Realizing optimal control performance for continuum robots(CRs) poses huge challenges on traditional modelbased optimal control approaches due to their high degrees of freedom,complex nonlinear dynamics and soft conti...Realizing optimal control performance for continuum robots(CRs) poses huge challenges on traditional modelbased optimal control approaches due to their high degrees of freedom,complex nonlinear dynamics and soft continuum morphologies which are difficult to explicitly model.This paper proposes a model-free adaptive optimal control algorithm(ADAPT)for CRs.In our strategy,we consider CRs as a class of nonlinear continuous-time dynamical systems in the state space,wherein the position of the end-effector is considered as the state and the input torque is mapped as the control input.Then,the optimized Hamilton-Jacobi-Bellman(HJB) equation is derived by optimal control principles,and subsequently solved by the proposed ADAPT algorithm without requiring knowledge of the original system dynamics.Under some mild assumptions,the global stability and convergence of the closed-loop control approach are guaranteed.Several simulation experiments are conducted on a magnetic CR(MCR) to demonstrate the practicality and effectiveness of the ADAPT algorithm.展开更多
For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies ...For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies bionic analytical framework based on the partial differential equation-ordinary differential equation(PDE-ODE)approach.Specifically,by designing a specialized network communication protocol and employing the spatial continuum method for densely distributed agents,this paper models the tracking errors of densely distributed agents as a PDE equivalent to a human disease transmission model,and that of sparsely distributed agents as several ODEs equivalent to the predator population models.The coupling relationship between the PDE and ODE models is established through boundary conditions of the PDE,thereby forming a PDE-ODE-based tracking error model for the considered MASs.Furthermore,by integrating adaptive neural control scheme with the aforementioned biological models,a“Flexible Neural Network”endowed with adaptive and self-stabilized capabilities is constructed,which acts upon the considered MASs,enabling their practical finite-time deployment.Finally,effectiveness of the developed approach is illustrated through a numerical example.展开更多
A goal-oriented adaptive finite element（FE） method for solving 3D direct current（DC） resistivity modeling problem is presented. The model domain is subdivided into unstructured tetrahedral elements that allow for ...A goal-oriented adaptive finite element（FE） method for solving 3D direct current（DC） resistivity modeling problem is presented. The model domain is subdivided into unstructured tetrahedral elements that allow for efficient local mesh refinement and flexible description of complex models. The elements that affect the solution at each receiver location are adaptively refined according to a goal-oriented posteriori error estimator using dual-error weighting approach. The FE method with adapting mesh can easily handle such structures at almost any level of complexity. The method is demonstrated on two synthetic resistivity models with analytical solutions and available results from integral equation method, so the errors can be quantified. The applicability of the numerical method is illustrated on a resistivity model with a topographic ridge. Numerical examples show that this method is flexible and accurate for geometrically complex situations.展开更多
Nowadays, high-precision motion controls are needed in modern manufacturing industry. A data-driven nonparametric model adaptive control(NMAC) method is proposed in this paper to control the position of a linear servo...Nowadays, high-precision motion controls are needed in modern manufacturing industry. A data-driven nonparametric model adaptive control(NMAC) method is proposed in this paper to control the position of a linear servo system. The controller design requires no information about the structure of linear servo system, and it is based on the estimation and forecasting of the pseudo-partial derivatives(PPD) which are estimated according to the voltage input and position output of the linear motor. The characteristics and operational mechanism of the permanent magnet synchronous linear motor(PMSLM) are introduced, and the proposed nonparametric model control strategy has been compared with the classic proportional-integral-derivative(PID) control algorithm. Several real-time experiments on the motion control system incorporating a permanent magnet synchronous linear motor showed that the nonparametric model adaptive control method improved the system s response to disturbances and its position-tracking precision, even for a nonlinear system with incompletely known dynamic characteristics.展开更多
