中国科学院数学与系统科学研究院期刊网

25 December 2024, Volume 37 Issue 6
    

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  • RIGATOS Gerasimos, ABBASZADEH Masoud, SIANO Pierluigi, AL-NUMA Mohammed, ZOUARI Farouk
    Journal of Systems Science & Complexity. 2024, 37(6): 2293-2317. https://doi.org/10.1007/s11424-024-3566-5
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    The overuse and misuse of antibiotics has become a major problem for public health. People become resistant to antibiotics and because of this the anticipated therapeutic effect is never reached. In-hospital infections are often aggravated and large amounts of money are spent for treating complications in the patients' condition. In this paper a nonlinear optimal (H-infinity) control method is developed for the dynamic model of bacterial infections exhibiting resistance to antibiotics. First, differential flatness properties are proven for the associated state-space model. Next, the state-space description undergoes approximate linearization with the use of first-order Taylor series expansion and through the computation of the associated Jacobian matrices. The linearization process takes place at each sampling instance around a time-varying operating point which is defined by the present value of the system's state vector and by the last sampled value of the control inputs vector. For the approximately linearized model of the system a stabilizing H-infinity feedback controller is designed. To compute the controller's gains an algebraic Riccati equation has to be repetitively solved at each time-step of the control algorithm. The global stability properties of the control scheme are proven through Lyapunov analysis. The proposed method achieves stabilization and remedy for the bacterial infection under moderate use of antibiotics.
  • IBEN AMMAR Imen, DOUMIATI Moustapha, TALJ Reine, CHOKOR Abbas, MACHMOUM Mohamed
    Journal of Systems Science & Complexity. 2024, 37(6): 2318-2346. https://doi.org/10.1007/s11424-024-3197-x
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    The safety of vehicle travel relies on good stability performance, making vehicle motion control a vital technology in vehicles. This paper focuses on investigating the impact of roll control on vehicle performance, particularly in terms of avoiding rollover and ensuring lateral stability. By introducing a feedback roll moment, the roll motion can be effectively controlled. The paper considers two roll reference generators: A static one aimed at zero roll, and a dynamic one based on the vehicle's lateral acceleration. The static roll reference generator enhances stability by employing a fixed reference, particularly beneficial during routine driving conditions. In contrast, the dynamic roll reference generator continually adapts the roll angle reference in response to real-time vehicle dynamics and driving conditions. These proposed reference generators can be paired with varying suspension systems — Static reference could be achieved using semi-active suspensions, while the dynamic one is integrated into advanced active suspension systems, offering heightened adaptability and performance. To address the roll control objectives, this paper proposes a novel sum of squares (SOS) integral polynomial tracking control. The proposed controller satisfies control bounds and considers control constraints during the design phase. The effectiveness and robustness of the proposed control scheme are evaluated through numerical simulations using a full vehicle nonlinear model in Matlab/Simulink. The results of these simulations are compared to super-twisting sliding mode and Lyapunov-based controllers.
  • WU Haiwen, XU Dabo
    Journal of Systems Science & Complexity. 2024, 37(6): 2347-2367. https://doi.org/10.1007/s11424-024-3539-8
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    In this paper, the authors address the attitude regulation problem of uncertain flexible spacecraft with unknown control directions and input disturbances. The major challenges of the problem include the concurrence of the unknown actuation sign and the unknown parameters in both the plant and the external disturbances, along with the impact of vibrations from flexible appendages. To overcome these challenges, the authors transform the conventional mathematical model of a flexible spacecraft to a multivariable strict-feedback normal form and adopt a systematic approach within the framework of nonlinear output regulation. To solve the attitude regulation and disturbance rejection problem, the authors introduce a nonlinear internal model candidate to convert the problem into a stabilization problem for an augmented system. Then, a Nussbaum function-based stabilizer is designed to handle unknown control directions and complete the design. Simulation results are provided to show the effectiveness of the proposed controller.
  • FU Songren, CHEN Liangbiao, ZHANG Ji-Feng
    Journal of Systems Science & Complexity. 2024, 37(6): 2368-2389. https://doi.org/10.1007/s11424-024-3565-6
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    In this paper, the authors consider the inverse problem for the Moore-Gibson-Thompson equation with a memory term and variable diffusivity, which introduce a sort of delay in the dynamics, producing nonlocal effects in time. The Hölder stability of simultaneously determining the spatially varying viscosity coefficient and the source term is obtained by means of the key pointwise Carleman estimate for the Moore-Gibson-Thompson equation. For the sake of generality in mathematical tools, the analysis of this paper is discussed within the framework of Riemannian geometry.
