the Clean Sky framework,a multimodal morphing flap device was designed based on tight industrial requirements and tailored for large civil aircraft applications.The flap is deployed in one unique setting,and its cross section is morphed differently in take-off and landing to get the necessary extra lift for the specific flight phase.Moreover,during the cruise,the tip of the flap is deflected for load control and induced drag reduction.Before manufacturing the first flap prototype,a high-speed(Ma=0.3),large-scale test campaign(geometric scale factor 1:3)was deemed necessary to validate the performance improvements brought by this novel system at the aircraft level.On the other hand,the geometrical scaling of the flap prototype was considered impracticable due to the unscalability of the embedded mechanisms and actuators for shape transition.Therefore,a new architecture was conceived for the flap model to comply with the scaled dimensions requirements,withstand the relevant loads expected during the wind tunnel tests and emulate the shape transition capabilities of the true-scale flap.Simplified strategies were developed to effectively morph the model during wind tunnel tests while ensuring the robustness of each morphed configuration and maintaining adequate stiffness levels to prevent undesirable deviations from the intended aerodynamic shapes.Additionally,a simplified design was conceived for the flap-wing interface,allowing for quick adjustments of the flap setting and enabling load transmission paths like those arising between the full-scale flap and the wing.The design process followed for the definition of this challenging wind tunnel model has been addressed in this work,covering the definition of the conceptual layout,the numerical evaluation of the most severe loads expected during the test,and the verification of the structural layout by means of advanced finite element analyses.
文摘Traditional e-commerce recommendation systems often struggle with dynamic user preferences and a vast array of products,leading to suboptimal user experiences.To address this,our study presents a Personalized Adaptive Multi-Product Recommendation System(PAMR)leveraging transfer learning and Bi-GRU(Bidirectional Gated Recurrent Units).Using a large dataset of user reviews from Amazon and Flipkart,we employ transfer learning with pre-trained models(AlexNet,GoogleNet,ResNet-50)to extract high-level attributes from product data,ensuring effective feature representation even with limited data.Bi-GRU captures both spatial and sequential dependencies in user-item interactions.The innovation of this study lies in the innovative feature fusion technique that combines the strengths of multiple transfer learning models,and the integration of an attention mechanism within the Bi-GRU framework to prioritize relevant features.Our approach addresses the classic recommendation systems that often face challenges such as cold start along with data sparsity difficulties,by utilizing robust user and item representations.The model demonstrated an accuracy of up to 96.9%,with precision and an F1-score of 96.2%and 96.97%,respectively,on the Amazon dataset,significantly outperforming the baselines and marking a considerable advancement over traditional configurations.This study highlights the effectiveness of combining transfer learning with Bi-GRU for scalable and adaptive recommendation systems,providing a versatile solution for real-world applications.
基金supported in part by National Natural Science Foundation of China(61573108,61273192,61333013)the Ministry of Education of New Century Excellent Talent(NCET-12-0637)+1 种基金Natural Science Foundation of Guangdong Province through the Science Fund for Distinguished Young Scholars(S20120011437)Doctoral Fund of Ministry of Education of China(20124420130001)
文摘The problem of robust stabilization for nonlinear systems with partially known uncertainties is considered in this paper. The required information about uncertainties in the system is merely that the uncertainties are bounded, but the upper bounds are incompletely known. This paper can be viewed as an extension of the work in reference [1]. To compensate the uncertainties, an adaptive robust controller based on Lyapunov method is proposed and the design algorithm is also suggested. Compared with some previous controllers which can only ensure ultimate uniform boundedness of the systems, the controller given in the paper can make sure that the obtained closed-loop system is asymptotically stable in the large. Simulations show that the method presented is available and effective.
基金supported by Esfahan Regional Electric Company(EREC)
文摘This paper presents a robust adaptive state feedback control scheme for a class of parametric-strict-feedback nonlinear systems in the presence of time varying actuator failures. The designed adaptive controller compensates a general class of actuator failures without any need for explicit fault detection. The parameters, times, and patterns of the considered failures are completely unknown. The proposed controller is constructed based on a backstepping design method. The global boundedness of all the closed-loop signals is guaranteed and the tracking error is proved to converge to a small neighborhood of the origin. The proposed approach is employed for a two-axis positioning stage system as well as an aircraft wing system. The simulation results show the correctness and effectiveness of the proposed robust adaptive actuator failure compensation approach.
基金Supported by the National Natural Science Foundation of China(61333010,21376077,61203157)the Natural Science Foundation of Shanghai(14ZR1421800)State Key Laboratory of Synthetical Automation for Process Industries(PAL-N201404)
文摘An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy is composed of a linear adaptive controller, a neural network(NN) based nonlinear adaptive controller and a switching mechanism. An incremental model is derived to represent the considered system and an improved robust adaptive law is chosen to update the parameters of the linear adaptive controller. A new performance criterion of the switching mechanism is designed to select the proper controller. Using this control scheme, all the signals in the system are proved to be bounded. Numerical examples verify the effectiveness of the proposed algorithm.