Through the coherent accumulation of target echoes, inverse synthetic aperture radar （ISAR） imaging achieves high azimuth resolution. However, because of the instability of the radar system, the echoes of the 1SAR w...Through the coherent accumulation of target echoes, inverse synthetic aperture radar （ISAR） imaging achieves high azimuth resolution. However, because of the instability of the radar system, the echoes of the 1SAR will be randomly lost. The conventional FFT processing methods can cause image blur and high sidelobes or other issues. A novel algorithm for ISAR missing-data imaging based on the Iterative Adaptive Approach （IAA） is proposed. The algorithm enjoys global convergence properties and does not need to set the parameters in advance. The missing-data ISAR imaging results for simulated and measured data illustrate the effectiveness of the algorithm.展开更多
In this paper, a real-time online data-driven adaptive method is developed to deal with uncertainties such as high nonlinearity, strong coupling, parameter perturbation and external disturbances in attitude control of...In this paper, a real-time online data-driven adaptive method is developed to deal with uncertainties such as high nonlinearity, strong coupling, parameter perturbation and external disturbances in attitude control of fixed-wing unmanned aerial vehicles (UAVs). Firstly, a model-free adaptive control (MFAC) method requiring only input/output (I/O) data and no model information is adopted for control scheme design of angular velocity subsystem which contains all model information and up-mentioned uncertainties. Secondly, the internal model control (IMC) method featured with less tuning parameters and convenient tuning process is adopted for control scheme design of the certain Euler angle subsystem. Simulation results show that, the method developed is obviously superior to the cascade PID (CPID) method and the nonlinear dynamic inversion (NDI) method.展开更多
This paper focuses on the numerical solution of a tumor growth model under a data-driven approach.Based on the inherent laws of the data and reasonable assumptions,an ordinary differential equation model for tumor gro...This paper focuses on the numerical solution of a tumor growth model under a data-driven approach.Based on the inherent laws of the data and reasonable assumptions,an ordinary differential equation model for tumor growth is established.Nonlinear fitting is employed to obtain the optimal parameter estimation of the mathematical model,and the numerical solution is carried out using the Matlab software.By comparing the clinical data with the simulation results,a good agreement is achieved,which verifies the rationality and feasibility of the model.展开更多
Hepatocellular carcinoma is becoming an increasing indication for liver transplantation, but selection and allocation of patients are challenging because of organ shortages. Conventional Milan criteria are the referen...Hepatocellular carcinoma is becoming an increasing indication for liver transplantation, but selection and allocation of patients are challenging because of organ shortages. Conventional Milan criteria are the reference for the selection of patients worldwide, but many expanded criteria, like University of California San Francisco criteria and up-to-7 criteria, have demonstrated that survival and recurrence results are lower than those for restricted indications. Correct staging is crucial and should include surrogate markers of biological aggressiveness(α-fetoprotein, response to loco-regional treatments). Successful down-staging can select between patients with tumor burden initially beyond transplantation criteria those with a more favorable biology, provided a 3-mo stability in meeting the transplantation criteria. Allocation rules are constantly adjusted to minimize the imbalance between the priorities of candidates with and without hepatocellular carcinoma, and take into account local donor rate and waitlist dynamics. Recently, Mazzaferro et al proposed a benefit-oriented "adaptive approach", in which the selection and allocation of patients are based on their response to non-transplantation treatments: low priority for transplantation in case of complete response, high priority in case of partial response or recurrence, and no listing in case of progression beyond transplantation criteria.展开更多
Extreme wave is highly nonlinear and may occur due to diverse reasons unexpectedly.The simulated results of extreme wave based on wave focusing,which were generated using high order spectrum method,are presented.The i...Extreme wave is highly nonlinear and may occur due to diverse reasons unexpectedly.The simulated results of extreme wave based on wave focusing,which were generated using high order spectrum method,are presented.The influences of the steepness,frequency bandwidth as well as frequency spectrum on focusing position shift were examined,showing that they can affect the wave focusing significantly.Hence,controlled accurate generation of extreme wave at a predefined position in wave flume is a difficult but important task.In this paper,an iterative adaptive approach is applied using linear dispersion theory to optimize the control signal of the wavemaker.The performance of the proposed approach is numerically investigated for a wide variety of scenarios.The results demonstrate that this approach can reproduce accurate wave focusing effectively.展开更多
