Systems & Control Letters最新文献

英文中文

A dynamic event-triggered approach for observer-based formation control of multi-agent systems with designable inter-event time 基于观测器的多代理系统编队控制的动态事件触发方法，事件间时间可设计

IF 2.1 3区计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS

Systems & Control Letters

Pub Date : 2024-11-26 DOI: 10.1016/j.sysconle.2024.105970

Zeyuan Wang , Mohammed Chadli , Steven X. Ding

This paper addresses the leader-following formation control problems for generic linear multi-agent systems under directed topology with designable inter-event time. A synthesis approach combining controller and observer design is developed under a dynamic event-triggered communication and control scheme. The proposed feedback control, state estimation, and event-triggered rules are distributed, and only local information is required for each agent to implement these algorithms. The proposed dynamic event-triggered protocol incorporates model-based estimation and clock-like auxiliary dynamic variables to prolong the inter-event time and economize the network resources. Furthermore, the inter-event time is designable, which allows more flexible tuning of communication frequency with only minor performance degradation. Sufficient conditions for formation control are established by linear matrix inequalities. The proposed method exhibits significant improvement over the dynamic event-triggered control methods described in the existing literature. Compared to the existing static event-triggered strategy, the proposed approach significantly reduces the utilization of communication resources while preserving asymptotic convergence to the desired formation. Comparative simulations demonstrate the validity and effectiveness of the proposed theoretical results.

本文探讨了在可设计事件间时间的有向拓扑结构下，通用线性多代理系统的领导-跟随编队控制问题。在动态事件触发通信和控制方案下，开发了一种结合控制器和观测器设计的综合方法。所提出的反馈控制、状态估计和事件触发规则都是分布式的，每个代理只需要本地信息就能实现这些算法。所提出的动态事件触发协议结合了基于模型的估计和类似时钟的辅助动态变量，延长了事件间时间，节约了网络资源。此外，事件间时间是可设计的，这就允许更灵活地调整通信频率，而仅有轻微的性能下降。通过线性矩阵不等式建立了编队控制的充分条件。与现有文献中描述的动态事件触发控制方法相比，所提出的方法有显著改进。与现有的静态事件触发策略相比，所提出的方法大大减少了通信资源的使用，同时保持了对所需编队的渐进收敛。对比模拟证明了所提理论结果的正确性和有效性。

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引用次数: 0

Finite-time stability in probability of stochastic delay systems via generalized Halanay inequality 通过广义哈拉内不等式实现随机延迟系统概率的有限时间稳定性

IF 2.1 3区计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS

Systems & Control Letters

Pub Date : 2024-11-24 DOI: 10.1016/j.sysconle.2024.105969

Han Yu , Song Zhu , Shiping Wen , Chaoxu Mu

This paper presents novel advancements in the analysis and control of stochastic systems with time-varying delays, focusing on the concept of finite-time stability. Firstly, a new kind of generalized Halanay inequality is established. With this crucial approach, two essential stochastic Lyapunov theorems on the finite-time stability in probability of stochastic delay systems with bounded time delays and unbounded time delays, respectively, are derived. In addition, upper bound estimate for the stochastic settling time is given. Furthermore, a type of nonlinear stochastic delay systems is investigated and a delay-independent controller is proposed to achieve finite-time stability in probability. The effectiveness of the results is demonstrated through two illustrative examples.

本文介绍了具有时变延迟的随机系统的分析和控制方面的新进展，重点是有限时间稳定性的概念。首先，本文建立了一种新的广义哈拉内不等式。利用这一关键方法，分别推导出了关于有界时延和无界时延随机延迟系统概率有限时间稳定性的两个基本随机李雅普诺夫定理。此外，还给出了随机沉降时间的上限估计。此外，还研究了一种非线性随机延迟系统，并提出了一种与延迟无关的控制器，以实现概率有限时间稳定性。通过两个示例证明了结果的有效性。

引用次数: 0

Adaptive control of reaction–diffusion PDEs via neural operator-approximated gain kernels 通过神经算子近似增益核对反应扩散 PDE 进行自适应控制

IF 2.1 3区计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS

Systems & Control Letters

Pub Date : 2024-11-22 DOI: 10.1016/j.sysconle.2024.105968

Luke Bhan , Yuanyuan Shi , Miroslav Krstic

Neural operator approximations of the gain kernels in PDE backstepping has emerged as a viable method for implementing controllers in real time. With such an approach, one approximates the gain kernel, which maps the plant coefficient into the solution of a PDE, with a neural operator. It is in adaptive control that the benefit of the neural operator is realized, as the kernel PDE solution needs to be computed online, for every updated estimate of the plant coefficient. We extend the neural operator methodology from adaptive control of a hyperbolic PDE to adaptive control of a benchmark parabolic PDE (a reaction–diffusion equation with a spatially-varying and unknown reaction coefficient). We prove global stability and asymptotic regulation of the plant state for a Lyapunov design of parameter adaptation. The key technical challenge of the result is handling the

2 D

nature of the gain kernels and proving that the target system with two distinct sources of perturbation terms, due to the parameter estimation error and due to the neural approximation error, is Lyapunov stable. To verify our theoretical result, we present simulations achieving calculation speedups up to

45 \times

relative to the traditional finite difference solvers for every timestep in the simulation trajectory.