  • YUAN Shuo, YU Chengpu, SUN Jian
    Journal of Systems Science & Complexity. 2024, 37(6): 2390-2405. https://doi.org/10.1007/s11424-024-3563-8
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    This paper studies the distributed consensus control for linear multi-agent systems under discontinuous communication and control updating. A fully distributed event-triggered adaptive control protocol with strictly positive minimum interevent time (MIET) guarantees is proposed. First, an event-triggered distributed adaptive control law without using prior global information of network topologies is presented, which achieves asymptotic consensus via discrete control updating and intermittent communication. Then, a hybrid adaptive event-triggering scheme with an internal timer is designed that is activated only when the timer decreases to zero from a specified positive value. Under the proposed triggering scheme, not only Zeno behavior is excluded but also a strictly positive MIET between any two consecutive events is guaranteed, which facilitates the physical implementation. In contrast to the existing related results, the proposed fully distributed protocol only needs low-frequency communication and control updating, while ensuring the strictly positive MIET property. Finally, a simulation example is given to illustrate the effectiveness of the theoretical results.
  • BAI Peng, KANG Yu, WANG Kangcheng, ZHAO Yunbo, DONG Shaojie
    Journal of Systems Science & Complexity. 2024, 37(6): 2406-2423. https://doi.org/10.1007/s11424-024-3502-8
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    Functional testing is key to fulfill quality control in laptop manufacturing and is of great economic value. However, due to the unavailability of practical data, mathematical model and systematic perspective, it has barely been touched from the academic community to date. For the first time, this work provides technical understanding of the key principles of functional testing, mathematically models the general framework, elucidates existing testing strategy under the proposed framework and model, and finally proposes a specified optimization strategy which outperforms existing strategies. This work lays the model foundation for the further optimization of functional testing, and can be regarded as a good example of how a systematic approach can solve practical industrial challenges.
  • LI Tianhao, LIU Zhixin, LIU Lizheng, HU Xiaoming
    Journal of Systems Science & Complexity. 2024, 37(6): 2424-2450. https://doi.org/10.1007/s11424-024-3154-8
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    This paper studies a dynamical system that models the free recall dynamics of working memory. This model is an attractor neural network with $n$ modules, named hypercolumns, and each module consists of $m$ minicolumns. Under mild conditions on the connection weights between minicolumns, the authors investigate the long-term evolution behavior of the model, namely the existence and stability of equilibria and limit cycles. The authors also give a critical value in which Hopf bifurcation happens. Finally, the authors give a sufficient condition under which this model has a globally asymptotically stable equilibrium consisting of synchronized minicolumn states in each hypercolumn, which implies that in this case recalling is impossible. Numerical simulations are provided to illustrate the proposed theoretical results. Furthermore, a numerical example the authors give suggests that patterns can be stored in not only equilibria and limit cycles, but also strange attractors (or chaos).
  • YANG Chen, LI Yan, CHEN Qijun
    Journal of Systems Science & Complexity. 2024, 37(6): 2451-2465. https://doi.org/10.1007/s11424-024-3293-y
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    This study addresses the fault detection problem in multi-agent systems (MASs) with additive faults and stochastic uncertainties. The main focus is on enhancing the fault detection capability of each agent through a cooperative fault detection scheme, fostering cooperation between agents in two scenarios. For Gaussian uncertainties, one scheme is developed using the maximum likelihood estimation (MLE) matching expectation maximization (EM) algorithm. Additionally, a novel cooperative fault detection scheme is introduced to handle non-Gaussian uncertainties, where the cooperation mechanism among agents is determined by approximating non-Gaussian uncertainties using the Gaussian mixture model (GMM). The effectiveness and improvements of the proposed cooperative fault detection method are validated through numerical simulations.
  • WANG Bin, SHI Jingtao
    Journal of Systems Science & Complexity. 2024, 37(6): 2466-2486. https://doi.org/10.1007/s11424-024-4236-3
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    This paper is concerned with the relationship between general maximum principle and dynamic programming principle for the stochastic recursive optimal control problem with jumps, where the control domain is not necessarily convex. Relations among the adjoint processes, the generalized Hamiltonian function and the value function are proven, under the assumption of a smooth value function and within the framework of viscosity solutions, respectively. Some examples are given to illustrate the theoretical results.
