This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramia...This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramians directly from the expansion coefficients of impulse responses.Leveraging these factors,we develop two model reduction algorithms that integrate the low-rank square root method with dominant subspace projection.Our method is computationally efficient and flexible,requiring only a few matrix-vector operations and a singular value decomposition of a low-dimensional matrix,thereby avoiding the need to solve differential Lyapunov equations.Numerical experiments confirm the effectiveness of the proposed approach.展开更多
A parametric method for the gain-scheduled controller design of a linear time-varying system is given. According to the proposed scheduling method, the performance between adjacent characteristic points is preserved b...A parametric method for the gain-scheduled controller design of a linear time-varying system is given. According to the proposed scheduling method, the performance between adjacent characteristic points is preserved by the invariant eigenvalues and the gradually varying eigenvectors. A sufficient stability criterion is given by constructing a series of Lyapunov functions based on the selected discrete characteristic points. An important contribution is that it provides a simple and feasible approach for the design of gain-scheduled controllers for linear time-varying systems, which can guarantee both the global stability and the desired closed-loop performance of the resulted system. The method is applied to the design of a BTT missile autopilot and the simulation results show that the method is superior to the traditional one in sense of either global stability or system performance.展开更多
In this paper, an iterative learning control algorithm is proposed for discrete linear time-varying systems to track iterationvarying desired trajectories. A high-order internal model(HOIM) is utilized to describe the...In this paper, an iterative learning control algorithm is proposed for discrete linear time-varying systems to track iterationvarying desired trajectories. A high-order internal model(HOIM) is utilized to describe the variation of desired trajectories in the iteration domain. In the sequel, the HOIM is incorporated into the design of learning gains. The learning convergence in the iteration axis can be guaranteed with rigorous proof. The simulation results with permanent magnet linear motors(PMLM) demonstrate that the proposed HOIM based approach yields good performance and achieves perfect tracking.展开更多
The adaptive control of nonlinear systems that are linear in the unknown but time-varying parameters are treated in this paper.Since satisfactory transient performance is an important factor,multiple models are requir...The adaptive control of nonlinear systems that are linear in the unknown but time-varying parameters are treated in this paper.Since satisfactory transient performance is an important factor,multiple models are required as these parameters change abruptly in the parameter space.In this paper we consider both the multiple models with switching and tuning methodology as well as multiple models with second level adaptation for this class of systems.We demonstrate that the latter approach is better than the former.展开更多
The optimal control problem was studied for linear time-varying systems,which was affected by external persistent disturbances with known dynamic characteristics but unknown initial conditions. To damp the effect of d...The optimal control problem was studied for linear time-varying systems,which was affected by external persistent disturbances with known dynamic characteristics but unknown initial conditions. To damp the effect of disturbances in an optimal fashion,we obtained a new feedforward and feedback optimal control law and gave the control algorithm by solving a Riccati differential equation and a matrix differential equation. Simulation results showed that the achieved optimal control law was realizable,efficient and robust to reject the external disturbances.展开更多
An efficient algorithm for the representation and approximation of linear time-varying systems is presented via the fast real-valued discrete Gabor transform. Compared with the existing algorithm based on the traditio...An efficient algorithm for the representation and approximation of linear time-varying systems is presented via the fast real-valued discrete Gabor transform. Compared with the existing algorithm based on the traditional complex-valued discrete Gabor transform, the proposed algorithm runs faster, can more easily be implemented in software or hardware, and leads to a more compact representation. Simulation results are given for demonstration.展开更多
The stabilization problem of linear time-varying systems with both state and input constraints is considered. Sufficient conditions for the existence of the solution to this problem are derived and a gain-switched（ga...The stabilization problem of linear time-varying systems with both state and input constraints is considered. Sufficient conditions for the existence of the solution to this problem are derived and a gain-switched（gain-scheduled） state feedback control scheme is built to stabilize the constrained timevarying system. The design problem is transformed to a series of convex feasibility problems which can be solved efficiently. A design example is given to illustrate the effect of the proposed algorithm.展开更多