The paper demonstrates the possibility to enhance the damping of inter-area oscillations using Wide Area Measurement (WAM) based adaptive supervisory controller (ASC) which considers the wide-area signal transmission ...The paper demonstrates the possibility to enhance the damping of inter-area oscillations using Wide Area Measurement (WAM) based adaptive supervisory controller (ASC) which considers the wide-area signal transmission delays. The paper uses an LMI-based iterative nonlinear optimization algorithm to establish a method of designing state-feedback controllers for power systems with a time-varying delay. This method is based on the delay-dependent stabilization conditions obtained by the improved free weighting matrix (IFWM) approach. In the stabilization conditions, the upper bound of feedback signal’s transmission delays is taken into consideration. Combining theoriesof state feedback control and state observer, the ASC is designed and time-delay output feedback robust controller is realized for power system. The ASC uses the input information from Phase Measurement Units (PMUs) in the system and dispatches supplementary control signals to the available local controllers. The design of the ASC is explained in detail and its performance validated by time domain simulations on a New England test power system (NETPS).展开更多
This paper studies the problem of diagnosis strategy for a doubly fed induction motor (DFIM) sensor faults. This strategy is based on unknown input proportional integral (PI) multiobserver. Thecontribution of this pap...This paper studies the problem of diagnosis strategy for a doubly fed induction motor (DFIM) sensor faults. This strategy is based on unknown input proportional integral (PI) multiobserver. Thecontribution of this paper is on one hand the creation of a new DFIM model based on multi-model approach and, on the other hand, the synthesis of an adaptive PI multi-observer. The DFIM Volt per Hertz drive system behaves as a nonlinear complex system. It consists of a DFIM powered through a controlled PWM Voltage Source Inverter (VSI). The need of a sensorless drive requires soft sensors such as estimators or observers. In particular, an adaptive Proportional-Integral multi-observer is synthesized in order to estimate the DFIM’s outputs which are affected by different faults and to generate the different residual signals symptoms of sensor fault occurrence. The convergence of the estimation error is guaranteed by using the Lyapunov’s based theory. The proposed diagnosis approach is experimentally validated on a 1 kW Induction motor. Obtained simulation results confirm that the adaptive PI multiobserver consent to accomplish the detection, isolation and fault identification tasks with high dynamic performances.展开更多
By adopting the linguistic adaptation model in particular,irony is pragmatically analyzed as adaptation to the physical,social and mental elements in language use and language interpretation.Meanwhile the adaptation i...By adopting the linguistic adaptation model in particular,irony is pragmatically analyzed as adaptation to the physical,social and mental elements in language use and language interpretation.Meanwhile the adaptation is processed dynamically,and the medium of adaptation is salience.展开更多
Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and ...Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.展开更多
A strategy for spacecraft autonomous rendezvous on an elliptical orbit in situation of no orbit information is developed.Lawden equation is used to describe relative motion of two spacecraft.Then an adaptive gain fact...A strategy for spacecraft autonomous rendezvous on an elliptical orbit in situation of no orbit information is developed.Lawden equation is used to describe relative motion of two spacecraft.Then an adaptive gain factor is introduced,and an adaptive control law for auton-omous rendezvous on the elliptical orbit is designed using Lyapunov approach.The relative motion is proved to be ultimately bounded under this control law,and the final relative position error can achieve the expected magnitude.Simulation results indicate that the adaptive control law can realize autonomous rendezvous on the elliptical orbit with relative state information only.展开更多
In order to analyze the stability impact of cooperative adaptive cruise control （CACC） platoon, an adaptive control model designed for the lead vehicle in a CACC platoon （LCACC model） in heterogeneous traffic flow...In order to analyze the stability impact of cooperative adaptive cruise control （CACC） platoon, an adaptive control model designed for the lead vehicle in a CACC platoon （LCACC model） in heterogeneous traffic flow with both CACC and manual vehicles is proposed. Considering the communication delay of a CACC platoon, a frequency-domain approach is taken to analyze the stability conditions of the novel lead-vehicle CACC model. Field trajectory data from the next-generation simulation （NGSIM） data is used as the initial condition. To account for car- following behaviors in reality, an intelligent driver model （IDM） is calibrated with the same NGSIM dataset from a previous study to model manual vehicles. The stability conditions of the proposed model are validated by the ring- road stability analysis. The ring-road test results indicate the potential of the LCACC model for improving the traffic flow stability impact of CACC platoons. Sensitivity analysis shows that the CACC fleet size has impact on the parameters of the LCACC model.展开更多
