Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a netwo...Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a network, the delay is with epistemic uncertainty, which makes the traditional routing scheme based on deterministic theory or probability theory not applicable. Motivated by this problem, the MCN with epistemic uncertainty is first summarized as a dynamic uncertain network based on uncertainty theory, which is widely applied to model epistemic uncertainties. Then by modeling the uncertain end-toend delay, a new delay bounded routing scheme is proposed to find the path with the maximum belief degree that satisfies the delay threshold for the dynamic uncertain network. Finally, a lowEarth-orbit satellite communication network(LEO-SCN) is used as a case to verify the effectiveness of our routing scheme. It is first modeled as a dynamic uncertain network, and then the delay bounded paths with the maximum belief degree are computed and compared under different delay thresholds.展开更多
This paper addresses the state estimation for a class of nonlinear time-varying stochastic systems with both uncertain dynam-ics and unknown measurement bias.A novel extended state based Kalman filter(ESKF)algorithm i...This paper addresses the state estimation for a class of nonlinear time-varying stochastic systems with both uncertain dynam-ics and unknown measurement bias.A novel extended state based Kalman filter(ESKF)algorithm is developed to estimate the original state,the uncertain dynamics and the measurement bias.It is shown that the estimation error of the proposed algorithm is bounded in the mean square sense.Also,the estimation of the measurement bias asymptotically converges to its true value,such that the infuence of measurement bias is eliminated.Furthermore,the asymptotic optimality of the estima-tion result is proved while the uncertain dynamics approaches to a constant vector.Finally,a simulation study for harmonic oscillator system model is provided to ilustrate the effectiveness of proposed method.展开更多
Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is faidy difficult to distinguish the cause o...Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is faidy difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A ＂chaining＂ inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic rea- soning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure.展开更多
This paper studies the global exponential synchronization of uncertain complex delayed dynamical networks. The network model considered is general dynamical delay networks with unknown network structure and unknown co...This paper studies the global exponential synchronization of uncertain complex delayed dynamical networks. The network model considered is general dynamical delay networks with unknown network structure and unknown coupling functions but bounded. Novel delay-dependent linear controllers are designed via the Lyapunov stability theory. Especially, it is shown that the controlled networks are globally exponentially synchronized with a given convergence rate. An example of typical dynamical network of this class, having the Lorenz system at each node, has been used to demonstrate and verify the novel design proposed. And, the numerical simulation results show the effectiveness of proposed synchronization approaches.展开更多
In order to overcome the drawbacks of conventional artificial potential fields (APF) based methods for the motion planning problems of mobile robots in dynamic uncertain environments, an artificial coordinating fields...In order to overcome the drawbacks of conventional artificial potential fields (APF) based methods for the motion planning problems of mobile robots in dynamic uncertain environments, an artificial coordinating fields (ACF) based method has been proposed recently. This paper deals with the reachability problem of the ACF, that is, how to design and choose the parameters of the ACF and how the environment should be such that the robot can reach its goal without being trapped in local minima. Some sufficient conditions for these purposes are developed theoretically. Theoretical analyses show that, the ACF can effectively remove local minima in dynamic uncertain environments with V-shape or U-shape obstacles, and guide the mobile robot to reach its goal with some necessary environment constraints and based on the methods provided in this paper to properly choose the parameters of the ACF. Comparisons between the ACF and APF, and simulations are provided to illustrate the advantages of the ACF.展开更多
In this paper, a robust controller for electrically driven robotic systems is developed. The controller is designed in a backstepping manner. The main features of the controller are: 1) Control strategy is developed a...In this paper, a robust controller for electrically driven robotic systems is developed. The controller is designed in a backstepping manner. The main features of the controller are: 1) Control strategy is developed at the voltage level and can deal with both mechanical and electrical uncertainties. 2) The proposed control law removes the restriction of previous robust methods on the upper bound of system uncertainties. 3) It also benefits from global asymptotic stability in the Lyapunov sense. It is worth to mention that the proposed controller can be utilized for constrained and nonconstrained robotic systems. The effectiveness of the proposed controller is verified by simulations for a two link robot manipulator and a four-bar linkage. In addition to simulation results,experimental results on a two link serial manipulator are included to demonstrate the performance of the proposed controller in tracking a given trajectory.展开更多
In this paper, PID（proportional-integral-derivative） controllers will be designed to solve the tracking problem for a class of coupled multi-agent systems, where each agent is described by a second-order high-dimens...In this paper, PID（proportional-integral-derivative） controllers will be designed to solve the tracking problem for a class of coupled multi-agent systems, where each agent is described by a second-order high-dimensional nonlinear uncertain dynamical system, which only has access to its own tracking error information and does not need to communicate with others. This paper will show that a 3-dimensional manifold can be constructed based on the information about the Lipschitz constants of the system nonlinear dynamics, such that whenever the three parameters of each PID controller are chosen from the manifold, the whole multi-agent system can be stabilized globally and the tracking error of each agent approaches to zero asymptotically. For a class of coupled first-order multi-agent nonlinear uncertain systems, a PI controller will be designed to stabilize the whole system.展开更多