By applying genetic algorithms (GA) to on-line identification of linear time-varying systems; a number of modifications are made to the Simple Genetic Algorithm to improve the performance of the algorithm in identific...By applying genetic algorithms (GA) to on-line identification of linear time-varying systems; a number of modifications are made to the Simple Genetic Algorithm to improve the performance of the algorithm in identification applications. The simulation results indicate that the method is not only capable of following the changing parameters of the system, but also has improved the identification accuracy compared with that using the least square method.展开更多
A wavelet based identification method for linear time-varying systems is presented,and the ridge and skeleton of the continuous wavelet transform of free response is used to extract time-varying parameters. The stiffn...A wavelet based identification method for linear time-varying systems is presented,and the ridge and skeleton of the continuous wavelet transform of free response is used to extract time-varying parameters. The stiffness and damping coefficients of single-degree-of—freedom systems,frequencies and damping ratios of multi-degree-of-freedom systems are estimated without any prior information of systems. The proposed method is applied to linear time-varying systems with both abrupt and smooth variation parameters. Gaussian white noise is added to the response to test the anti-noise performance of the algorithm. The simulation results show that the proposed method is capable of accurately tracking the variation of the systems.展开更多
The optimal control problem for linear time-varying systems affected by external persistent disturbances with known dynamic characteristics but unknown initial conditions is consider and a design procedure of a feedfo...The optimal control problem for linear time-varying systems affected by external persistent disturbances with known dynamic characteristics but unknown initial conditions is consider and a design procedure of a feedforward and feedbaek optimal controller is presented. The condition of existence and uniqueness of the control law is given. The disturbanee observer is proposed to make the feedforward control law realizable physically. Simulation results demonstrate that the feedforward and feedbaek optimal control law is more effective and robust than the elassical state feedbaek control law with respect to external disturbanees.展开更多
In this paper, an iterative learning control strategy is presented for a class of nonlinear time-varying systems, the timevarying parameters are expanded into Fourier series with bounded remainder term. The backsteppi...In this paper, an iterative learning control strategy is presented for a class of nonlinear time-varying systems, the timevarying parameters are expanded into Fourier series with bounded remainder term. The backstepping design technique is used to deal with system dynamics with non-global Lipschitz nonlinearities and the approach proposed in this paper solves the non-uniform trajectory tracking problem. Based on the Lyapunov-like synthesis, the proposed method shows that all signals in the closed-loop system remain bounded over a pre-specified time interval [0, T ]. And perfect non-uniform trajectory tracking of the system output is completed. A typical series is introduced in order to deal with the unknown bound of remainder term. Finally, a simulation example shows the feasibility and effectiveness of the approach.展开更多
The problem of linear time-varying（LTV） system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system mo...The problem of linear time-varying（LTV） system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system modal analysis under the ＂frozen-time＂ assumption are not able to determine the dynamic stability of LTV systems. Time-dependent state space representations of LTV systems are first introduced, and the corresponding modal analysis theories are subsequently presented via a stabilitypreserving state transformation. The time-varying modes of LTV systems are extended in terms of uniqueness, and are further interpreted to determine the system＇s stability. An extended modal identification is proposed to estimate the time-varying modes, consisting of the estimation of the state transition matrix via a subspace-based method and the extraction of the time-varying modes by the QR decomposition. The proposed approach is numerically validated by three numerical cases, and is experimentally validated by a coupled moving-mass simply supported beam exper- imental case. The proposed approach is capable of accurately estimating the time-varying modes, and provides anew way to determine the dynamic stability of LTV systems by using the estimated time-varying modes.展开更多
An iterative learning control algorithm based on shifted Legendre orthogonal polynomials is proposed to address the terminal control problem of linear time-varying systems. First, the method parameterizes a linear tim...An iterative learning control algorithm based on shifted Legendre orthogonal polynomials is proposed to address the terminal control problem of linear time-varying systems. First, the method parameterizes a linear time-varying system by using shifted Legendre polynomials approximation. Then, an approximated model for the linear time-varying system is deduced by employing the orthogonality relations and boundary values of shifted Legendre polynomials. Based on the model, the shifted Legendre polynomials coefficients of control function are iteratively adjusted by an optimal iterative learning law derived. The algorithm presented can avoid solving the state transfer matrix of linear time-varying systems. Simulation results illustrate the effectiveness of the proposed method.展开更多
