This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a larg...This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and satellites.All these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become unavailable.Motivated by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical dynamics.The approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control approach.Different from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control signal.The developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output tracking.Eventually,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.展开更多
在基于接收信号强度(received signal strength,RSS)的定位中,传感器量测的系统偏差及锚节点位置的不确定性会对定位结果造成严重影响。对此,提出一种面向不确定量测的鲁棒定位方法。首先,针对传感器量测有偏差及锚节点位置不确定的定...在基于接收信号强度(received signal strength,RSS)的定位中,传感器量测的系统偏差及锚节点位置的不确定性会对定位结果造成严重影响。对此,提出一种面向不确定量测的鲁棒定位方法。首先,针对传感器量测有偏差及锚节点位置不确定的定位问题,建立相应的量测模型;其次,基于经典的极大似然估计准则建立关于目标位置的估计问题;最后,对所建立的非凸位置估计问题,采用合理的近似、松弛数学手段,将其转化为凸的半正定规划问题,从而保证得到全局最优解。仿真实验表明,在不同定位场景和条件下,所提方法的定位精度相比文献中的几种定位方法均有明显的优势,最高可提升约50%,证明其能有效降低量测不确定性对定位结果的不利影响,具有良好的鲁棒性。展开更多
The synchronization of Chua＇s system, whose inputs include an unknown constant parameter, is studied in this paper. A constructive method is applied to designing an adaptive controller, in which only one variable inf...The synchronization of Chua＇s system, whose inputs include an unknown constant parameter, is studied in this paper. A constructive method is applied to designing an adaptive controller, in which only one variable information of the master system is needed. With the action of control signals, the parameter of the slave system will approach the corresponding unknown parameter in the master system. At the same time, the synchronization errors will also converge to zero asymptotically. Numerical simulations show that the proposed theoretical approach is very effective.展开更多
This paper addresses the adaptive synchronization for uncertain Liu system via a nonlinear input. By using a single nonlinear controller, the approach is utilized to implement the synchronization of Liu system with to...This paper addresses the adaptive synchronization for uncertain Liu system via a nonlinear input. By using a single nonlinear controller, the approach is utilized to implement the synchronization of Liu system with total parameters unknown. This method is simple and can be easily designed. What is more, it improves the existing conclusions in Ref [12]. Simulation results prove that the controller is effective and feasible in the end.展开更多
Since the joint actuator of the space robot executes the control instructions frequently in the harsh space environment,it is prone to the partial loss of control effectiveness(PLCE)fault.An adaptive fault-tolerant co...Since the joint actuator of the space robot executes the control instructions frequently in the harsh space environment,it is prone to the partial loss of control effectiveness(PLCE)fault.An adaptive fault-tolerant control algorithm is designed for a space robot system with the uncertain parameters and the PLCE actuator faults.The mathematical model of the system is established based on the Lagrange method,and the PLCE actuator fault is described as an effectiveness factor.The lower bound of the effectiveness factors and the upper bound of the uncertain parameters are estimated by an adaptive strategy,and the estimated value is fed back to the control algorithm.Compared with the traditional fault-tolerant algorithms,the proposed algorithm does not need to predetermine the lower bound of the effectiveness factor,hence it is more in line with the actual engineering application.It is proved that the algorithm can guarantee the stability of the closed-loop system based on the Lyapunov function method.The numerical simulation results show that the proposed algorithm can not only compensate for the uncertain parameters,but also can tolerate the PLCE actuator faults effectively,which verifies the effectiveness and superiority of the control scheme.展开更多
By using the quasi-Lyapunov function, some sufficient conditions of global exponential stability for impulsive systems are established, which is the basis for the following discussion. Then, by employing Riccati inequ...By using the quasi-Lyapunov function, some sufficient conditions of global exponential stability for impulsive systems are established, which is the basis for the following discussion. Then, by employing Riccati inequality and Hamilton-Jacobi inequality approach, some sufficient conditions of robust exponential stability for uncertain linear/nonlinear impulsive systems are derived, respectively. Finally, some examples are given to illustrate the applications of the theory.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