It is pointed out that the damping matrix deduced by active members in the finite element vibration equation of a truss adaptive structure generally can not be decoupled, which leads to the difficulty in the process o...It is pointed out that the damping matrix deduced by active members in the finite element vibration equation of a truss adaptive structure generally can not be decoupled, which leads to the difficulty in the process of modal analysis by classical superposition method. This paper focuses on the computational method of the dynamic response for truss adaptive structures. Firstly, a new technique of state vector approach is applied to study the dynamic response of truss adaptive structures. It can make the coeffic lent matrix of first derivative of state vector a symmetric positive definite matrix, and particularly a diagonal matrix provided that mass matrix is derived by lumped method, so the coefficient matrix of the first derivative of state vector can be exactly decomposed by CHOLESKY method. In this case, the proposed technique not only improves the calculation accuracy, but also saves the computing time. Based on the procedure mentioned above, the mathematical formulation for the system response of truss adaptive structures is systematically derived in theory. Thirdly, by using FORTRAN language, a program system for computing dynamic response of truss adaptive structures is developed. Fourthly, a typical 18 bar space truss adaptive structure has been chosen as test numerical examples to show the feasibility and effectiveness of the proposed method. Finally, some good suggestions, such as how to choose complex mode shapes practically in determining the dynamic response are also given. The new approach can be extended to calculate the dynamic response of general adaptive structures.展开更多
An adaptive neuro-fuzzy inference system(ANFIS) for predicting the performance of a reversibly used cooling tower(RUCT) under cross flow conditions as part of a heat pump system for a heating mode in winter was demons...An adaptive neuro-fuzzy inference system(ANFIS) for predicting the performance of a reversibly used cooling tower(RUCT) under cross flow conditions as part of a heat pump system for a heating mode in winter was demonstrated.Extensive field experimental work was carried out in order to gather enough data for training and prediction.The statistical methods,such as the correlation coefficient,absolute fraction of variance and root mean square error,were given to compare the predicted and actual values for model validation.The simulation results predicted with the ANFIS can be used to simulate the performance of a reversibly used cooling tower quite accurately.Therefore,the ANFIS approach can reliably be used for forecasting the performance of RUCT.展开更多
Predictive biomarkers are important to the future of oncology; they can be used to identify patient populations who will benefit from therapy, increase the value of cancer medicines, and decrease the size and cost of ...Predictive biomarkers are important to the future of oncology; they can be used to identify patient populations who will benefit from therapy, increase the value of cancer medicines, and decrease the size and cost of clinical trials while increasing their chance of success. But predictive biomarkers do not always work. When unsuccessful, they add cost, complexity, and time to drug development. This perspective describes phases 2 and 3 development methods that efficiently and adaptively check the ability of a biomarker to predict clinical outcomes. In the end, the biomarker is emphasized to the extent that it can actually predict.展开更多
The mathematical model of optimal placement of active members in truss adaptive structures is essentially a nonlinear multi-objective optimization problem with mixed variables. It is usually much difficult and costly ...The mathematical model of optimal placement of active members in truss adaptive structures is essentially a nonlinear multi-objective optimization problem with mixed variables. It is usually much difficult and costly to be solved. In this paper, the optimal location of active members is treated in terms of （0, 1） discrete variables. Structural member sizes, control gains, and （0, 1） placement variables are treated simultaneously as design variables. Then, a succinct and reasonable compromise scalar model, which is transformed from original multi-objective optimization, is established, in which the （0, 1） discrete variables are converted into an equality constraint. Secondly, by penalty function approach, the subsequent scalar mixed variable compromise model can be formulated equivalently as a sequence of continuous variable problems. Thirdly, for each continuous problem in the sequence, by choosing intermediate design variables and temporary critical constraints, the approximation concept is carried out to generate a sequence of explicit approximate problems which enhance the quality of the approximate design problems. Considering the proposed method, a FORTRAN program OPAMTAS2.0 for optimal placement of active members in truss adaptive structures is developed, which is used by the constrained variable metric method with the watchdog technique （CVMW method）. Finally, a typical 18 bar truss adaptive structure as test numerical examples is presented to illustrate that the design methodology set forth is simple, feasible, efficient and stable. The established scalar mixed variable compromise model that can avoid the ill-conditioned possibility caused by the different orders of magnitude of various objective functions in optimization process, therefore, it enables the optimization algorithm to have a good stability. On the other hand, the proposed novel optimization technique can make both discrete and continuous variables be optimized simultaneously.展开更多