This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact ...This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact set large enough in which the approximation of any unknown continuous function by a fuzzy logic system(FLS)is effective while compensating sensor/actuator faults and external disturbances.The difficulty is to verify the boundedness of closed-loop signals on the constructed compact set and to reduce the number of the variables of the fuzzy membership functions as many as possible.By a new lemma,linear/nonlinear terms are introduced in adaptive laws to dominate unknown residual terms.With adding a power integrator method,a unified fault-tolerant controller is designed to drive the tracking error to converge to a small compact set of the origin within a fixed time,regardless of whether the system suffers from faults and disturbances.Superior to the existing results,in the presence of time-varying factors the scheme of this paper clarifies the logical relationship between the compactness of the approximation and the boundedness of the state variables.Finally,the application of control strategy is demonstrated by numerical/practical examples.展开更多
现有电力负荷预测方法面临诸多挑战,尤其是在考虑气象因素对负荷波动的影响时,传统方法往往忽视气象特征与负荷之间复杂的非线性关系,导致预测精度不足。对此文中提出一种基于气象相似日修正(meteorological similar day correction,MS...现有电力负荷预测方法面临诸多挑战,尤其是在考虑气象因素对负荷波动的影响时,传统方法往往忽视气象特征与负荷之间复杂的非线性关系,导致预测精度不足。对此文中提出一种基于气象相似日修正(meteorological similar day correction,MSDC)和改进鹦鹉优化(improved parrot optimizer,IPO)线性分解(decomposition-based linear,DLinear)的日前电力负荷预测模型。首先运用Logistic映射、自适应变异策略、螺旋波动搜索IPO对DLinear超参数进行优化,然后由DLinear提取数据的周期性和趋势性特征,最后通过比对气象特征欧氏距离修正负荷预测值,形成基于IPO-DLinear-MSDC的日前电力负荷预测模型。采用2024年6月至10月湖南株洲地区总电力负荷数据集进行仿真分析,IPO-DLinear-MSDC模型的输出平均绝对百分比误差(mean absolute percentage error,MAPE)、决定系数R2分别为4.67%、0.833,相较于IPO-DLinear与PO-DLinear模型,MAPE分别下降了0.83个百分点、1.43个百分点,R2分别提升了0.074、0.125。展开更多
This paper considers adaptive event-triggered stabilization for a class of uncertain time-varying nonlinear systems.Remarkably,the systems contain intrinsic time-varying unknown parameters which are allowed to be non-...This paper considers adaptive event-triggered stabilization for a class of uncertain time-varying nonlinear systems.Remarkably,the systems contain intrinsic time-varying unknown parameters which are allowed to be non-differentiable and in turn can be fast-varying.Moreover,the systems admit unknown control directions.To counteract the different uncertainties,more than one compensation mechanism has to be incorporated.However,in the context of event-triggered control,ensuring the effectiveness of these compensation mechanisms under reduced execution necessitates delicate design and analysis.This paper proposes a tight and powerful strategy for adaptive event-triggered control(ETC)by integrating the state-of-the-art adaptive techniques.In particular,the strategy substantially mitigates the conservatism caused by repetitive inequality-based treatments of uncertainties.Specifically,by leveraging the congelation-of-variables method and tuning functions,the conservatism in the treatment of the fast-varying parameters is significantly reduced.With multiple Nussbaum functions employed to handle unknown control directions,a set of dynamic compensations is designed to counteract unknown amplitudes of control coefficients without relying on inequality-based treatments.Moreover,a dedicated dynamic compensation is introduced to deal with the control coefficient coupled with the execution error,based on which a relativethreshold event-triggering mechanism(ETM)is rigorously validated.It turns out that the adaptive event-triggered controller achieves the closed-loop convergence while guaranteeing a uniform lower bound for inter-execution times.Simulation results verify the effectiveness and superiority of the proposed strategy.展开更多
Two new linear furocoumarins were isolated from Notopterygium incisum using silica gel,gel Sephadex LH-20 column chromatography,and preparative high-performance liquid chromatography.The structures of the new compound...Two new linear furocoumarins were isolated from Notopterygium incisum using silica gel,gel Sephadex LH-20 column chromatography,and preparative high-performance liquid chromatography.The structures of the new compounds were elucidated through analysis of spectroscopic evidence,including data obtained from high-resolution electrospray ionization mass spectrometry(HRESIMS)and nuclear magnetic resonance(NMR).The absolute configurations of Notoprenylate L(1)and Nototerprinol K(2)were further confirmed using electronic circular dichroism(ECD)calculations.Compound 1 demonstrated the ability to inhibit the expression of nitric oxide(NO),a pro-inflammatory factor,in lipopolysaccharide-induced RAW264.7 macrophages at a concentration of 7.5μmol/L,indicating its potential for anti-inflammatory activity.展开更多