神经算子近似 PDE 反步法中的增益核，已成为实时执行控制器的一种可行方法。利用这种方法，可以用神经算子近似将工厂系数映射为 PDE 解的增益核。在自适应控制中，神经算子的优势才得以体现，因为每更新一次工厂系数估计值，都需要在线计算 PDE 内核解。我们将神经算子方法从双曲型 PDE 的自适应控制扩展到基准抛物型 PDE 的自适应控制（具有空间变化和未知反应系数的反应扩散方程）。我们证明了参数适应的 Lyapunov 设计的全局稳定性和植物状态的渐近调节。该结果的关键技术挑战在于处理增益核的二维性质，并证明具有两个不同扰动项来源（参数估计误差和神经逼近误差）的目标系统是 Lyapunov 稳定的。为了验证我们的理论结果，我们进行了仿真，在仿真轨迹的每个时间步中，计算速度比传统的有限差分求解器提高了 45 倍。

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引用次数: 0

Finite-time output consensus control of nonlinear uncertain multi-agent systems via extended state observer 通过扩展状态观测器实现非线性不确定多代理系统的有限时间输出共识控制

IF 2.1 3区计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS

Systems & Control Letters

Pub Date : 2024-11-18 DOI: 10.1016/j.sysconle.2024.105967

Xixi Shen , Jiangping Hu , Wenchao Xue , Bin Meng

This paper investigates the finite-time consensus problem for nonlinear uncertain multi-agent systems (MASs) affected by mismatched uncertainties and disturbances, as well as partial measurements. An active disturbance rejection control (ADRC) strategy that combines the backstepping technique with an extended state observer is proposed. Firstly, a finite-time state feedback controller is designed to ensure consensus when ignoring external disturbances. Secondly, a finite-time extended state observer (FTESO) is proposed for each agent to estimate the unavailable state and external disturbances, and a feedforward-feedback composite consensus controller is then developed. Furthermore, utilizing the homogeneous domination approach, we demonstrate that the proposed composite control strategy guarantees finite-time output consensus. Finally, the effectiveness of the proposed composite control strategy is illustrated using a multiple-manipulator system as an example.

本文研究了受不匹配不确定性和干扰以及部分测量影响的非线性不确定多代理系统（MAS）的有限时间共识问题。本文提出了一种结合了反向步进技术和扩展状态观测器的主动干扰抑制控制（ADRC）策略。首先，设计了一个有限时间状态反馈控制器，以确保在忽略外部干扰时达成一致。其次，为每个代理提出了一个有限时间扩展状态观测器（FTESO）来估计不可用状态和外部干扰，然后开发了一个前馈-反馈复合共识控制器。此外，我们还利用同质支配方法证明了所提出的复合控制策略能保证有限时间输出共识。最后，我们以一个多操纵器系统为例，说明了所提出的复合控制策略的有效性。

引用次数: 0

A timestamp-based Nesterov’s accelerated projected gradient method for distributed Nash equilibrium seeking in monotone games 基于时间戳的涅斯捷罗夫加速投影梯度法，用于单调博弈中的分布式纳什均衡寻求

IF 2.1 3区计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS

Systems & Control Letters

Pub Date : 2024-11-15 DOI: 10.1016/j.sysconle.2024.105966

Nian Liu , Shaolin Tan , Ye Tao , Jinhu Lü

In this paper, a timestamp-based Nesterov’s accelerated gradient algorithm is proposed for Nash equilibrium seeking over communication networks for strongly monotone games. Its difference from the well-known consensus-based Nash equilibrium seeking method is that each player’s local estimates of players’ actions is updated by both Nesterov’s accelerated gradient method and timestamp-based broadcasting protocol. We prove its convergence to the

ϵ

-approximation Nash equilibrium with the fixed step-size. Simulation results are given to demonstrate the outperformance of the proposed algorithm over some well-known projected gradient approaches. It is shown that the required number of iterations to reach the Nash equilibrium is greatly reduced in our proposed algorithm.