The chaos control of uncertain unified chaotic systems is considered. Cascade adaptive control approach with only one control input is presented to stabilize states of the uncertain unified chaotic system at the zero ...The chaos control of uncertain unified chaotic systems is considered. Cascade adaptive control approach with only one control input is presented to stabilize states of the uncertain unified chaotic system at the zero equilibrium point. Since an adaptive controller based on dynamic compensation mechanism is employed, the exact model of the unified chaotic system is not necessarily required. By choosing appropriate controller parameters, chaotic phenomenon can be suppressed and the response speed is tunable. Sufficient condition for the asymptotic stability of the approach is derived. Numerical simulation results confirm that the cascade adaptive control approach with only one control signal is valid in chaos control of uncertain unified chaotic systems.展开更多
基金supported in part by the Innovation and Technology Commission of Hong Kong,China(ITS/136/20,ITS/234/21,MHP/096/22,ITS/235/22)Multi-Scale Medical Robotics Center,InnoHK,China(8312051)+1 种基金Research Grants Council(RGC) of Hong Kong,China(CUHK 14217822,CUHK14207823,AoE/E-407/24-N)The Chinese University of Hong Kong(CUHK) Direct Grant。
文摘Realizing optimal control performance for continuum robots(CRs) poses huge challenges on traditional modelbased optimal control approaches due to their high degrees of freedom,complex nonlinear dynamics and soft continuum morphologies which are difficult to explicitly model.This paper proposes a model-free adaptive optimal control algorithm(ADAPT)for CRs.In our strategy,we consider CRs as a class of nonlinear continuous-time dynamical systems in the state space,wherein the position of the end-effector is considered as the state and the input torque is mapped as the control input.Then,the optimized Hamilton-Jacobi-Bellman(HJB) equation is derived by optimal control principles,and subsequently solved by the proposed ADAPT algorithm without requiring knowledge of the original system dynamics.Under some mild assumptions,the global stability and convergence of the closed-loop control approach are guaranteed.Several simulation experiments are conducted on a magnetic CR(MCR) to demonstrate the practicality and effectiveness of the ADAPT algorithm.
基金The National Key R&D Program of China(2021ZD0201300)the National Natural Science Foundation of China(624B2058,U1913602 and 61936004)+1 种基金the Innovation Group Project of the National Natural Science Foundation of China(61821003)the 111 Project on Computational Intelligence and Intelligent Control(B18024).
文摘For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies bionic analytical framework based on the partial differential equation-ordinary differential equation(PDE-ODE)approach.Specifically,by designing a specialized network communication protocol and employing the spatial continuum method for densely distributed agents,this paper models the tracking errors of densely distributed agents as a PDE equivalent to a human disease transmission model,and that of sparsely distributed agents as several ODEs equivalent to the predator population models.The coupling relationship between the PDE and ODE models is established through boundary conditions of the PDE,thereby forming a PDE-ODE-based tracking error model for the considered MASs.Furthermore,by integrating adaptive neural control scheme with the aforementioned biological models,a“Flexible Neural Network”endowed with adaptive and self-stabilized capabilities is constructed,which acts upon the considered MASs,enabling their practical finite-time deployment.Finally,effectiveness of the developed approach is illustrated through a numerical example.
基金supported by the National Natural Science Foundation of China (No. 41204055)the National Basic Research Program of China (No. 2013CB733203)the Opening Project (No. SMIL-2014-06) of Hubei Subsurface Multi-Scale Imaging Lab (SMIL), China University of Geosciences, Wuhan, China
文摘A goal-oriented adaptive finite element（FE） method for solving 3D direct current（DC） resistivity modeling problem is presented. The model domain is subdivided into unstructured tetrahedral elements that allow for efficient local mesh refinement and flexible description of complex models. The elements that affect the solution at each receiver location are adaptively refined according to a goal-oriented posteriori error estimator using dual-error weighting approach. The FE method with adapting mesh can easily handle such structures at almost any level of complexity. The method is demonstrated on two synthetic resistivity models with analytical solutions and available results from integral equation method, so the errors can be quantified. The applicability of the numerical method is illustrated on a resistivity model with a topographic ridge. Numerical examples show that this method is flexible and accurate for geometrically complex situations.