The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show...The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show clinical potential,their development has been hindered by the intrinsic trade-off between high sensitivity and full-range linearity(R^(2)>0.99 up to 1 MPa)in conventional designs.Inspired by the tactile sensing mechanism of human skin,where dermal stratification enables wide-range pressure adaptation and ion-channelregulated signaling maintains linear electrical responses,we developed a dual-mechanism flexible iontronic pressure sensor(FIPS).This innovative design synergistically combines two bioinspired components:interdigitated fabric microstructures enabling pressure-proportional contact area expansion(αP1/3)and iontronic film facilitating self-adaptive ion concentration modulation(αP^(2/3)),which together generate a linear capacitance-pressure response(CαP).The FIPS achieves breakthrough performance:242 kPa^(-1)sensitivity with 0.997linearity across 0-1 MPa,yielding a record linear sensing factor(LSF=242,000).The design is validated across various substrates and ionic materials,demonstrating its versatility.Finally,the FIPS-driven design enables a smart insole demonstrating 1.8%error in tibial load assessment during gait analysis,outperforming nonlinear counterparts(6.5%error)in early fracture-risk prediction.The biomimetic design framework establishes a universal approach for developing high-performance linear sensors,establishing generalized principles for medical-grade wearable devices.展开更多
The bipartite containment control problem for heterogeneous nonlinear multi-agent systems(HNMASs)within multi-group networks under signed digraphs is investigated,where the first-order and second-order nonlinear dynam...The bipartite containment control problem for heterogeneous nonlinear multi-agent systems(HNMASs)within multi-group networks under signed digraphs is investigated,where the first-order and second-order nonlinear dynamic agents belong to distinct groups.Interactions are cooperative-antagonistic within each group and sign-in-degree balanced across the inter-groups.Firstly,a state feedback control protocol is designed to ensure that the trajectories of followers in diverse groups can converge to distinct convex hulls formed by their corresponding leaders,respectively.As an extension,the bipartite control problem with time-variant formation for the multi-agent system(MAS)is also considered,and a corresponding control protocol with formation compensation vectors is given.Finally,in view of Lyapunov stability theory and matrix inequality,the sufficient conditions for realizing the bipartite containment control are obtained,and several simulations are provided to verify the validity of the above methods.展开更多
Rydberg-atom-based superheterodyne receivers integrate self-calibration,high sensitivity,a wide operational frequency range,and phase/frequency resolved detection capabilities,demonstrating broad application prospects...Rydberg-atom-based superheterodyne receivers integrate self-calibration,high sensitivity,a wide operational frequency range,and phase/frequency resolved detection capabilities,demonstrating broad application prospects as nextgeneration microwave receivers.Linear gain and linear dynamic range(LDR)are critical metrics for assessing receiver sensitivity and demodulation fidelity,respectively.We numerically solve the four-level master equation and then employ particle swarm optimization(PSO)algorithm to co-optimize linear gain and LDR in atomic superheterodyne receivers based on balanced homodyne detection.Further,we systematically account for dominant dephasing mechanisms in the simulation,encompassing spontaneous decay,transit dephasing,collision dephasing,laser linewidth dephasing,and Doppler averaging.Homodyne readout utilizes both the real and imaginary parts of polarizability for sensing.In the case of the photon shot noise limit,its signal-to-noise ratio(SNR)expression resembles that of direct optical-intensity readout.However,the inherent coherent subtraction operation in homodyne detection significantly suppresses common-mode noise,while appropriately increasing the reference beam power enhances the gain in practical experiments.Indeed,this co-optimization problem,characterized by a high-dimensional variable space,two objectives,and non-convexity,is well-suited for solution by PSO.In addition,probe and coupling detuning contribute equivalently to polarizability and compensate for each other owing to Doppler averaging,thereby reducing the optimization variable space by one.By adopting a product form of linear gain and LDR as the fitness function,the PSO achieves rapid convergence.Here,the effectiveness of the PSO results is verified via the total harmonic distortion(THD).The relative error-based LDR calculation method we proposed efficiently measures receiver response linearity with consuming fewer computational resources.This research is expected to offer valuable insights into enhancing the performance of Rydberg-atom-based superheterodyne receivers.展开更多
文摘This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramians directly from the expansion coefficients of impulse responses.Leveraging these factors,we develop two model reduction algorithms that integrate the low-rank square root method with dominant subspace projection.Our method is computationally efficient and flexible,requiring only a few matrix-vector operations and a singular value decomposition of a low-dimensional matrix,thereby avoiding the need to solve differential Lyapunov equations.Numerical experiments confirm the effectiveness of the proposed approach.