基金Project supported by the National Basic Research Program of China (Grant No. 2007CB210106)
文摘The synchronization of hyperchaotic Chen systems is considered. An adaptive synchronization approach and a cascade adaptive synchronization approach are presented to synchronize a drive system and a response system. By utilizing an adaptive controller based on the dynamic compensation mechanism, exact knowledge of the systems is not necessarily required, and the synchronous speed is controllable by tuning the controller parameters. Sufficient conditions for the asymptotic stability of the two synchronization schemes are derived. Numerical simulation results demonstrate that the adaptive synchronization scheme with four control inputs and the cascade adaptive synchronization scheme with only one control signal are effective and feasible in chaos synchronization of hyperchaotic systems.
基金Sponsored by the National Natural Science Foundation of China (Grant No.60974106,91116017 )the Aeronautical Science Fund (Grant No.20095152028)the Funding for Outstanding Doctoral Dissertation in NUAA (Grant No.BCXJ10-04)
文摘An adaptive fuzzy tracking control scheme is presented for a class of switched multi-input-multi-output (MIMO) nonlinear systems with disturbances under arbitrary switching. Adaptive fuzzy systems are employed to approximate the unknown functions on line,and a systematic framework for adaptive fuzzy tracking controller design is given,where the dynamic surface control (DSC) approach is used to solve the problem of "explosion of complexity"in the backstepping design procedure. According to the common Lyapunov function theory,it is proved that the proposed controller can guarantee the boundedness of all signals in the closed loop system. Finally,the simulation results demonstrate the validity of the control approach.
文摘Human consciousness is the most interesting and mysterious phenomenon in the world.In this paper, the results of the computational studying and simulation of the conscious behaviour,such as the learning of language and image patterns, traditional conditioning, association, imagination and dream, have been presented. Based on these results, an experimental conscious systemCONSCITRON, has been developed. Further discussion on development of adaptive conscioussystems is also provided.
基金co-supported by the National Science and Technology Major Project, China (No. J2019-Ⅰ-0010-0010)the Project funded by China Postdoctoral Science Foundation (No. 2021M701692)+3 种基金the Fundamental Research Funds for the Central Universities, China (No. NS2022029)the Postgraduate Research & Practice Innovation Program of NUAA, China (No. xcxjh20220206)the National Natural Science Foundation of China (No. 51976089)Jiangsu Funding Program for Excellent Postdoctoral Talent, China (No. 2022ZB202)。
文摘Intelligent Adaptive Control(AC) has remarkable advantages in the control system design of aero-engine which has strong nonlinearity and uncertainty. Inspired by the Nonlinear Autoregressive Moving Average(NARMA)-L2 adaptive control, a novel Nonlinear State Space Equation(NSSE) based Adaptive neural network Control(NSSE-AC) method is proposed for the turbo-shaft engine control system design. The proposed NSSE model is derived from a special neural network with an extra layer, and the rotor speed of the gas turbine is taken as the main state variable which makes the NSSE model be able to capture the system dynamic better than the NARMA-L2 model. A hybrid Recursive Least-Square and Levenberg-Marquardt(RLS-LM) algorithm is advanced to perform the online learning of the neural network, which further enhances both the accuracy of the NSSE model and the performance of the adaptive controller. The feedback correction is also utilized in the NSSE-AC system to eliminate the steady-state tracking error. Simulation results show that, compared with the NARMA-L2 model, the NSSE model of the turboshaft engine is more accurate. The maximum modeling error is decreased from 5.92% to 0.97%when the LM algorithm is introduced to optimize the neural network parameters. The NSSE-AC method can not only achieve a better main control loop performance than the traditional controller but also limit all the constraint parameters efficiently with quick and accurate switching responses even if component degradation exists. Thus, the effectiveness of the NSSE-AC method is validated.
基金Natural Science Foundation of Guangdong Province,Grant/Award Number:2021A1515011847Special Project in Key Fields of Universities in Department of Education of Guangdong Province,Grant/Award Number:2019KZDZX1036+3 种基金Demonstration Bases for Joint Training of Postgraduates of Department of Education of Guangdong Province,Grant/Award Number:202205Key Lab of Digital Signal and Image Processing of Guangdong Province,Grant/Award Number:2019GDDSIPL-01Innovation and Entrepreneurship Training Program for College Students of Guangdong Ocean University,Grant/Award Number:202210566028Postgraduate Education Innovation Plan Project of Guangdong Ocean University,Grant/Award Numbers:202214,202250,202251,202160。
文摘The solving of dynamic matrix square root(DMSR)problems is frequently encountered in many scientific and engineering fields.Although the original zeroing neural network is powerful for solving the DMSR,it cannot vanish the influence of the noise perturbations,and its constant-coefficient design scheme cannot accelerate the convergence speed.Therefore,a noise-tolerate and adaptive coefficient zeroing neural network(NTACZNN)is raised to enhance the robust noise immunity performance and accelerate the conver-gence speed simultaneously.Then,the global convergence and robustness of the pro-posed NTACZNN are theoretically analysed under an ideal environment and noise-perturbed circumstances.Furthermore,some illustrative simulation examples are designed and performed in order to substantiate the efficacy and advantage of the NTACZNN for the DMSR problem solution.Compared with some existing ZNNs,the proposed NTACZNN possesses advanced performance in terms of noise tolerance,solution accuracy,and convergence rate.