Disorders of sex development(DSD)are a group of rare complex clinical syndromes with multiple etiologies.Distinguishing the various causes of DSD is quite difficult in clinical practice,even for senior general physici...Disorders of sex development(DSD)are a group of rare complex clinical syndromes with multiple etiologies.Distinguishing the various causes of DSD is quite difficult in clinical practice,even for senior general physicians because of the similar and atypical clinical manifestations of these conditions.In addition,DSD are difficult to diagnose because most primary doctors receive insufficient training for DSD.Delayed diagnoses and misdiagnoses are common for patients with DSD and lead to poor treatment and prognoses.On the basis of the principles and algorithms of dynamic uncertain causality graph(DUCG),a diagnosis model for DSD was jointly constructed by experts on DSD and engineers of artificial intelligence.“Chaining”inference algorithm and weighted logic operation mechanism were applied to guarantee the accuracy and efficiency of diagnostic reasoning under incomplete situations and uncertain information.Verification was performed using 153 selected clinical cases involving nine common DSD-related diseases and three causes other than DSD as the differential diagnosis.The model had an accuracy of 94.1%,which was significantly higher than that of interns and third-year residents.In conclusion,the DUCG model has broad application prospects as a computer-aided diagnostic tool for DSDrelated diseases.展开更多
Platoon control is widely studied for coordinating connected and automated vehicles(CAVs)on highways due to its potential for improving traffic throughput and road safety.Inspired by platoon control,the cooperation of...Platoon control is widely studied for coordinating connected and automated vehicles(CAVs)on highways due to its potential for improving traffic throughput and road safety.Inspired by platoon control,the cooperation of multiple CAVs in conflicting scenarios can be greatly simplified by virtual platooning.Vehicle-to-vehicle communication is an essential ingredient in virtual platoon systems.Massive data transmission with limited communication resources incurs inevitable imperfections such as transmission delay and dropped packets.As a result,unnecessary transmission needs to be avoided to establish a reliable wireless network.To this end,an event-triggered robust control method is developed to reduce the use of communication resources while ensuring the stability of the virtual platoon system with time-varying uncertainty.The uniform boundedness,uniform ultimate boundedness,and string stability of the closed-loop system are analytically proved.As for the triggering condition,the uncertainty of the boundary information is considered,so that the threshold can be estimated more reasonably.Simulation and experimental results verify that the proposed method can greatly reduce data transmission while creating multi-vehicle cooperation.The threshold affects the tracking ability and communication burden,and hence an optimization framework for choosing the threshold is worth exploring in future research.展开更多
基金National Natural Science Foundation of China (61773044,62073009)National key Laboratory of Science and Technology on Reliability and Environmental Engineering(WDZC2019601A301)。
文摘Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a network, the delay is with epistemic uncertainty, which makes the traditional routing scheme based on deterministic theory or probability theory not applicable. Motivated by this problem, the MCN with epistemic uncertainty is first summarized as a dynamic uncertain network based on uncertainty theory, which is widely applied to model epistemic uncertainties. Then by modeling the uncertain end-toend delay, a new delay bounded routing scheme is proposed to find the path with the maximum belief degree that satisfies the delay threshold for the dynamic uncertain network. Finally, a lowEarth-orbit satellite communication network(LEO-SCN) is used as a case to verify the effectiveness of our routing scheme. It is first modeled as a dynamic uncertain network, and then the delay bounded paths with the maximum belief degree are computed and compared under different delay thresholds.
基金This work was partly supported by National Key R&D Program of China(No.2018YFA0703800)the National Nature Science Foundation of China(Nos.I 1931018,61633003-3)the Beijing Advanced Innovation Center for Intelligent Robots and Systems(No.2019IRS09).
文摘This paper addresses the state estimation for a class of nonlinear time-varying stochastic systems with both uncertain dynam-ics and unknown measurement bias.A novel extended state based Kalman filter(ESKF)algorithm is developed to estimate the original state,the uncertain dynamics and the measurement bias.It is shown that the estimation error of the proposed algorithm is bounded in the mean square sense.Also,the estimation of the measurement bias asymptotically converges to its true value,such that the infuence of measurement bias is eliminated.Furthermore,the asymptotic optimality of the estima-tion result is proved while the uncertain dynamics approaches to a constant vector.Finally,a simulation study for harmonic oscillator system model is provided to ilustrate the effectiveness of proposed method.
基金supported by the Medical and Health Research Program of Zhejiang Province(No.2015KYB128)the Zhejiang Provincial Natural Science Foundation(No.LQ15H030004),China
文摘Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is faidy difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A ＂chaining＂ inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic rea- soning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure.
文摘This paper studies the global exponential synchronization of uncertain complex delayed dynamical networks. The network model considered is general dynamical delay networks with unknown network structure and unknown coupling functions but bounded. Novel delay-dependent linear controllers are designed via the Lyapunov stability theory. Especially, it is shown that the controlled networks are globally exponentially synchronized with a given convergence rate. An example of typical dynamical network of this class, having the Lorenz system at each node, has been used to demonstrate and verify the novel design proposed. And, the numerical simulation results show the effectiveness of proposed synchronization approaches.