  • CHENG Songsong, YU Xin, ZENG Xianlin, LIANG Shu, HONG Yiguang
    Journal of Systems Science & Complexity. 2024, 37(6): 2487-2510. https://doi.org/10.1007/s11424-024-3407-6
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    This paper develops distributed algorithms for solving Sylvester equations. The authors transform solving Sylvester equations into a distributed optimization problem, unifying all eight standard distributed matrix structures. Then the authors propose a distributed algorithm to find the least squares solution and achieve an explicit linear convergence rate. These results are obtained by carefully choosing the step-size of the algorithm, which requires particular information of data and Laplacian matrices. To avoid these centralized quantities, the authors further develop a distributed scaling technique by using local information only. As a result, the proposed distributed algorithm along with the distributed scaling design yields a universal method for solving Sylvester equations over a multi-agent network with the constant step-size freely chosen from configurable intervals. Finally, the authors provide three examples to illustrate the effectiveness of the proposed algorithms.
  • XU Shuai, LI Chanying
    Journal of Systems Science & Complexity. 2024, 37(6): 2511-2529. https://doi.org/10.1007/s11424-024-3564-7
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    This paper studies sampled-data proportional-integral (PI) control for a basic class of nonlinear uncertain systems. The authors claim that a process with the first-order dynamics can achieve zero steady-state error through a sampled-data PI controller whenever the sampling period $T<T_0(k_p,k_i,L)$, where $T_0(k_p,k_i,L)$ is a number determined by the parameters $k_p,k_i$ and the Lipschitz constant $L$ of the system. On the other hand, once the sampling period $T$ is given, the two parameters $k_p$ and $k_i$ of the sampled-data PI controller are apparently restricted by $T$, or the setpoint tracking error diverges.
  • LIANG Shu, ZHANG Lei, WEI Yiheng, LIU Yemo
    Journal of Systems Science & Complexity. 2024, 37(6): 2530-2555. https://doi.org/10.1007/s11424-024-3413-8
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    In this paper, the authors consider distributed convex optimization over hierarchical networks. The authors exploit the hierarchical architecture to design specialized distributed algorithms so that the complexity can be reduced compared with that of non-hierarchically distributed algorithms. To this end, the authors use local agents to process local functions in the same manner as other distributed algorithms that take advantage of multiple agents' computing resources. Moreover, the authors use pseudocenters to directly integrate lower-level agents' computation results in each iteration step and then share the outcomes through the higher-level network formed by pseudocenters. The authors prove that the complexity of the proposed algorithm exponentially decreases with respect to the total number of pseudocenters. To support the proposed decomposition-composition method for agents and pseudocenters, the authors develop a class of operators. These operators are generalizations of the widely-used subgradient based operator and the proximal operator and can be used in distributed convex optimization. Additionally, these operators are closed with respect to the addition and composition operations; thus, they are suitable to guide hierarchically distributed design and analysis. Furthermore, these operators make the algorithm flexible since agents with different local functions can adopt suitable operators to simplify their calculations. Finally, numerical examples also illustrate the effectiveness of the method.
  • XU Hao, YU Dengxiu, SUI Shuai, XU Bowen, CHEN C. L. Philip
    Journal of Systems Science & Complexity. 2024, 37(6): 2556-2578. https://doi.org/10.1007/s11424-024-4051-x
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    In this paper, the singularity-free predefined-time fuzzy adaptive tracking control problem is studied for non-strict feedback (NSF) nonlinear systems considering mismatched external disturbances. An innovative practical predefined-time stability (PPTS) criterion is proposed to provide the theoretical basis for subsequent control design. Compared to the existing predefined-time stability (PTS) criterion, this criterion has a broader application range and can solve the control design issues of nonlinear systems with system uncertainties. Fuzzy logic systems (FLSs) are employed to identify unknown nonlinear functions. Based on the backstepping control technology, a singularity-free predefined-time control (PTC) design method is proposed, in which the hyperbolic tangent function is utilized to avoid the singular problem, and the nature of fuzzy basis function is adopted to resolve the algebraic loop problem. The PPTS of the closed-loop NSF nonlinear system is proven with the Lyapunov theory and the proposed PPTS criterion. Ultimately, the efficiency of the presented PTC design method is verified by several sets of simulations on a single link manipulator system.