In this paper a parameter observer and a synchronization controller are designed to synchronize unknown chaotic systems with diverse structures. Based on stability theory the structures of the observer and the control...In this paper a parameter observer and a synchronization controller are designed to synchronize unknown chaotic systems with diverse structures. Based on stability theory the structures of the observer and the controller are presented. The unknown Coullet system and Rossler system are taken for examples to demonstrate that the method is effective and feasible. The artificial simulation results show that global synchronization between the unknown Coullet system and the Rossler system can be achieved by a single driving variable with co-operation of the observer and the controller, and all parameters of the Coullet system can be identified at the same time.展开更多
Cluster synchronization of nonlinear uncertain complex networks with desynchronizing impulse is explored. First of all, a feedback controller is employed, based on the Lyapunov stability theorem and Lipschitz conditio...Cluster synchronization of nonlinear uncertain complex networks with desynchronizing impulse is explored. First of all, a feedback controller is employed, based on the Lyapunov stability theorem and Lipschitz condition, to guarantee that the uncertain complex networks with desynchronizing impulse synchronize with an object trajectory. Furthermore, a synchronizing impulse controller is presented, which is more efficiently and directly used to achieve the cluster synchronization. Finally, numerical examples are examined to show the effectiveness of the proposed methods.展开更多
The lasting evolution of computing environment, software engineering and interaction methods leads to cloud computing. Cloud computing changes the configuration mode of resources on the Internet and all kinds of resou...The lasting evolution of computing environment, software engineering and interaction methods leads to cloud computing. Cloud computing changes the configuration mode of resources on the Internet and all kinds of resources are virtualized and provided as services. Mass participation and online interaction with social annotations become usual in human daily life. People who own similar interests on the Internet may cluster naturally into scalable and boundless communities and collective intelligence will emerge. Human is taken as an intelligent computing factor, and uncertainty becomes a basic property in cloud computing. Virtualization, soft computing and granular computing will become essential features of cloud computing. Compared with the engineering technological problems of IaaS (Infrastructure as a service), PaaS (Platform as a Service) and SaaS (Software as a Service), collective intelligence and uncertain knowledge representation will be more important frontiers in cloud computing for researchers within the community of intelligence science.展开更多
A robust adaptive control strategy was developed to force an underactuated surface vessel to follow a reference path,despite the presence of uncertain parameters and unstructured uncertainties including exogenous dist...A robust adaptive control strategy was developed to force an underactuated surface vessel to follow a reference path,despite the presence of uncertain parameters and unstructured uncertainties including exogenous disturbances and measurement noise.The reference path can be a curve or a straight line.The proposed controller was designed by using Lyapunov’s direct method and sliding mode control and backstepping techniques.Because the sway axis of the vessel was not directly actuated,two sliding surfaces were introduced,the first one in terms of the surge motion tracking errors and the second one for the yaw motion tracking errors.The adaptive control law guaranteed the uniform ultimate boundedness of the tracking errors.Numerical simulation results were provided to validate the effectiveness of the proposed controller for path following of underactuated surface vessels.展开更多
Purpose:Given the information overload of scientific literature,there is an increasing need for computable biomedical knowledge buried in free text.This study aimed to develop a novel approach to extracting and measur...Purpose:Given the information overload of scientific literature,there is an increasing need for computable biomedical knowledge buried in free text.This study aimed to develop a novel approach to extracting and measuring uncertain biomedical knowledge from scientific statements.Design/methodology/approach:Taking cardiovascular research publications in China as a sample,we extracted subject-predicate-object triples(SPO triples)as knowledge units and unknown/hedging/conflicting uncertainties as the knowledge context.We introduced information entropy(IE)as potential metric to quantify the uncertainty of epistemic status of scientific knowledge represented at subject-object pairs(SO pairs)levels.Findings:The results indicated an extraordinary growth of cardiovascular publications in China while only a modest growth of the novel SPO triples.After evaluating the uncertainty of biomedical knowledge with IE,we identified the Top 10 SO pairs with highest IE,which implied the epistemic status pluralism.Visual presentation of the SO pairs overlaid with uncertainty provided a comprehensive overview of clusters of biomedical knowledge and contending topics in cardiovascular