基金This paper was partly supported by the National Natural Science Foundation (No.60131160741,60334010) of China.
文摘In order to overcome the drawbacks of conventional artificial potential fields (APF) based methods for the motion planning problems of mobile robots in dynamic uncertain environments, an artificial coordinating fields (ACF) based method has been proposed recently. This paper deals with the reachability problem of the ACF, that is, how to design and choose the parameters of the ACF and how the environment should be such that the robot can reach its goal without being trapped in local minima. Some sufficient conditions for these purposes are developed theoretically. Theoretical analyses show that, the ACF can effectively remove local minima in dynamic uncertain environments with V-shape or U-shape obstacles, and guide the mobile robot to reach its goal with some necessary environment constraints and based on the methods provided in this paper to properly choose the parameters of the ACF. Comparisons between the ACF and APF, and simulations are provided to illustrate the advantages of the ACF.
文摘In this paper, a robust controller for electrically driven robotic systems is developed. The controller is designed in a backstepping manner. The main features of the controller are: 1) Control strategy is developed at the voltage level and can deal with both mechanical and electrical uncertainties. 2) The proposed control law removes the restriction of previous robust methods on the upper bound of system uncertainties. 3) It also benefits from global asymptotic stability in the Lyapunov sense. It is worth to mention that the proposed controller can be utilized for constrained and nonconstrained robotic systems. The effectiveness of the proposed controller is verified by simulations for a two link robot manipulator and a four-bar linkage. In addition to simulation results,experimental results on a two link serial manipulator are included to demonstrate the performance of the proposed controller in tracking a given trajectory.
基金supported by the National Natural Science Foundation of China under Grant No.11688101
文摘In this paper, PID（proportional-integral-derivative） controllers will be designed to solve the tracking problem for a class of coupled multi-agent systems, where each agent is described by a second-order high-dimensional nonlinear uncertain dynamical system, which only has access to its own tracking error information and does not need to communicate with others. This paper will show that a 3-dimensional manifold can be constructed based on the information about the Lipschitz constants of the system nonlinear dynamics, such that whenever the three parameters of each PID controller are chosen from the manifold, the whole multi-agent system can be stabilized globally and the tracking error of each agent approaches to zero asymptotically. For a class of coupled first-order multi-agent nonlinear uncertain systems, a PI controller will be designed to stabilize the whole system.
基金This research was supported by the National Key Research and Development Program of China(No.2016YFC0901501)CAMS Innovation Fund for Medical Science(No.CAMS-2017-I2M–1-011)the Research Project of the Institute of Internet Industry,Tsinghua University,titled“DUCG theory and application of medical aided diagnosis-algorithm of introducing classification variables in DUCG.”。
文摘Disorders of sex development(DSD)are a group of rare complex clinical syndromes with multiple etiologies.Distinguishing the various causes of DSD is quite difficult in clinical practice,even for senior general physicians because of the similar and atypical clinical manifestations of these conditions.In addition,DSD are difficult to diagnose because most primary doctors receive insufficient training for DSD.Delayed diagnoses and misdiagnoses are common for patients with DSD and lead to poor treatment and prognoses.On the basis of the principles and algorithms of dynamic uncertain causality graph(DUCG),a diagnosis model for DSD was jointly constructed by experts on DSD and engineers of artificial intelligence.“Chaining”inference algorithm and weighted logic operation mechanism were applied to guarantee the accuracy and efficiency of diagnostic reasoning under incomplete situations and uncertain information.Verification was performed using 153 selected clinical cases involving nine common DSD-related diseases and three causes other than DSD as the differential diagnosis.The model had an accuracy of 94.1%,which was significantly higher than that of interns and third-year residents.In conclusion,the DUCG model has broad application prospects as a computer-aided diagnostic tool for DSDrelated diseases.
基金supported by the National Natural Science Foundation of China(Nos.61872217,U20A20285,U1701262,and U1801263)。
文摘Platoon control is widely studied for coordinating connected and automated vehicles(CAVs)on highways due to its potential for improving traffic throughput and road safety.Inspired by platoon control,the cooperation of multiple CAVs in conflicting scenarios can be greatly simplified by virtual platooning.Vehicle-to-vehicle communication is an essential ingredient in virtual platoon systems.Massive data transmission with limited communication resources incurs inevitable imperfections such as transmission delay and dropped packets.As a result,unnecessary transmission needs to be avoided to establish a reliable wireless network.To this end,an event-triggered robust control method is developed to reduce the use of communication resources while ensuring the stability of the virtual platoon system with time-varying uncertainty.The uniform boundedness,uniform ultimate boundedness,and string stability of the closed-loop system are analytically proved.As for the triggering condition,the uncertainty of the boundary information is considered,so that the threshold can be estimated more reasonably.Simulation and experimental results verify that the proposed method can greatly reduce data transmission while creating multi-vehicle cooperation.The threshold affects the tracking ability and communication burden,and hence an optimization framework for choosing the threshold is worth exploring in future research.
