Automatica最新文献

英文中文

Randomized average consensus based on additive privacy sharing 基于加性隐私共享的随机平均共识

IF 5.9 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Automatica

Pub Date : 2026-02-04 DOI: 10.1016/j.automatica.2026.112847

Dongyu Li , Shanyao Ren , Hanzhou Wang , Jianwei Liu , Shuzhi Sam Ge

Distributed average consensus plays a crucial role in multi-agent systems. In data-sensitive applications, agents need to exchange state without disclosing true privacy. To address this issue, homomorphic encryption and random perturbations-based schemes are commonly adopted privacy-preserving approaches. However, homomorphic encryption is typically limited to scenarios where agents’ state values are non-negative integers with substantial computational overhead. On the other hand, random perturbation-based schemes often require prior knowledge of the total number of agents, rendering them ineffective in dynamic environments or vulnerable against external eavesdroppers. Motivated by this, we propose an additive secret-sharing method based on multiplication operations to achieve consensus among agents. Specifically, we first introduce random perturbations and exponentiation to true states. Based on this, each agent’s true state is decomposed into secret shares, which are then transmitted over public channels. We design the scheme to enable fundamental operations to be executed in a distributed manner, thereby facilitating distributed average consensus. This solution resists attacks from both honest-but-curious and global eavesdropping agents, under the condition that each node is connected to at least one trusted node. In comparison with differential privacy solutions, our approach achieves consensus by an exact state value. Furthermore, it has a lighter resource consumption and broader applicability than homomorphic encryption schemes. Simulation results show the feasibility and security of our approach.

分布式平均共识在多智能体系统中起着至关重要的作用。在数据敏感的应用程序中，代理需要在不泄露真正隐私的情况下交换状态。为了解决这个问题，通常采用同态加密和基于随机扰动的方案来保护隐私。然而，同态加密通常仅限于代理的状态值是非负整数且具有大量计算开销的场景。另一方面，基于随机扰动的方案通常需要事先知道代理的总数，这使得它们在动态环境中无效，或者容易受到外部窃听者的攻击。为此，我们提出了一种基于乘法运算的加性秘密共享方法，以实现agent间的共识。具体地说，我们首先将随机扰动和指数引入真态。在此基础上，每个代理的真实状态被分解成秘密共享，然后通过公共通道传输。我们设计的方案使基本操作能够以分布式方式执行，从而促进分布式平均共识。在每个节点至少连接到一个可信节点的条件下，该解决方案可以抵抗来自诚实但好奇和全局窃听代理的攻击。与差分隐私解决方案相比，我们的方法通过精确的状态值实现共识。此外，它比同态加密方案具有更少的资源消耗和更广泛的适用性。仿真结果表明了该方法的可行性和安全性。

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引用次数: 0

Differentially private projected gradient tracking for distributed constrained optimization 分布式约束优化的差分私有投影梯度跟踪

IF 5.9 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Automatica

Pub Date : 2026-02-04 DOI: 10.1016/j.automatica.2026.112851

Zhen Yang , Wangli He , Guanrong Chen

This paper investigates a distributed constrained optimization problem with privacy concerns over a multi-agent network, where each agent holds a private objective function and seeks a global optimizer subject to a global closed convex set of constraints in a distributed and privacy-preserving manner. To address this problem, a differentially private projected gradient tracking algorithm is proposed. The main idea is to introduce indirect projection in gradient tracking to handle the global constraints and to decompose the gradient tracking state into two sub-states, with the shared sub-state being perturbed by decaying Laplace noise, to establish differential privacy (DP). Two time scales and a lazy update rule are employed to facilitate the convergence analysis. It is demonstrated that the proposed algorithm simultaneously preserves linear convergence rates and

ϵ

-DP without requiring bounded gradients. Finally, numerical simulations are presented to verify the theoretical results.

