Systems & Control Letters最新文献

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Aperiodic sampled-data-based control for switched linear systems: An improved sampling-dependent event-triggered mechanism 基于非周期性采样数据的开关线性系统控制：一种改进的依赖采样的事件触发机制

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

Systems & Control Letters

Pub Date : 2025-02-01 DOI: 10.1016/j.sysconle.2024.105990

Lijun Gao, Suo Yang

This paper is contributing to designing a novel event-triggered control (ETC) policy for switched linear systems, where control systems obtain sampling information only at sampling instants. First, by allowing the length of any sampling interval to exceed the minimum DT of all system modes, an innovative aperiodic sampling programme is presented to avoid the high-frequency sampling. Then, based on the proposed aperiodic sampling method, three improvements are presented: (1) a novel aperiodic sampled-data-based event-triggered mechanism (ASETM) is developed, which is more flexible in scheduling communication resources than periodic sampled-data-based event-triggered mechanism (PSETM); (2) a multiple discontinuous Lyapunov function (MDLF) with adjustable sampling-dependent parameters is constructed, which covers the multiple Lyapunov function (MLF) as a special case and further increases the design flexibility; (3) the state-feedback controller gains and event-triggering parameters are sampling-dependent, which broadens the feasible solution range of matrix inequalities. It is shown that by choosing an appropriate aperiodic sampling intervals sequence and sampling-dependent parameters, a tighter bound on the mode-dependent average dwell time (MDADT) and larger sampling intervals can be achieved. Finally, an example is adopted to illustrate the effectiveness of the proposed approach.

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引用次数: 0

Optimal control problem with nonregular mixed constraints via penalty functions

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

Systems & Control Letters

Pub Date : 2025-02-01 DOI: 10.1016/j.sysconle.2024.106010

M.d.R. de Pinho , M. Margarida A. Ferreira , Georgi Smirnov

Below we deduce necessary conditions of optimality for problems with nonregular mixed constraints (see Dmitruk(2009), Dmitruk and Osmolovskii(2022)) using the method of penalty functions similar to the one we previously used to solve optimization problems for control sweeping processes (see, e.g., de Pinho et al. (2022)), with pure state constraints de Pinho et al.,2024 and with regular mixed constraints (de Pinho et al.,2024).

We intentionally consider a global minimum and the simplest boundary conditions.

下面，我们将使用惩罚函数方法，推导出具有非规则混合约束（见 Dmitruk(2009)、Dmitruk 和 Osmolovskii(2022)）问题的最优性必要条件，该方法类似于我们之前用于解决控制扫频过程优化问题的方法（见 de Pinho 等人(2022)、具有纯状态约束的 de Pinho 等人(2024)和具有规则混合约束的 de Pinho 等人(2024)、我们有意考虑全局最小值和最简单的边界条件。

引用次数: 0

Recursive identification of nonlinear nonparametric systems under event-triggered observations

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

Systems & Control Letters

Pub Date : 2025-02-01 DOI: 10.1016/j.sysconle.2024.106013

Xiaotao Ren , Wenxiao Zhao , Han Zhang

In the paper, recursive identification of the nonlinear nonparametric system is considered, where measurements for identification are subject to an event-triggered scheme and the system itself is of a finite impulse response (FIR) type. First, an adaptive event detector is designed and the measurements for identification are transmitted depending whether the value of the detector is 1 or 0. Second, a recursive identification algorithm is proposed with the help of a kernel-based stochastic approximation algorithm with expanding truncations (SAAWET). Third, under some reasonable assumptions, the estimates are proved to be strongly consistent, i.e., converging almost surely to the values of the unknown function in the system at any fixed points, and the transmission rate of the detector is analyzed as well. Finally, numerical examples are given to justify the theoretical results.

本文考虑了非线性非参数系统的递归识别问题，其中识别测量采用事件触发方案，系统本身为有限脉冲响应（FIR）类型。首先，设计了一个自适应事件检测器，并根据检测器的值是 1 还是 0 来传输用于识别的测量结果。其次，在基于核的随机逼近算法和扩展截断算法（SAAWET）的帮助下，提出了一种递归识别算法。第三，在一些合理的假设条件下，证明了估计值具有很强的一致性，即在任意固定点几乎肯定收敛于系统中未知函数的值，并分析了检测器的传输率。最后，还给出了数值示例来证明理论结果的正确性。

引用次数: 0

Distributed state estimation for interdependent and switching multi-agent systems 相互依存和切换多代理系统的分布式状态估计

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

Systems & Control Letters

Pub Date : 2025-02-01 DOI: 10.1016/j.sysconle.2024.105984

Camilla Fioravanti , Andrea Gasparri , Stefano Panzieri , Gabriele Oliva

This paper addresses the problem of multi-agent distributed state estimation in switching networks over directed graphs. Specifically, we consider a novel estimation setting for a linear continuous-time system that is broken down into subsystems, each of which is locally estimated by the corresponding agent. This task is undertaken despite the complexities due to interdependencies on both cyber and physical levels, and due to the fact that the system is switching, i.e., the different subsystems/agents can activate (e.g., to accomplish some specific task) or deactivate (e.g., due to a fault) during a transient that ends with a cutoff time, unknown to the agents, after which the topology becomes fixed. In particular, by exploiting the negativizability property – the pair

(A, C)

is negativizable if there is a feedback gain

K

such that

A - K C

is negative definite – each agent is able to locally perform the calculation of its own estimation gain matrix. The paper is complemented by the convergence analysis of the estimation error executed by leveraging on nonsmooth analysis and simulations to prove the effectiveness of the proposed results.