基金National Natural Science Foundation of China (60675054)National High Technology Research and Development Program of China (2006AA04Z228)"111" Project (B07018)
文摘This article provides a flexible-joint-manipulator,which incorporates with three means to make its mechanical arm come into compliant contact with the objects with a force kept within an acceptable range. At first,the Cartesian impedance control law is introduced on the basis of virtual decomposition to realize the compliance control. Then,adaptive dynamic joint compensators on all joints are used to achieve more precise control. Finally,a Cartesian force-feedback path generation is developed for collision ...
基金Supported by the National Nature Science Foundation of China (90716028)~~
文摘A novel nonlinear adaptive control method is presented for a near-space hypersonic vehicle （NHV） in the presence of strong uncertainties and disturbances. The control law consists of the optimal generalized predictive controller （OGPC） and the functional link network （FLN） direct adaptive law. OGPC is a continuous-time nonlinear predictive control law. The FLN adaptive law is used to offset the unknown uncertainties and disturbances in a flight through the online learning. The learning process does not need any offline training phase. The stability analyses of the NHV close-loop system are provided and it is proved that the system error and the weight learning error are uniformly ultimately hounded. Simulation results show the satisfactory performance of the con- troller for the attitude tracking.
基金The research herein reported did gratefully receive funding from Seventh Framework Programme of the European Union(FP7/2007-2013)under Grant Agreement N.284562,SARISTUThe project was prodigiously and effectively coordinated by Piet Christof Woelcken(Airbus)with the support of Michael Papadopoulos(EASN–European Aeronautic Science Network).
文摘SARISTU was a big cooperation project granted by the European Commission,7th Framework Programme,carried out between 2011 and 2015.It dealt with smart aeronautic structures,both morphing and sensored;its main target was to demonstrate the feasibility of designing,manufacturing and operating in representative environment,instrumented structures.Till now,it represents the major effort carried out within the European Union on the development of adaptive architectures for air systems.Inside that big activity,the realization of an Adaptive Trailing Edge Device(ATED)for wing camber adaptations aimed at compensating the weight reduction following the fuel consumption during cruise was addressed.It made the core of investigations target variable geometry aircraft components together with two other analyses concerning the development of shape-changing winglet and droop nose.ATED activities were conducted by the Italian Aerospace Research Centre(CIRA)in tight cooperation with the University of Napoli,"Federico II",who coordinated a group of 12 different partners from 8 different nations(France,Germany,Greece,the Netherlands,Israel,Spain,Turkey,and Italy).In this paper,an integral synthesis of that work is reported,with a focus on the definition and realization of the components of the presented device.The publication is in fact meant as the first part of a series that is aimed at overviewing the whole adaptive trailing edge development,till wind tunnel tests execution.Such a concise report is a critical and harmonized review of what have been performed by many colleagues spread all over Europe,all of which are duly recalled in the reported bibliography where the reader may access more detailed information and descriptions.In detail,the paper starts with a general introduction of the concept and its aims,to move to the specs definition immediately after.Then,it deals with a short but comprehensive description of the main ATED components:structural skeleton,skin,actuation and sensing systems.It is worth remarking that the paragraph dedicated to the body frame includes some discussion about aeroelastic assessment and manufacture,seen as complementation for a complete assessment of the design constraints.
文摘Semi-active dampers are used in base-isolation to reduce the seismic response of civil engineering structures. In the present study, a new semi-active damping system using variable amplification will be investigated for adaptive baseisolation. It uses a novel variable amplification device （VAD） connected in series with a passive damper. The VAD is capable of producing multiple amplification factors, each corresponding to a different amplification state. Forces from the damper are amplified to the structure according to the current amplification state, which is selected via a semi-active control algorithm specifically tailored to the system＇s tmique damping characteristics. To demonstrate the effectiveness of the VAD-damper system for adaptive base-isolation, numerical simulations are conducted for three and seven-story base-isolated buildings subject to both far and near-field ground motions. The results indicate that the system can achieve significant reductions in response compared to the base-isolated buildings with no damper. The proposed system is also found to perform well compared to a typical semi-active damper.