基金supported by the National Natural Science Foundation of China (60474015)Program for Changjiang Scholars and Innovative Research Team in University
文摘A parametric method for the gain-scheduled controller design of a linear time-varying system is given. According to the proposed scheduling method, the performance between adjacent characteristic points is preserved by the invariant eigenvalues and the gradually varying eigenvectors. A sufficient stability criterion is given by constructing a series of Lyapunov functions based on the selected discrete characteristic points. An important contribution is that it provides a simple and feasible approach for the design of gain-scheduled controllers for linear time-varying systems, which can guarantee both the global stability and the desired closed-loop performance of the resulted system. The method is applied to the design of a BTT missile autopilot and the simulation results show that the method is superior to the traditional one in sense of either global stability or system performance.
基金supported by National Basic Research Program of China(973 Program)(No.2012CB316400)National Natural Science Foundation of China(Nos.61171034 and 61273134)
文摘In this paper, an iterative learning control algorithm is proposed for discrete linear time-varying systems to track iterationvarying desired trajectories. A high-order internal model(HOIM) is utilized to describe the variation of desired trajectories in the iteration domain. In the sequel, the HOIM is incorporated into the design of learning gains. The learning convergence in the iteration axis can be guaranteed with rigorous proof. The simulation results with permanent magnet linear motors(PMLM) demonstrate that the proposed HOIM based approach yields good performance and achieves perfect tracking.
文摘The adaptive control of nonlinear systems that are linear in the unknown but time-varying parameters are treated in this paper.Since satisfactory transient performance is an important factor,multiple models are required as these parameters change abruptly in the parameter space.In this paper we consider both the multiple models with switching and tuning methodology as well as multiple models with second level adaptation for this class of systems.We demonstrate that the latter approach is better than the former.
基金the National Natural Science Foundation of China (Grant No.60074001)the Natural Science Foundation of Shandong Province (Grant No.Y2000G02).
文摘The optimal control problem was studied for linear time-varying systems,which was affected by external persistent disturbances with known dynamic characteristics but unknown initial conditions. To damp the effect of disturbances in an optimal fashion,we obtained a new feedforward and feedback optimal control law and gave the control algorithm by solving a Riccati differential equation and a matrix differential equation. Simulation results showed that the achieved optimal control law was realizable,efficient and robust to reject the external disturbances.
基金Supported by the Excellent Young Teachers Program of the Ministry of Education, P. R. China (No. 2001-1739 and No. 2003-145)
文摘An efficient algorithm for the representation and approximation of linear time-varying systems is presented via the fast real-valued discrete Gabor transform. Compared with the existing algorithm based on the traditional complex-valued discrete Gabor transform, the proposed algorithm runs faster, can more easily be implemented in software or hardware, and leads to a more compact representation. Simulation results are given for demonstration.
基金supported by the National Natural Science Foundation of China(6132106261503100)the China Postdoctoral Science Foundation(2014M550189)
文摘The stabilization problem of linear time-varying systems with both state and input constraints is considered. Sufficient conditions for the existence of the solution to this problem are derived and a gain-switched（gain-scheduled） state feedback control scheme is built to stabilize the constrained timevarying system. The design problem is transformed to a series of convex feasibility problems which can be solved efficiently. A design example is given to illustrate the effect of the proposed algorithm.