research.Research limitations:The current methods didn’t distinguish the specificity and probabilities of uncertainty cue words.The number of sentences surrounding a given triple may also influence the value of IE.Practical implications:Our approach identified major uncertain knowledge areas such as diagnostic biomarkers,genetic polymorphism and co-existing risk factors related to cardiovascular diseases in China.These areas are suggested to be prioritized;new hypotheses need to be verified,while disputes,conflicts,and contradictions need to be settled.Originality/value:We provided a novel approach by combining natural language processing and computational linguistics with informetric methods to extract and measure uncertain knowledge from scientific statements.展开更多
With the increasing popularity of wireless sensor network and GPS （ global positioning system）, uncertain data as a new type of data brings a new challenge for the traditional data processing methods. Data broadcast...With the increasing popularity of wireless sensor network and GPS （ global positioning system）, uncertain data as a new type of data brings a new challenge for the traditional data processing methods. Data broadcast is an effective means for data dissemination in mobile networks. In this paper, the def＇mition of the mean uncertainty ratio of data is presented and a broadcasting scheme is proposed for uncertain data dissemination. Simulation results show that the scheme can reduce the uncertainty of the broadcasted uncertain data effectively at the cost of a minor increase in data access time, in the case of no transmission error and presence of transmission errors. As a result, lower uncertainty of data benefits the qualifies of the query results based on the data.展开更多
Through taking uncertain mechanical parameters of composites into consideration,this paper carries out uncertain modal analysis for an unmanned aircraft landing gear.By describing correlated multi-dimensional mechanic...Through taking uncertain mechanical parameters of composites into consideration,this paper carries out uncertain modal analysis for an unmanned aircraft landing gear.By describing correlated multi-dimensional mechanical parameters as a convex polyhedral model,the modal analysis problem of a composite landing gear is transferred into a linear fractional programming(LFR)eigenvalue solution problem.As a consequent,the extreme-point algorithm is proposed to estimate lower and upper bounds of eigenvalues,namely the exact results of eigenvalues can be easily obtained at the extreme-point locations of the convex polyhedral model.The simulation results show that the proposed model and algorithm can play an important role in the eigenvalue solution problem and possess valuable engineering significance.It will be a powerful and effective tool for further vibration analysis for the landing gear.展开更多
基金supported in part by the National Key R&D Program of China under Grant 2021YFB2011300the National Natural Science Foundation of China under Grant 52075262。
文摘This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and satellites.All these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become unavailable.Motivated by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical dynamics.The approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control approach.Different from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control signal.The developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output tracking.Eventually,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.
文摘在基于接收信号强度(received signal strength,RSS)的定位中,传感器量测的系统偏差及锚节点位置的不确定性会对定位结果造成严重影响。对此,提出一种面向不确定量测的鲁棒定位方法。首先,针对传感器量测有偏差及锚节点位置不确定的定位问题,建立相应的量测模型;其次,基于经典的极大似然估计准则建立关于目标位置的估计问题;最后,对所建立的非凸位置估计问题,采用合理的近似、松弛数学手段,将其转化为凸的半正定规划问题,从而保证得到全局最优解。仿真实验表明,在不同定位场景和条件下,所提方法的定位精度相比文献中的几种定位方法均有明显的优势,最高可提升约50%,证明其能有效降低量测不确定性对定位结果的不利影响,具有良好的鲁棒性。
基金Project supported by the National Natural Science Foundation of China （Grant No 60502009）.
文摘The synchronization of Chua＇s system, whose inputs include an unknown constant parameter, is studied in this paper. A constructive method is applied to designing an adaptive controller, in which only one variable information of the master system is needed. With the action of control signals, the parameter of the slave system will approach the corresponding unknown parameter in the master system. At the same time, the synchronization errors will also converge to zero asymptotically. Numerical simulations show that the proposed theoretical approach is very effective.
基金Project supported by the Educational Commission of Hubei Province of China,(Grant No 080056)
文摘This paper addresses the adaptive synchronization for uncertain Liu system via a nonlinear input. By using a single nonlinear controller, the approach is utilized to implement the synchronization of Liu system with total parameters unknown. This method is simple and can be easily designed. What is more, it improves the existing conclusions in Ref [12]. Simulation results prove that the controller is effective and feasible in the end.