基金supported by Beijing Natural Science Foundation(No.4142017)International Cooperation Project of National Natural Science Foundation of China(No.61120106009)Beijing Science and Technology Commission Precision Machinery Projects(No.Z121100001612007)
文摘Nowadays, high-precision motion controls are needed in modern manufacturing industry. A data-driven nonparametric model adaptive control(NMAC) method is proposed in this paper to control the position of a linear servo system. The controller design requires no information about the structure of linear servo system, and it is based on the estimation and forecasting of the pseudo-partial derivatives(PPD) which are estimated according to the voltage input and position output of the linear motor. The characteristics and operational mechanism of the permanent magnet synchronous linear motor(PMSLM) are introduced, and the proposed nonparametric model control strategy has been compared with the classic proportional-integral-derivative(PID) control algorithm. Several real-time experiments on the motion control system incorporating a permanent magnet synchronous linear motor showed that the nonparametric model adaptive control method improved the system s response to disturbances and its position-tracking precision, even for a nonlinear system with incompletely known dynamic characteristics.
基金Sponsored by the National Natural Science Foundation of China(Grant Nos.61471149 and 61622107)
文摘Through the coherent accumulation of target echoes, inverse synthetic aperture radar （ISAR） imaging achieves high azimuth resolution. However, because of the instability of the radar system, the echoes of the 1SAR will be randomly lost. The conventional FFT processing methods can cause image blur and high sidelobes or other issues. A novel algorithm for ISAR missing-data imaging based on the Iterative Adaptive Approach （IAA） is proposed. The algorithm enjoys global convergence properties and does not need to set the parameters in advance. The missing-data ISAR imaging results for simulated and measured data illustrate the effectiveness of the algorithm.
文摘In this paper, a real-time online data-driven adaptive method is developed to deal with uncertainties such as high nonlinearity, strong coupling, parameter perturbation and external disturbances in attitude control of fixed-wing unmanned aerial vehicles (UAVs). Firstly, a model-free adaptive control (MFAC) method requiring only input/output (I/O) data and no model information is adopted for control scheme design of angular velocity subsystem which contains all model information and up-mentioned uncertainties. Secondly, the internal model control (IMC) method featured with less tuning parameters and convenient tuning process is adopted for control scheme design of the certain Euler angle subsystem. Simulation results show that, the method developed is obviously superior to the cascade PID (CPID) method and the nonlinear dynamic inversion (NDI) method.
基金National Natural Science Foundation of China(Project No.:12371428)Projects of the Provincial College Students’Innovation and Training Program in 2024(Project No.:S202413023106,S202413023110)。
文摘This paper focuses on the numerical solution of a tumor growth model under a data-driven approach.Based on the inherent laws of the data and reasonable assumptions,an ordinary differential equation model for tumor growth is established.Nonlinear fitting is employed to obtain the optimal parameter estimation of the mathematical model,and the numerical solution is carried out using the Matlab software.By comparing the clinical data with the simulation results,a good agreement is achieved,which verifies the rationality and feasibility of the model.
文摘Hepatocellular carcinoma is becoming an increasing indication for liver transplantation, but selection and allocation of patients are challenging because of organ shortages. Conventional Milan criteria are the reference for the selection of patients worldwide, but many expanded criteria, like University of California San Francisco criteria and up-to-7 criteria, have demonstrated that survival and recurrence results are lower than those for restricted indications. Correct staging is crucial and should include surrogate markers of biological aggressiveness(α-fetoprotein, response to loco-regional treatments). Successful down-staging can select between patients with tumor burden initially beyond transplantation criteria those with a more favorable biology, provided a 3-mo stability in meeting the transplantation criteria. Allocation rules are constantly adjusted to minimize the imbalance between the priorities of candidates with and without hepatocellular carcinoma, and take into account local donor rate and waitlist dynamics. Recently, Mazzaferro et al proposed a benefit-oriented "adaptive approach", in which the selection and allocation of patients are based on their response to non-transplantation treatments: low priority for transplantation in case of complete response, high priority in case of partial response or recurrence, and no listing in case of progression beyond transplantation criteria.
基金supported by the Basic Research Program of Dalian Maritime University(Grant No.3132019112)the Open Fund Program of State Key Laboratory of Coastal and Offshore Engineering,Dalian University of Technology(Grant No.LP1910).
文摘Extreme wave is highly nonlinear and may occur due to diverse reasons unexpectedly.The simulated results of extreme wave based on wave focusing,which were generated using high order spectrum method,are presented.The influences of the steepness,frequency bandwidth as well as frequency spectrum on focusing position shift were examined,showing that they can affect the wave focusing significantly.Hence,controlled accurate generation of extreme wave at a predefined position in wave flume is a difficult but important task.In this paper,an iterative adaptive approach is applied using linear dispersion theory to optimize the control signal of the wavemaker.The performance of the proposed approach is numerically investigated for a wide variety of scenarios.The results demonstrate that this approach can reproduce accurate wave focusing effectively.