本文提出了一种基于时间戳的涅斯捷罗夫加速梯度算法，用于通过通信网络寻求强单调博弈的纳什均衡。它与众所周知的基于共识的纳什均衡寻求方法的区别在于，每个博弈方对博弈方行动的局部估计都是通过内斯特洛夫加速梯度法和基于时间戳的广播协议更新的。我们证明了该方法在步长固定的情况下对ϵ-近似纳什均衡的收敛性。仿真结果表明，所提算法的性能优于一些著名的投影梯度方法。结果表明，我们提出的算法大大减少了达到纳什均衡所需的迭代次数。

引用次数: 0

From data to reduced-order models via moment matching 通过矩匹配从数据到降阶模型

IF 2.1 3区计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS

Systems & Control Letters

Pub Date : 2024-11-11 DOI: 10.1016/j.sysconle.2024.105965

Azka M. Burohman , Bart Besselink , Jacquelien M.A. Scherpen , M. Kanat Camlibel

A new method for data-driven interpolatory model reduction for discrete-time systems is presented in this paper. Using the so-called data informativity perspective, we define a framework that enables the computation of moments at given (possibly complex) interpolation points based on time-domain input–output data only, without explicitly identifying the high-order system. Instead, by characterizing the set of all systems explaining the data, necessary and sufficient conditions are provided under which all systems in this set share the same moment at a given interpolation point. Moreover, these conditions allow for explicitly computing these moments. Reduced-order models are then derived by employing a variation of the classical rational interpolation method. The condition to enforce moment matching model reduction with prescribed poles is also discussed as a means to obtain stable reduced-order models. An example of an electrical circuit illustrates this framework.

本文介绍了一种用于离散时间系统的数据驱动插值模型还原的新方法。利用所谓的数据信息性视角，我们定义了一个框架，使我们能够仅根据时域输入输出数据计算给定（可能复杂）插值点的矩，而无需明确识别高阶系统。相反，通过描述解释数据的所有系统的集合，提供了必要条件和充分条件，在这些条件下，该集合中的所有系统在给定插值点共享相同的时刻。此外，这些条件允许明确计算这些时刻。然后，通过采用经典的有理插值法的变体，推导出减阶模型。此外，还讨论了用规定极点强制矩匹配模型还原的条件，以此获得稳定的还原阶模型。一个电路实例说明了这一框架。

引用次数: 0

Smooth adaptive finite-time tracking for uncertain time-varying systems 不确定时变系统的平滑自适应有限时间跟踪

IF 2.1 3区计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS

Systems & Control Letters

Pub Date : 2024-11-09 DOI: 10.1016/j.sysconle.2024.105963

Guoqing Liu , Kaiwen Chen , Yang-Yang Chen

This paper addresses the adaptive finite-time tracking control problem of strict-feedback nonlinear systems, where the control coefficient and the model parameters are time-varying and unknown. Based on the so-called congelation of variables method, a novel fractional-power adaptive update law is designed to achieve finite-time practical tracking in the presence of unknown time-varying coefficient/parameters. The virtual and actual control inputs of the proposed finite-time controller are designed in a smooth sign-function-like form complemented by a smooth sign-function-like filter, which allows for circumventing the singularity issues and the chattering phenomenon caused by non-smooth terms in classical finite-time controllers and filters. The tracking error proves to be bounded and converges to a desired compact set in finite time. Simulations of two practical examples are presented and show the effectiveness of the proposed algorithm.

本文探讨了严格反馈非线性系统的自适应有限时间跟踪控制问题，其中控制系数和模型参数都是时变和未知的。基于所谓的变量同化方法，设计了一种新颖的分数功率自适应更新律，以在存在未知时变系数/参数的情况下实现有限时间实际跟踪。所提出的有限时间控制器的虚拟和实际控制输入被设计成平滑的类符号函数形式，并辅以平滑的类符号函数滤波器，从而避免了经典有限时间控制器和滤波器中的非平滑项引起的奇异性问题和颤振现象。事实证明，跟踪误差是有界的，并能在有限时间内收敛到所需的紧凑集。本文介绍了两个实际例子的仿真，显示了所提算法的有效性。

引用次数: 0

Iteration governor for suboptimal MPC with input constraints 具有输入约束条件的次优 MPC 的迭代调节器

IF 2.1 3区计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS

Systems & Control Letters

Pub Date : 2024-11-08 DOI: 10.1016/j.sysconle.2024.105962

Jordan Leung, Ilya Kolmanovsky

This paper introduces a supervisory scheme, called the iteration governor (IG), that augments a suboptimal input-constrained MPC policy by performing online selection of the reference command and the number of optimization iterations used to generate a control input. At each time step, an auxiliary reference command is selected so that the state is contained in a region of attraction (ROA) for a corresponding auxiliary equilibrium under optimal MPC. Simultaneously, the number of optimization iterations used to generate the control input is preselected to ensure that the resulting suboptimal input steers the state towards this auxiliary equilibrium. Theoretical guarantees are provided that ensure the auxiliary reference converges to the target reference in finite-time, the state converges to the target equilibrium, and the number of online iterations never exceeds a constant that can be computed offline.