基金supported by the National Natural Science Foundation of China(11372073,11072061)
文摘Since the joint actuator of the space robot executes the control instructions frequently in the harsh space environment,it is prone to the partial loss of control effectiveness(PLCE)fault.An adaptive fault-tolerant control algorithm is designed for a space robot system with the uncertain parameters and the PLCE actuator faults.The mathematical model of the system is established based on the Lagrange method,and the PLCE actuator fault is described as an effectiveness factor.The lower bound of the effectiveness factors and the upper bound of the uncertain parameters are estimated by an adaptive strategy,and the estimated value is fed back to the control algorithm.Compared with the traditional fault-tolerant algorithms,the proposed algorithm does not need to predetermine the lower bound of the effectiveness factor,hence it is more in line with the actual engineering application.It is proved that the algorithm can guarantee the stability of the closed-loop system based on the Lyapunov function method.The numerical simulation results show that the proposed algorithm can not only compensate for the uncertain parameters,but also can tolerate the PLCE actuator faults effectively,which verifies the effectiveness and superiority of the control scheme.
文摘By using the quasi-Lyapunov function, some sufficient conditions of global exponential stability for impulsive systems are established, which is the basis for the following discussion. Then, by employing Riccati inequality and Hamilton-Jacobi inequality approach, some sufficient conditions of robust exponential stability for uncertain linear/nonlinear impulsive systems are derived, respectively. Finally, some examples are given to illustrate the applications of the theory.
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Project supported by the National Natural Science Foundation of China (Grant No 60574011)
文摘In this paper a parameter observer and a synchronization controller are designed to synchronize unknown chaotic systems with diverse structures. Based on stability theory the structures of the observer and the controller are presented. The unknown Coullet system and Rossler system are taken for examples to demonstrate that the method is effective and feasible. The artificial simulation results show that global synchronization between the unknown Coullet system and the Rossler system can be achieved by a single driving variable with co-operation of the observer and the controller, and all parameters of the Coullet system can be identified at the same time.
基金Project supported by the National Natural Science foundation of China(Grant Nos.51276081 and 11326193)the Students’ Research Foundation of Jiangsu University,China(Grant Nos.Y13A127 and 12A415)
文摘Cluster synchronization of nonlinear uncertain complex networks with desynchronizing impulse is explored. First of all, a feedback controller is employed, based on the Lyapunov stability theorem and Lipschitz condition, to guarantee that the uncertain complex networks with desynchronizing impulse synchronize with an object trajectory. Furthermore, a synchronizing impulse controller is presented, which is more efficiently and directly used to achieve the cluster synchronization. Finally, numerical examples are examined to show the effectiveness of the proposed methods.
基金supported by National Key Basic Research Program of China (973 Program) under Grant No.2007CB310804China Post-doctoral Science Foundation under Grants No.20090460107, 201003794
文摘The lasting evolution of computing environment, software engineering and interaction methods leads to cloud computing. Cloud computing changes the configuration mode of resources on the Internet and all kinds of resources are virtualized and provided as services. Mass participation and online interaction with social annotations become usual in human daily life. People who own similar interests on the Internet may cluster naturally into scalable and boundless communities and collective intelligence will emerge. Human is taken as an intelligent computing factor, and uncertainty becomes a basic property in cloud computing. Virtualization, soft computing and granular computing will become essential features of cloud computing. Compared with the engineering technological problems of IaaS (Infrastructure as a service), PaaS (Platform as a Service) and SaaS (Software as a Service), collective intelligence and uncertain knowledge representation will be more important frontiers in cloud computing for researchers within the community of intelligence science.