文摘By applying genetic algorithms (GA) to on-line identification of linear time-varying systems; a number of modifications are made to the Simple Genetic Algorithm to improve the performance of the algorithm in identification applications. The simulation results indicate that the method is not only capable of following the changing parameters of the system, but also has improved the identification accuracy compared with that using the least square method.
文摘A wavelet based identification method for linear time-varying systems is presented,and the ridge and skeleton of the continuous wavelet transform of free response is used to extract time-varying parameters. The stiffness and damping coefficients of single-degree-of—freedom systems,frequencies and damping ratios of multi-degree-of-freedom systems are estimated without any prior information of systems. The proposed method is applied to linear time-varying systems with both abrupt and smooth variation parameters. Gaussian white noise is added to the response to test the anti-noise performance of the algorithm. The simulation results show that the proposed method is capable of accurately tracking the variation of the systems.
基金This project was supported by the National Natural Science Foundation of China (60074001) and the Natural ScienceFoundation of Shandong Province (Y2000G02)
文摘The optimal control problem for linear time-varying systems affected by external persistent disturbances with known dynamic characteristics but unknown initial conditions is consider and a design procedure of a feedforward and feedbaek optimal controller is presented. The condition of existence and uniqueness of the control law is given. The disturbanee observer is proposed to make the feedforward control law realizable physically. Simulation results demonstrate that the feedforward and feedbaek optimal control law is more effective and robust than the elassical state feedbaek control law with respect to external disturbanees.
基金supported by National Natural Science Foundation of China(No.60974139)Fundamental Research Funds for the Central Universities(No.72103676)
文摘In this paper, an iterative learning control strategy is presented for a class of nonlinear time-varying systems, the timevarying parameters are expanded into Fourier series with bounded remainder term. The backstepping design technique is used to deal with system dynamics with non-global Lipschitz nonlinearities and the approach proposed in this paper solves the non-uniform trajectory tracking problem. Based on the Lyapunov-like synthesis, the proposed method shows that all signals in the closed-loop system remain bounded over a pre-specified time interval [0, T ]. And perfect non-uniform trajectory tracking of the system output is completed. A typical series is introduced in order to deal with the unknown bound of remainder term. Finally, a simulation example shows the feasibility and effectiveness of the approach.
基金Supported by the China Scholarship Council,National Natural Science Foundation of China(Grant No.11402022)the Interuniversity Attraction Poles Programme of the Belgian Science Policy Office(DYSCO)+1 种基金the Fund for Scientific Research–Flanders(FWO)the Research Fund KU Leuven
文摘The problem of linear time-varying（LTV） system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system modal analysis under the ＂frozen-time＂ assumption are not able to determine the dynamic stability of LTV systems. Time-dependent state space representations of LTV systems are first introduced, and the corresponding modal analysis theories are subsequently presented via a stabilitypreserving state transformation. The time-varying modes of LTV systems are extended in terms of uniqueness, and are further interpreted to determine the system＇s stability. An extended modal identification is proposed to estimate the time-varying modes, consisting of the estimation of the state transition matrix via a subspace-based method and the extraction of the time-varying modes by the QR decomposition. The proposed approach is numerically validated by three numerical cases, and is experimentally validated by a coupled moving-mass simply supported beam exper- imental case. The proposed approach is capable of accurately estimating the time-varying modes, and provides anew way to determine the dynamic stability of LTV systems by using the estimated time-varying modes.
基金Supported by National Natural Science Foundation of P. R. China (60474049)
文摘An iterative learning control algorithm based on shifted Legendre orthogonal polynomials is proposed to address the terminal control problem of linear time-varying systems. First, the method parameterizes a linear time-varying system by using shifted Legendre polynomials approximation. Then, an approximated model for the linear time-varying system is deduced by employing the orthogonality relations and boundary values of shifted Legendre polynomials. Based on the model, the shifted Legendre polynomials coefficients of control function are iteratively adjusted by an optimal iterative learning law derived. The algorithm presented can avoid solving the state transfer matrix of linear time-varying systems. Simulation results illustrate the effectiveness of the proposed method.