本文研究了一个考虑隐私的多智能体网络的分布式约束优化问题，其中每个智能体拥有一个私有目标函数，并以分布式和隐私保护的方式寻求全局优化器，该优化器受全局封闭凸集约束。为了解决这一问题，提出了一种差分私有投影梯度跟踪算法。其主要思想是在梯度跟踪中引入间接投影来处理全局约束，并将梯度跟踪状态分解为两个子状态，共享子状态被衰减拉普拉斯噪声扰动，以建立差分隐私（DP）。为了便于收敛分析，采用了两个时间尺度和一个延迟更新规则。结果表明，该算法不需要有界梯度，同时保持了线性收敛率和ϵ-DP。最后，通过数值模拟验证了理论结果。

引用次数: 0

Varying horizon learning economic MPC with unknown costs of disturbed nonlinear systems 扰动非线性系统的未知成本变视界学习经济MPC

IF 5.9 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Automatica

Pub Date : 2026-02-03 DOI: 10.1016/j.automatica.2026.112856

Weiliang Xiong , Defeng He , Haiping Du , Jianbin Mu

This paper proposes a novel varying horizon economic model predictive control (EMPC) scheme without terminal state constraints for constrained nonlinear systems with additive disturbances and unknown economic costs. The general regression learning framework with mixed kernels is first used to reconstruct the unknown cost. Then an online iterative procedure is developed to adjust the horizon adaptively. Again, an elegant horizon-dependent contraction constraint is designed to ensure the convergence of the closed-loop system to a neighborhood of the desired steady state. Moreover, sufficient conditions ensuring recursive feasibility and input-to-state stability are established for the system in closed-loop with the EMPC. The merits of the proposed scheme are verified by the simulations of a continuous stirred tank reactor and a four-tank system in terms of robustness, economic performance and online computational burden.

针对具有加性扰动和未知经济成本的非线性约束系统，提出了一种无终端状态约束的变视界经济模型预测控制方案。首先采用混合核回归学习框架对未知代价进行重构。在此基础上，提出了一种自适应调整视界的在线迭代方法。再次，设计了一个优雅的依赖于水平的收缩约束，以确保闭环系统收敛到理想稳态的邻域。同时，建立了系统在闭环状态下保证递归可行性和输入状态稳定的充分条件。通过连续搅拌槽式反应器和四槽式系统的仿真，验证了该方案的鲁棒性、经济性和在线计算量。

引用次数: 0

Designated-time fault-tolerant stabilization for planar nonlinear systems with unknown time-varying powers and deferred constraints 具有未知时变功率和延迟约束的平面非线性系统的指定时间容错镇定

IF 5.9 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Automatica

Pub Date : 2026-02-03 DOI: 10.1016/j.automatica.2026.112852

Zong-Yao Sun , Shiji Ren , Zhuo Wang , Chih-Chiang Chen

This paper investigates the stabilization for a class of uncertain planar nonlinear systems with unknown time-varying powers and deferred output constraints. The innovation lies in removing the condition on the relative magnitudes of unknown time-varying powers and providing a unified scheme which ensures that the system state enters an adjustable neighborhood of the origin within an arbitrarily designated time instant and ultimately converges to the origin. The effectiveness of our strategy is demonstrated via the stabilization of the dynamical model of a boiler-turbine unit.

研究了一类具有未知时变功率和延迟输出约束的不确定平面非线性系统的镇定问题。其创新之处在于消除了未知时变功率相对大小的条件，提供了一种统一的方案，保证系统状态在任意指定的时间瞬间进入原点的可调邻域，并最终收敛到原点。通过对锅炉汽轮机组动力学模型的稳定化验证了该策略的有效性。

引用次数: 0

Comments on “Innovative non-asymptotic and robust estimation method using auxiliary modulating dynamical systems” [Automatica 152 (2023) 110953] 关于“基于辅助调制动力系统的创新非渐近鲁棒估计方法”的评论[自动化]152 (2023)110953]

IF 5.9 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Automatica

Pub Date : 2026-02-03 DOI: 10.1016/j.automatica.2026.112846

Matti Noack , Davi Goncalves Accioli , Johann Reger , Jerome Jouffroy

In the paper “Innovative non-asymptotic and robust estimation method using auxiliary modulating dynamical systems” by J. Liu et al., the authors discuss state estimation for singular systems using the modulating function method, incorporating auxiliary systems for kernel calculation. This note provides additional context for their work by highlighting that the use of auxiliary systems within the modulating function framework has already been explored in earlier contributions.