基金Supported by the National Natural Science Foundation of China （Grant No. 61074053）the Applied Basic Research Program of Ministry of Transport of China （Grant No. 2011-329-225-390）
文摘A robust adaptive control strategy was developed to force an underactuated surface vessel to follow a reference path,despite the presence of uncertain parameters and unstructured uncertainties including exogenous disturbances and measurement noise.The reference path can be a curve or a straight line.The proposed controller was designed by using Lyapunov’s direct method and sliding mode control and backstepping techniques.Because the sway axis of the vessel was not directly actuated,two sliding surfaces were introduced,the first one in terms of the surge motion tracking errors and the second one for the yaw motion tracking errors.The adaptive control law guaranteed the uniform ultimate boundedness of the tracking errors.Numerical simulation results were provided to validate the effectiveness of the proposed controller for path following of underactuated surface vessels.
基金funded by the National Natural Science Foundation of China(nos.71603280,72074006,and 82070235)the Beijing Municipal Natural Science Foundation(7191013)+1 种基金Research Unit of Medical Science Research Management/Basic and Clinical Research of Metabolic Cardiovascular Diseases,Chinese Academy of Medical Sciences(2021RU003)Peking University Health Science Center and the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(2017QNRC001).
文摘Purpose:Given the information overload of scientific literature,there is an increasing need for computable biomedical knowledge buried in free text.This study aimed to develop a novel approach to extracting and measuring uncertain biomedical knowledge from scientific statements.Design/methodology/approach:Taking cardiovascular research publications in China as a sample,we extracted subject-predicate-object triples(SPO triples)as knowledge units and unknown/hedging/conflicting uncertainties as the knowledge context.We introduced information entropy(IE)as potential metric to quantify the uncertainty of epistemic status of scientific knowledge represented at subject-object pairs(SO pairs)levels.Findings:The results indicated an extraordinary growth of cardiovascular publications in China while only a modest growth of the novel SPO triples.After evaluating the uncertainty of biomedical knowledge with IE,we identified the Top 10 SO pairs with highest IE,which implied the epistemic status pluralism.Visual presentation of the SO pairs overlaid with uncertainty provided a comprehensive overview of clusters of biomedical knowledge and contending topics in cardiovascular research.Research limitations:The current methods didn’t distinguish the specificity and probabilities of uncertainty cue words.The number of sentences surrounding a given triple may also influence the value of IE.Practical implications:Our approach identified major uncertain knowledge areas such as diagnostic biomarkers,genetic polymorphism and co-existing risk factors related to cardiovascular diseases in China.These areas are suggested to be prioritized;new hypotheses need to be verified,while disputes,conflicts,and contradictions need to be settled.Originality/value:We provided a novel approach by combining natural language processing and computational linguistics with informetric methods to extract and measure uncertain knowledge from scientific statements.
基金Initial Research Foundation of Shanghai Second Polytechnic University ( No.001943)National High Technology Research and Development Program of China(863 Program) (No.2007AA01Z309)
文摘With the increasing popularity of wireless sensor network and GPS （ global positioning system）, uncertain data as a new type of data brings a new challenge for the traditional data processing methods. Data broadcast is an effective means for data dissemination in mobile networks. In this paper, the def＇mition of the mean uncertainty ratio of data is presented and a broadcasting scheme is proposed for uncertain data dissemination. Simulation results show that the scheme can reduce the uncertainty of the broadcasted uncertain data effectively at the cost of a minor increase in data access time, in the case of no transmission error and presence of transmission errors. As a result, lower uncertainty of data benefits the qualifies of the query results based on the data.
基金supported by the National Nature Science Foundation of China(No.51805503)the Beijing Natural Science Foundation(No.3202035)。
文摘Through taking uncertain mechanical parameters of composites into consideration,this paper carries out uncertain modal analysis for an unmanned aircraft landing gear.By describing correlated multi-dimensional mechanical parameters as a convex polyhedral model,the modal analysis problem of a composite landing gear is transferred into a linear fractional programming(LFR)eigenvalue solution problem.As a consequent,the extreme-point algorithm is proposed to estimate lower and upper bounds of eigenvalues,namely the exact results of eigenvalues can be easily obtained at the extreme-point locations of the convex polyhedral model.The simulation results show that the proposed model and algorithm can play an important role in the eigenvalue solution problem and possess valuable engineering significance.It will be a powerful and effective tool for further vibration analysis for the landing gear.