基金supported by National Natural Science Foundation of China[grant number 62173208]Taishan Scholar Project of Shandong Province of China[grant number tsqn202103061]。
文摘This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact set large enough in which the approximation of any unknown continuous function by a fuzzy logic system(FLS)is effective while compensating sensor/actuator faults and external disturbances.The difficulty is to verify the boundedness of closed-loop signals on the constructed compact set and to reduce the number of the variables of the fuzzy membership functions as many as possible.By a new lemma,linear/nonlinear terms are introduced in adaptive laws to dominate unknown residual terms.With adding a power integrator method,a unified fault-tolerant controller is designed to drive the tracking error to converge to a small compact set of the origin within a fixed time,regardless of whether the system suffers from faults and disturbances.Superior to the existing results,in the presence of time-varying factors the scheme of this paper clarifies the logical relationship between the compactness of the approximation and the boundedness of the state variables.Finally,the application of control strategy is demonstrated by numerical/practical examples.
文摘现有电力负荷预测方法面临诸多挑战,尤其是在考虑气象因素对负荷波动的影响时,传统方法往往忽视气象特征与负荷之间复杂的非线性关系,导致预测精度不足。对此文中提出一种基于气象相似日修正(meteorological similar day correction,MSDC)和改进鹦鹉优化(improved parrot optimizer,IPO)线性分解(decomposition-based linear,DLinear)的日前电力负荷预测模型。首先运用Logistic映射、自适应变异策略、螺旋波动搜索IPO对DLinear超参数进行优化,然后由DLinear提取数据的周期性和趋势性特征,最后通过比对气象特征欧氏距离修正负荷预测值,形成基于IPO-DLinear-MSDC的日前电力负荷预测模型。采用2024年6月至10月湖南株洲地区总电力负荷数据集进行仿真分析,IPO-DLinear-MSDC模型的输出平均绝对百分比误差(mean absolute percentage error,MAPE)、决定系数R2分别为4.67%、0.833,相较于IPO-DLinear与PO-DLinear模型,MAPE分别下降了0.83个百分点、1.43个百分点,R2分别提升了0.074、0.125。
基金supported in part by the National Natural Science Foundation of China(62033007)the Fundamental Research Program of Shandong Province(ZR2023ZD37).
文摘This paper considers adaptive event-triggered stabilization for a class of uncertain time-varying nonlinear systems.Remarkably,the systems contain intrinsic time-varying unknown parameters which are allowed to be non-differentiable and in turn can be fast-varying.Moreover,the systems admit unknown control directions.To counteract the different uncertainties,more than one compensation mechanism has to be incorporated.However,in the context of event-triggered control,ensuring the effectiveness of these compensation mechanisms under reduced execution necessitates delicate design and analysis.This paper proposes a tight and powerful strategy for adaptive event-triggered control(ETC)by integrating the state-of-the-art adaptive techniques.In particular,the strategy substantially mitigates the conservatism caused by repetitive inequality-based treatments of uncertainties.Specifically,by leveraging the congelation-of-variables method and tuning functions,the conservatism in the treatment of the fast-varying parameters is significantly reduced.With multiple Nussbaum functions employed to handle unknown control directions,a set of dynamic compensations is designed to counteract unknown amplitudes of control coefficients without relying on inequality-based treatments.Moreover,a dedicated dynamic compensation is introduced to deal with the control coefficient coupled with the execution error,based on which a relativethreshold event-triggering mechanism(ETM)is rigorously validated.It turns out that the adaptive event-triggered controller achieves the closed-loop convergence while guaranteeing a uniform lower bound for inter-execution times.Simulation results verify the effectiveness and superiority of the proposed strategy.
文摘Two new linear furocoumarins were isolated from Notopterygium incisum using silica gel,gel Sephadex LH-20 column chromatography,and preparative high-performance liquid chromatography.The structures of the new compounds were elucidated through analysis of spectroscopic evidence,including data obtained from high-resolution electrospray ionization mass spectrometry(HRESIMS)and nuclear magnetic resonance(NMR).The absolute configurations of Notoprenylate L(1)and Nototerprinol K(2)were further confirmed using electronic circular dichroism(ECD)calculations.Compound 1 demonstrated the ability to inhibit the expression of nitric oxide(NO),a pro-inflammatory factor,in lipopolysaccharide-induced RAW264.7 macrophages at a concentration of 7.5μmol/L,indicating its potential for anti-inflammatory activity.