  • XU Yu-Tian, WU Ai-Guo
    Journal of Systems Science & Complexity. 2024, 37(6): 2579-2594. https://doi.org/10.1007/s11424-024-4036-9
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    In this paper, attitude tracking control with arbitrary convergence time for rigid spacecraft is considered. First, a novel time-varying sliding function is proposed to achieve free-will arbitrary time convergence when the system states reside on the sliding surface. With such a sliding function, an attitude tracking controller is designed to guarantee that the states of the closed-loop system converge to the sliding surface within a predetermined time in the presence of external disturbances. The free-will arbitrary time convergences of the closed-loop system and sliding function are illustrated by numerical simulations.
  • DAMAK Hanen, ABOTHHER Amal, HAMMAMI Mohamed Ali
    Journal of Systems Science & Complexity. 2024, 37(6): 2595-2613. https://doi.org/10.1007/s11424-024-4247-0
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    This paper focuses on studying the problem of robust output practical stability of time-varying nonlinear control systems. The main innovation lies in the fact that the proposed approach for stability analysis allows for the computation of bounds that characterize the asymptotic convergence of solutions to a small ball centered at the origin using a Lyapunov method with a definite derivative. Under different conditions on the perturbation, the authors demonstrate that the system can be globally robustly asymptotically output stable by designing a candidate feedback controller. Finally, three examples are given to illustrate the practical implications and significance of the theoretical results.
  • ZHAO Bin
    Journal of Systems Science & Complexity. 2024, 37(6): 2614-2632. https://doi.org/10.1007/s11424-024-3295-9
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    This paper investigates optimal control for two kinds of multi-agent systems with the sampled-data based communication protocols. Necessary and sufficient conditions on data-sampling controllability are obtained for sampled-data based multi-agent systems, which indicate that sampling periods affect the controllability of double-integrator systems, whereas the controllability of single-integrator systems is decided by the interconnection topology. To obtain the optimal control inputs under different objectives, two concepts of 2-norm-optimal control and infinity-norm-optimal control are proposed. For both kinds of systems, generalised inverse matrices of controllability test matrices are utilised to derive the 2-norm-optimal controls, and the infinity-norm-optimal controls are equivalently transformed to be the optimal solutions of some specific linear programming problems via matrix vectorization. Some illustrative examples are provided for the main results in this paper.
  • ZHANG Liuliu, WANG Peng, QIAN Cheng, HUA Changchun
    Journal of Systems Science & Complexity. 2024, 37(6): 2633-2653. https://doi.org/10.1007/s11424-024-3445-0
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    This paper focuses on the trajectory tracking control problem of unmanned underwater vehicles (UUVs) with unknown dead-zone inputs. The primary objective is to design an adaptive trajectory tracking error constraint controller using the fully actuated systems (FAs) approach to enable UUVs to asymptotically track target signals. Firstly, a novel error constraint fully actuated systems (ECFAs) approach is proposed by incorporating the tracking error dependent normalized function and barrier function along with time-varying scaling. Secondly, in order to deal with the model uncertainties of the UUVs, adaptive radial basis function neural networks (RBFNNs) is combined with the ECFAs approach. Then, a positive time-varying integral function is introduced to completely eliminate the effect of the residual effect caused by unknown dead-zone inputs, and it is proved that the trajectory tracking error converges to zero asymptotically based on the Lyapunov functions. Finally, the simulation results demonstrate the effectiveness of the designed adaptive controller.
  • WU Binrong, WANG Lin, ZENG Yu-Rong
    Journal of Systems Science & Complexity. 2024, 37(6): 2654-2679. https://doi.org/10.1007/s11424-024-2307-0
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    This paper proposes a novel interpretable tourism demand forecasting framework that considers the impact of the COVID-19 pandemic by using multi-source heterogeneous data, namely, historical tourism volume, newly confirmed cases in tourist origins and destinations, and search engine data. This paper introduces newly confirmed cases in tourist origins and tourist destinations to forecast tourism demand and proposes a new two-stage decomposition method called ensemble empirical mode decomposition-variational mode decomposition to deal with the tourist arrival sequence. To solve the problem of insufficient interpretability of existing tourism demand forecasting, this paper also proposes a novel interpretable tourism demand forecasting model called JADE-TFT, which utilizes an adaptive differential evolution algorithm with external archiving (JADE) to intelligently and efficiently optimize the hyperparameters of temporal fusion transformers (TFT). The validity of the proposed prediction framework is verified by actual cases based on Hainan and Macau tourism data sets. The interpretable experimental results show that newly confirmed cases in tourist origins and tourist destinations can better reflect tourists' concerns about travel in the post-pandemic era, and the two-stage decomposition method can effectively identify the inflection point of tourism prediction, thereby increasing the prediction accuracy of tourism demand.