在J. Liu等人的论文《利用辅助调制动力系统的创新非渐近鲁棒估计方法》中，作者利用调制函数方法讨论了奇异系统的状态估计，并引入辅助系统进行核计算。本笔记通过强调在调制函数框架内使用辅助系统已经在早期的文章中进行了探索，为他们的工作提供了额外的背景。

引用次数: 0

Guaranteed bounds on the H2 performance of uncertain linear systems 不确定线性系统H2性能的保证界

IF 5.9 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Automatica

Pub Date : 2026-02-02 DOI: 10.1016/j.automatica.2026.112853

Tommaso Casati , Clément Roos , Jean-Marc Biannic , Hélène Evain

The

H_{2}

norm is a fundamental metric in many control applications, and it is important to assess how this norm varies in the presence of model uncertainties. This paper proposes sufficient conditions to compute guaranteed lower and upper bounds on the

H_{2}

performance of uncertain linear systems. The proposed approach is particularly interesting as it can be applied to both deterministic and probabilistic evaluation of the

H_{2}

norm on continuous or discrete-time models. The main idea to compute guaranteed

H_{2}

-norm bounds consists in solving a SemiDefinite Program characterized by Linear Matrix Inequalities at each point of a frequency grid. A Hamiltonian-based technique is then adopted to validate the results on a continuous frequency range. The method initially developed for deterministic

H_{2}

analysis is then integrated into a Branch and Bound scheme to compute hard bounds on the probability that the

H_{2}

performance of an uncertain system is either satisfied or violated. The developed algorithms are eventually applied to test cases of increasing complexity.

H2规范是许多控制应用中的基本指标，在模型不确定性存在的情况下，评估该规范如何变化是很重要的。本文给出了计算不确定线性系统H2性能保证下界和上界的充分条件。所提出的方法特别有趣，因为它可以应用于连续或离散时间模型上H2范数的确定性和概率评估。计算保证h2 -范数边界的主要思想是在频率网格的每个点上求解一个以线性矩阵不等式为特征的半定规划。然后采用基于哈密顿的技术在连续频率范围内验证结果。将最初用于确定性H2分析的方法集成到分支定界方案中，以计算不确定系统满足或违反H2性能的概率的硬界。所开发的算法最终应用于越来越复杂的测试用例。

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引用次数: 0

Sign-perturbed sums method for multivariate ARX systems 多元ARX系统的符号摄动和方法

IF 5.9 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Automatica

Pub Date : 2026-02-02 DOI: 10.1016/j.automatica.2026.112848

Masanori Oshima , Sanghong Kim , Yuri A.W. Shardt , Ken-Ichiro Sotowa

Assessing the accuracy of the dynamic model obtained using system identification is important before using it in a model-based control system. In practical situations, only finite-sample data is available to assess model accuracy, that is, it is not guaranteed that asymptotic theory, which assumes infinite-sample data, precisely assesses the model accuracy. The sign-perturbed sums (SPS) method can exactly assess the model accuracy using finite-sample, input–output data. The SPS method calculates the confidence region of the model parameters using the multiple data sets that are generated by randomly perturbing the signs of the noise innovations. This paper proposes an extended SPS method that can handle both open-loop and closed-loop multivariate systems with an autoregressive exogenous input (ARX) structure. Moreover, it is mathematically proved that the extension of the SPS method preserves the exactness of the confidence region. As well, the features of the SPS confidence region, such as star convexity and boundedness, are theoretically discussed for the case where the regressor is uncorrelated with the noise innovations. Finally, a numerical example is considered to show other features of the SPS confidence region, such as the degree of losing the exactness in the presence of violated assumptions and the change of the boundary as a function of the number of samples.