基金supported by the National Natural Science Foundation of China(NSFC 52175281,52475315)Youth Innovation Promotion Association of CAS(2021382)。
文摘The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show clinical potential,their development has been hindered by the intrinsic trade-off between high sensitivity and full-range linearity(R^(2)>0.99 up to 1 MPa)in conventional designs.Inspired by the tactile sensing mechanism of human skin,where dermal stratification enables wide-range pressure adaptation and ion-channelregulated signaling maintains linear electrical responses,we developed a dual-mechanism flexible iontronic pressure sensor(FIPS).This innovative design synergistically combines two bioinspired components:interdigitated fabric microstructures enabling pressure-proportional contact area expansion(αP1/3)and iontronic film facilitating self-adaptive ion concentration modulation(αP^(2/3)),which together generate a linear capacitance-pressure response(CαP).The FIPS achieves breakthrough performance:242 kPa^(-1)sensitivity with 0.997linearity across 0-1 MPa,yielding a record linear sensing factor(LSF=242,000).The design is validated across various substrates and ionic materials,demonstrating its versatility.Finally,the FIPS-driven design enables a smart insole demonstrating 1.8%error in tibial load assessment during gait analysis,outperforming nonlinear counterparts(6.5%error)in early fracture-risk prediction.The biomimetic design framework establishes a universal approach for developing high-performance linear sensors,establishing generalized principles for medical-grade wearable devices.
基金National Natural Science Foundation of China(No.12071370)。
文摘The bipartite containment control problem for heterogeneous nonlinear multi-agent systems(HNMASs)within multi-group networks under signed digraphs is investigated,where the first-order and second-order nonlinear dynamic agents belong to distinct groups.Interactions are cooperative-antagonistic within each group and sign-in-degree balanced across the inter-groups.Firstly,a state feedback control protocol is designed to ensure that the trajectories of followers in diverse groups can converge to distinct convex hulls formed by their corresponding leaders,respectively.As an extension,the bipartite control problem with time-variant formation for the multi-agent system(MAS)is also considered,and a corresponding control protocol with formation compensation vectors is given.Finally,in view of Lyapunov stability theory and matrix inequality,the sufficient conditions for realizing the bipartite containment control are obtained,and several simulations are provided to verify the validity of the above methods.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.62331024 and 62571549)the National Key Research and Development Program of China(Grant No.2022YFB2802804)。
文摘Rydberg-atom-based superheterodyne receivers integrate self-calibration,high sensitivity,a wide operational frequency range,and phase/frequency resolved detection capabilities,demonstrating broad application prospects as nextgeneration microwave receivers.Linear gain and linear dynamic range(LDR)are critical metrics for assessing receiver sensitivity and demodulation fidelity,respectively.We numerically solve the four-level master equation and then employ particle swarm optimization(PSO)algorithm to co-optimize linear gain and LDR in atomic superheterodyne receivers based on balanced homodyne detection.Further,we systematically account for dominant dephasing mechanisms in the simulation,encompassing spontaneous decay,transit dephasing,collision dephasing,laser linewidth dephasing,and Doppler averaging.Homodyne readout utilizes both the real and imaginary parts of polarizability for sensing.In the case of the photon shot noise limit,its signal-to-noise ratio(SNR)expression resembles that of direct optical-intensity readout.However,the inherent coherent subtraction operation in homodyne detection significantly suppresses common-mode noise,while appropriately increasing the reference beam power enhances the gain in practical experiments.Indeed,this co-optimization problem,characterized by a high-dimensional variable space,two objectives,and non-convexity,is well-suited for solution by PSO.In addition,probe and coupling detuning contribute equivalently to polarizability and compensate for each other owing to Doppler averaging,thereby reducing the optimization variable space by one.By adopting a product form of linear gain and LDR as the fitness function,the PSO achieves rapid convergence.Here,the effectiveness of the PSO results is verified via the total harmonic distortion(THD).The relative error-based LDR calculation method we proposed efficiently measures receiver response linearity with consuming fewer computational resources.This research is expected to offer valuable insights into enhancing the performance of Rydberg-atom-based superheterodyne receivers.