  • YAN Linlin, CHEN Xiaolan, YANG Yi, HE Yong
    Journal of Systems Science & Complexity. 2024, 37(6): 2680-2696. https://doi.org/10.1007/s11424-024-4071-6
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    In this paper, the authors take Hubei carbon trading market prices as a sample, and select 27 variables from five aspects: International carbon market prices, energy prices, the macroeconomic situation, exchange rate factors and climate environment. The authors construct the elliptical approximate factor model and use a robust two step method based on multivariate Kendall's Tau matrix to extract common factors, identify the influencing factors of carbon prices, make out-of-sample forecasting of carbon prices, and compare with the prediction based on the historical mean of carbon trading market prices. The results show that the prediction of carbon trading market prices using elliptical approximate factor model is more accurate than the prediction based on the historical mean of carbon trading market prices. Among them, fossil energy prices, international carbon prices and climate environment are important influencing factors of carbon trading prices.
  • DAI Zhifeng, WU Tong
    Journal of Systems Science & Complexity. 2024, 37(6): 2697-2720. https://doi.org/10.1007/s11424-024-3224-y
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    This study examines the influence of oil shocks on systemic risk spillover among the commodity markets. Specifically, this paper uses the DCC-GARCH approach combined with the TVP-VAR model to calculate risk connectedness and the GARCH-MIDAS model to explore how oil shocks from different sources affect the risk spillover effects among the commodity markets. The results are the following: First, there are significant risk spillovers among the commodity markets with important time-varying characteristics and with sharp changes in times of crisis. The industrial metals, agriculture, precious metals, and light energy commodity markets are risk recipients, and the energy and livestock commodity markets are risk exporters. Second, oil price shocks, particularly oil aggregate demand shocks, prominently affect the total risk connectedness among the commodity markets. In particular, the impact on the net risk spillover effect of different commodity market differs.
  • FENG Fan, ZHAO Shishun, LI Shuwei, SUN Jianguo
    Journal of Systems Science & Complexity. 2024, 37(6): 2721-2737. https://doi.org/10.1007/s11424-024-3549-6
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    Interval-censored failure time data arise frequently in periodical follow-up studies including clinical trials and epidemiological surveys. In addition, some covariates may be subject to measurement errors due to the instrumental contamination, biological variation or other reasons. For the analysis of interval-censored data with mis-measured covariates, the existing methods either assume a parametric model or rely on the availability of replicated surrogate measurements for the error-prone covariate, which both have obvious limitations. To overcome these shortcomings, the authors propose a simulation-extrapolation estimation procedure under a general class of transformation models. The resulting estimators are shown to be consistent and asymptotically normal. The numerical results obtained from a simulation study indicate that the proposed method performs reasonably well in practice. In particular, the proposed method can reduce the estimation bias given by the naive method that does not take measurement errors into account. Finally, the proposed method is applied to a real data set on hypobaric decompression sickness.
  • WANG Wenjun, YANG Zhihuang
    Journal of Systems Science & Complexity. 2024, 37(6): 2738-2770. https://doi.org/10.1007/s11424-024-3129-9
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    This paper investigates the moment selection and parameter estimation problem of high-dimensional unconditional moment conditions. First, the authors propose a Fantope projection and selection (FPS) approach to distinguish the informative and uninformative moments in high-dimensional unconditional moment conditions. Second, for the selected unconditional moment conditions, the authors present a generalized empirical likelihood (GEL) approach to estimate unknown parameters. The proposed method is computationally feasible, and can efficiently avoid the well-known ill-posed problem of GEL approach in the analysis of high-dimensional unconditional moment conditions. Under some regularity conditions, the authors show the consistency of the selected moment conditions, the consistency and asymptotic normality of the proposed GEL estimator. Two simulation studies are conducted to investigate the finite sample performance of the proposed methodologies. The proposed method is illustrated by a real example.