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引用次数: 0

Minimal finite-time observability of Markovian jump Boolean networks

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

Systems & Control Letters

Pub Date : 2025-02-01 DOI: 10.1016/j.sysconle.2024.106007

Lina Wang , Zicong Xia , Yang Liu , Shun-ichi Azuma , Weihua Gui

In this paper, the finite-time observability and minimal finite-time observability problems of Markovian jump Boolean networks (MJBNs) are addressed. The signal space is partitioned to facilitate the observability analysis, followed by novel criteria for the finite-time observability of MJBNs. To reduce measurement costs, a minimal finite-time observability problem is formulated, involving the injection of the minimum number of sensors necessary for an unobservable MJBN to achieve finite-time observability. By introducing an indicator matrix, the minimal finite-time observability problem is converted into a 0–1 programming problem, and a collaborative neurodynamic optimization approach with multiple recurrent neural networks is developed for obtaining a global optimal solution. Two illustrative examples, including a biological simulation, are provided to demonstrate the theoretical results.

引用次数: 0

Event-dependent intermittent synchronization of complex networks based on discrete-time state observation

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

Systems & Control Letters

Pub Date : 2025-01-30 DOI: 10.1016/j.sysconle.2025.106025

Zelin Yang, Jian-An Wang, Jie Zhang, Mingjie Li, Hui Shi

This paper studies the synchronization issue of complex networks via event-dependent intermittent discrete-time observation control (EIDOC) for the first time. Three non-negative real domains are characterized by introducing two boundary functions. The work and rest time of intermittent control rely on the relationship between the Lyapunov function trajectory and non-negative regions. The proposed aperiodically intermittent control is based on discrete-time state observation rather than continuous observation during the work interval. Some sufficient criteria are derived for ensuring synchronization of the network. The theoretical results are employed to deal with single pendulum systems, and numerical simulation have demonstrated the effectiveness of the derived method.

引用次数: 0

Corrigendum to “Remarks on input to state stability of perturbed gradient flows, motivated by model-free feedback control learning” [Syst. Control Lett. 161 (2022) 105138] “由无模型反馈控制学习驱动的扰动梯度流状态稳定性的输入注释”的勘误表[系统]。控制通讯。161 (2022)105138]

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

Systems & Control Letters

Pub Date : 2024-12-01 DOI: 10.1016/j.sysconle.2024.105952

Eduardo D. Sontag

引用次数: 0

Corrigendum to “Compensation of spatially-varying state delay for a first-order hyperbolic PIDE using boundary control” [Syst. Control Lett. 157 (2021) 105050] “用边界控制补偿一阶双曲PIDE的空间变化状态延迟”的勘误表[系统]。管制通告157 (2021)105050]

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

Systems & Control Letters

Pub Date : 2024-12-01 DOI: 10.1016/j.sysconle.2024.105964

Jing Zhang , Jie Qi

引用次数: 0

Exponential stabilizability and observability at the target imply semiglobal exponential stabilizability by templated output feedback 目标的指数稳定性和可观测性暗示了模板输出反馈的半全局指数稳定性

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

Systems & Control Letters

Pub Date : 2024-11-30 DOI: 10.1016/j.sysconle.2024.105971

Vincent Andrieu , Lucas Brivadis , Jean-Paul Gauthier , Ludovic Sacchelli , Ulysse Serres

For nonlinear analytic control systems, we introduce a new paradigm for dynamic output feedback stabilization. We propose to periodically sample the usual observer based control law, and to reshape it so that it coincides with a “control template” on each time period. By choosing a control template making the system observable, we prove that this method allows to bypass the uniform observability assumption that is used in most nonlinear separation principles. We prove the genericity of control templates by adapting a universality theorem of Sussmann.

对于非线性分析控制系统，我们引入了一种新的动态输出反馈镇定范式。我们建议对通常的基于观测器的控制律进行周期性采样，并对其进行重塑，使其在每个时间段与“控制模板”一致。通过选择一个使系统可观察的控制模板，我们证明了该方法可以绕过大多数非线性分离原理中使用的均匀可观察性假设。利用Sussmann的通用性定理证明了控制模板的通用性。

引用次数: 0

Data-driven control of echo state-based recurrent neural networks with robust stability guarantees 具有鲁棒稳定性保证的基于回波状态的递归神经网络数据驱动控制

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

Systems & Control Letters

Pub Date : 2024-11-29 DOI: 10.1016/j.sysconle.2024.105974

William D’Amico, Alessio La Bella, Marcello Farina

In this work we propose a new data-based approach for robust controller design for a rather general class of recurrent neural networks affected by bounded measurement noise. We first identify the model set compatible with available data in a selected model class via set membership (SM). Then, incremental input-to-state stability and desired performances for the closed loop system are enforced robustly to all models in the identified model set via a linear matrix inequality (LMI) optimization problem. Numerical results show the effectiveness of the comprehensive method.

在这项工作中，我们提出了一种新的基于数据的鲁棒控制器设计方法，用于受有界测量噪声影响的相当一般的递归神经网络。我们首先通过集合隶属度（SM）确定与选定模型类中可用数据兼容的模型集。然后，通过线性矩阵不等式（LMI）优化问题，将闭环系统的增量输入状态稳定性和期望性能鲁棒地强制到已识别模型集中的所有模型上。数值结果表明了该综合方法的有效性。

引用次数: 0

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