文摘The paper demonstrates the possibility to enhance the damping of inter-area oscillations using Wide Area Measurement (WAM) based adaptive supervisory controller (ASC) which considers the wide-area signal transmission delays. The paper uses an LMI-based iterative nonlinear optimization algorithm to establish a method of designing state-feedback controllers for power systems with a time-varying delay. This method is based on the delay-dependent stabilization conditions obtained by the improved free weighting matrix (IFWM) approach. In the stabilization conditions, the upper bound of feedback signal’s transmission delays is taken into consideration. Combining theoriesof state feedback control and state observer, the ASC is designed and time-delay output feedback robust controller is realized for power system. The ASC uses the input information from Phase Measurement Units (PMUs) in the system and dispatches supplementary control signals to the available local controllers. The design of the ASC is explained in detail and its performance validated by time domain simulations on a New England test power system (NETPS).
文摘This paper studies the problem of diagnosis strategy for a doubly fed induction motor (DFIM) sensor faults. This strategy is based on unknown input proportional integral (PI) multiobserver. Thecontribution of this paper is on one hand the creation of a new DFIM model based on multi-model approach and, on the other hand, the synthesis of an adaptive PI multi-observer. The DFIM Volt per Hertz drive system behaves as a nonlinear complex system. It consists of a DFIM powered through a controlled PWM Voltage Source Inverter (VSI). The need of a sensorless drive requires soft sensors such as estimators or observers. In particular, an adaptive Proportional-Integral multi-observer is synthesized in order to estimate the DFIM’s outputs which are affected by different faults and to generate the different residual signals symptoms of sensor fault occurrence. The convergence of the estimation error is guaranteed by using the Lyapunov’s based theory. The proposed diagnosis approach is experimentally validated on a 1 kW Induction motor. Obtained simulation results confirm that the adaptive PI multiobserver consent to accomplish the detection, isolation and fault identification tasks with high dynamic performances.
文摘By adopting the linguistic adaptation model in particular,irony is pragmatically analyzed as adaptation to the physical,social and mental elements in language use and language interpretation.Meanwhile the adaptation is processed dynamically,and the medium of adaptation is salience.
基金supported in part by the National Natural Science Foundation of China(62222301, 62073085, 62073158, 61890930-5, 62021003)the National Key Research and Development Program of China (2021ZD0112302, 2021ZD0112301, 2018YFC1900800-5)Beijing Natural Science Foundation (JQ19013)。
文摘Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.
基金supported by the National Natural Science Foundation of China(10702003)
文摘A strategy for spacecraft autonomous rendezvous on an elliptical orbit in situation of no orbit information is developed.Lawden equation is used to describe relative motion of two spacecraft.Then an adaptive gain factor is introduced,and an adaptive control law for auton-omous rendezvous on the elliptical orbit is designed using Lyapunov approach.The relative motion is proved to be ultimately bounded under this control law,and the final relative position error can achieve the expected magnitude.Simulation results indicate that the adaptive control law can realize autonomous rendezvous on the elliptical orbit with relative state information only.
基金The National High Technology Research and Development Program of China(863 Program)(No.2011AA110405)
文摘In order to analyze the stability impact of cooperative adaptive cruise control （CACC） platoon, an adaptive control model designed for the lead vehicle in a CACC platoon （LCACC model） in heterogeneous traffic flow with both CACC and manual vehicles is proposed. Considering the communication delay of a CACC platoon, a frequency-domain approach is taken to analyze the stability conditions of the novel lead-vehicle CACC model. Field trajectory data from the next-generation simulation （NGSIM） data is used as the initial condition. To account for car- following behaviors in reality, an intelligent driver model （IDM） is calibrated with the same NGSIM dataset from a previous study to model manual vehicles. The stability conditions of the proposed model are validated by the ring- road stability analysis. The ring-road test results indicate the potential of the LCACC model for improving the traffic flow stability impact of CACC platoons. Sensitivity analysis shows that the CACC fleet size has impact on the parameters of the LCACC model.