本文介绍了一种称为迭代治理器（IG）的监督方案，它通过在线选择参考指令和用于生成控制输入的优化迭代次数来增强次优输入受限 MPC 策略。在每个时间步长内，选择辅助参考指令，使状态包含在最优 MPC 下相应辅助平衡的吸引区域 (ROA) 内。同时，预选用于生成控制输入的优化迭代次数，以确保所生成的次优输入能将状态导向该辅助平衡。理论保证可确保辅助参考在有限时间内收敛到目标参考，状态收敛到目标平衡，并且在线迭代次数永远不会超过可离线计算的常数。

引用次数: 0

Finite-time annular domain H2/H∞ filtering for mean-field stochastic systems with Wiener and Poisson noises 具有维纳和泊松噪声的均值场随机系统的有限时间环域 H2/H∞ 滤波

IF 2.1 3区计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS

Systems & Control Letters

Pub Date : 2024-11-08 DOI: 10.1016/j.sysconle.2024.105959

Zhiguo Yan , Zhengxiang Pan , Guolin Hu

This paper investigates the finite-time annular domain

H_{2} / H_{\infty}

filtering for mean-field stochastic systems with external disturbance, Wiener and Poisson noises. Initially, the novel concept of finite-time annular domain (FTAD)

H_{2} / H_{\infty}

filtering is introduced, which ensures the system’s mean square finite-time annular domain boundedness (MSFTADB) and minimizes the

H_{2}

and

H_{\infty}

filtering performance indices. Next, using the Itô-Levy formula and the reverse differential Gronwall inequality, a less conservative sufficient condition for the existence of finite-time annular domain

H_{2} / H_{\infty}

filter is derived. Furthermore, a new algorithm is devised to establish the relationship between the ranges of adjustable parameters and the minimum value of

H_{2}

performance index. Finally, a practical example is provided to verify the effectiveness of the proposed method.

本文研究了具有外部干扰、维纳和泊松噪声的均方场随机系统的有限时间环域 H2/H∞ 滤波。首先，引入了有限时间环域（FTAD）H2/H∞滤波的新概念，确保了系统的均方有限时间环域有界性（MSFTADB），并使 H2 和 H∞ 滤波性能指标最小化。接下来，利用 Itô-Levy 公式和反向微分 Gronwall 不等式，推导出了一个不太保守的有限时间环域 H2/H∞ 滤波器存在的充分条件。此外，还设计了一种新算法来确定可调参数范围与 H2 性能指标最小值之间的关系。最后，提供了一个实际例子来验证所提方法的有效性。

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引用次数: 0

A continuous-time fundamental lemma and its application in data-driven optimal control 连续时间基本定理及其在数据驱动最优控制中的应用

IF 2.1 3区计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS

Systems & Control Letters

Pub Date : 2024-10-30 DOI: 10.1016/j.sysconle.2024.105950

Philipp Schmitz , Timm Faulwasser , Paolo Rapisarda , Karl Worthmann

Data-driven control of discrete-time and continuous-time systems is of tremendous research interest. In this paper, we explore data-driven optimal control of continuous-time linear systems using input–output data. Based on a density result, we rigorously derive error bounds for finite-order polynomial approximations of elements of the system behavior. To this end, we leverage a link between latent variables and flat outputs of controllable systems. Combined with a continuous-time counterpart of Willems et al.’s fundamental lemma, we characterize the suboptimality resulting from polynomial approximations in data-driven linear–quadratic optimal control. Finally, we draw upon a numerical example to illustrate our results.

离散时间和连续时间系统的数据驱动控制是一项极具研究价值的课题。在本文中，我们利用输入输出数据探索连续时间线性系统的数据驱动最优控制。基于密度结果，我们严格推导出了系统行为元素的有限阶多项式近似误差边界。为此，我们利用了可控系统的潜变量和平面输出之间的联系。结合 Willems 等人的连续时间对应基本定理，我们描述了数据驱动的线性-二次方最优控制中多项式近似产生的次最优性。最后，我们利用一个数值示例来说明我们的结果。

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全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

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全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

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Systems & Control Letters

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