基金supported by National Natural Science Foundation of China (Grant No. 10472007)
文摘It is pointed out that the damping matrix deduced by active members in the finite element vibration equation of a truss adaptive structure generally can not be decoupled, which leads to the difficulty in the process of modal analysis by classical superposition method. This paper focuses on the computational method of the dynamic response for truss adaptive structures. Firstly, a new technique of state vector approach is applied to study the dynamic response of truss adaptive structures. It can make the coeffic lent matrix of first derivative of state vector a symmetric positive definite matrix, and particularly a diagonal matrix provided that mass matrix is derived by lumped method, so the coefficient matrix of the first derivative of state vector can be exactly decomposed by CHOLESKY method. In this case, the proposed technique not only improves the calculation accuracy, but also saves the computing time. Based on the procedure mentioned above, the mathematical formulation for the system response of truss adaptive structures is systematically derived in theory. Thirdly, by using FORTRAN language, a program system for computing dynamic response of truss adaptive structures is developed. Fourthly, a typical 18 bar space truss adaptive structure has been chosen as test numerical examples to show the feasibility and effectiveness of the proposed method. Finally, some good suggestions, such as how to choose complex mode shapes practically in determining the dynamic response are also given. The new approach can be extended to calculate the dynamic response of general adaptive structures.
基金Projects(51108165, 51178170) supported by the National Natural Science Foundation of China
文摘An adaptive neuro-fuzzy inference system(ANFIS) for predicting the performance of a reversibly used cooling tower(RUCT) under cross flow conditions as part of a heat pump system for a heating mode in winter was demonstrated.Extensive field experimental work was carried out in order to gather enough data for training and prediction.The statistical methods,such as the correlation coefficient,absolute fraction of variance and root mean square error,were given to compare the predicted and actual values for model validation.The simulation results predicted with the ANFIS can be used to simulate the performance of a reversibly used cooling tower quite accurately.Therefore,the ANFIS approach can reliably be used for forecasting the performance of RUCT.
文摘Predictive biomarkers are important to the future of oncology; they can be used to identify patient populations who will benefit from therapy, increase the value of cancer medicines, and decrease the size and cost of clinical trials while increasing their chance of success. But predictive biomarkers do not always work. When unsuccessful, they add cost, complexity, and time to drug development. This perspective describes phases 2 and 3 development methods that efficiently and adaptively check the ability of a biomarker to predict clinical outcomes. In the end, the biomarker is emphasized to the extent that it can actually predict.
基金supported by National Natural Science Foundation of China(Grant No.10472007)
文摘The mathematical model of optimal placement of active members in truss adaptive structures is essentially a nonlinear multi-objective optimization problem with mixed variables. It is usually much difficult and costly to be solved. In this paper, the optimal location of active members is treated in terms of （0, 1） discrete variables. Structural member sizes, control gains, and （0, 1） placement variables are treated simultaneously as design variables. Then, a succinct and reasonable compromise scalar model, which is transformed from original multi-objective optimization, is established, in which the （0, 1） discrete variables are converted into an equality constraint. Secondly, by penalty function approach, the subsequent scalar mixed variable compromise model can be formulated equivalently as a sequence of continuous variable problems. Thirdly, for each continuous problem in the sequence, by choosing intermediate design variables and temporary critical constraints, the approximation concept is carried out to generate a sequence of explicit approximate problems which enhance the quality of the approximate design problems. Considering the proposed method, a FORTRAN program OPAMTAS2.0 for optimal placement of active members in truss adaptive structures is developed, which is used by the constrained variable metric method with the watchdog technique （CVMW method）. Finally, a typical 18 bar truss adaptive structure as test numerical examples is presented to illustrate that the design methodology set forth is simple, feasible, efficient and stable. The established scalar mixed variable compromise model that can avoid the ill-conditioned possibility caused by the different orders of magnitude of various objective functions in optimization process, therefore, it enables the optimization algorithm to have a good stability. On the other hand, the proposed novel optimization technique can make both discrete and continuous variables be optimized simultaneously.
基金supported by the National Basic Research Program of China (Grant No.2007CB210106)
文摘The chaos control of uncertain unified chaotic systems is considered. Cascade adaptive control approach with only one control input is presented to stabilize states of the uncertain unified chaotic system at the zero equilibrium point. Since an adaptive controller based on dynamic compensation mechanism is employed, the exact model of the unified chaotic system is not necessarily required. By choosing appropriate controller parameters, chaotic phenomenon can be suppressed and the response speed is tunable. Sufficient condition for the asymptotic stability of the approach is derived. Numerical simulation results confirm that the cascade adaptive control approach with only one control signal is valid in chaos control of uncertain unified chaotic systems.