在将系统辨识得到的动态模型应用于基于模型的控制系统之前，对其准确性进行评估是非常重要的。在实际情况中，只有有限样本的数据可以用来评估模型的精度，也就是说，不能保证假设无限样本数据的渐近理论能够精确地评估模型的精度。符号摄动和（SPS）方法可以在有限样本的输入输出数据中准确地评估模型的精度。该方法利用随机扰动噪声创新符号产生的多个数据集计算模型参数的置信区域。本文提出了一种扩展的SPS方法，该方法可以处理具有自回归外源输入（ARX）结构的开环和闭环多变量系统。此外，从数学上证明了该方法的扩展保留了置信区域的准确性。同时，从理论上讨论了回归量与噪声创新不相关情况下SPS置信区域的星形凸性和有界性等特征。最后，考虑了一个数值例子来显示SPS置信区域的其他特征，例如在违反假设的情况下失去准确性的程度以及作为样本数量的函数的边界变化。

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引用次数: 0

The most powerful unfalsified linear parameter-varying model 最强大的非证伪线性参数变模型

IF 5.9 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Automatica

Pub Date : 2026-02-02 DOI: 10.1016/j.automatica.2026.112855

Ivan Markovsky , Chris Verhoek , Roland Tóth

The most powerful unfalsified model (MPUM), i.e., the least complex exact model for the given data, is well established for linear time-invariant (LTI) systems. It has not been generalized for linear parameter-varying (LPV) systems. In order to do this, we define the notions of complexity for LPV systems with shifted-affine scheduling dependence. The MPUM leads to identifiability conditions and a method for exact LPV system identification. The method is based on lifting the LPV system to a higher dimensional space and LTI embedding in the lifted space. It is made rigorous by proving a formal connection between the parameters of the LTI embedding and the original LPV system.

最强大的未证伪模型（MPUM），即给定数据的最不复杂的精确模型，已经很好地建立了线性时不变（LTI）系统。它还没有推广到线性变参（LPV）系统。为了做到这一点，我们定义了具有移位仿射调度依赖的LPV系统的复杂性概念。MPUM给出了LPV系统的可识别性条件和精确识别方法。该方法基于将LPV系统提升到更高的维度空间，并在提升的空间中嵌入LTI。通过证明LTI嵌入参数与原始LPV系统参数之间的形式化联系，使其更加严格。

引用次数: 0

On dissipativity of cross-entropy loss in training ResNets — A turnpike towards architecture search 训练ResNets中交叉熵损失的耗散性——结构搜索的收费公路

IF 5.9 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Automatica

Pub Date : 2026-01-27 DOI: 10.1016/j.automatica.2025.112767

Jens Püttschneider , Timm Faulwasser

The training of ResNets and neural ODEs can be formulated and analyzed from the perspective of optimal control. This paper proposes a dissipative formulation of the training of ResNets and neural ODEs for classification problems. Specifically, we consider a variant of the cross-entropy (label smoothing) as a loss function and as a regularization in the stage cost. Based on our dissipative formulation of the training, we prove that the training OCPs for ResNets and neural ODEs alike exhibit the turnpike phenomenon. We illustrate this finding with numerical results for the two spirals and MNIST datasets. Crucially, our training formulation ensures that the transformation of the data from input to output is achieved in the first layers. In the following layers, which constitute the turnpike, the data remains at an equilibrium state and therefore these layers do not contribute to the transformation learned. In principle, these layers can be pruned after training, resulting in a network with only the necessary number of layers thus simplifying tuning of hyperparameters.

resnet和神经ode的训练可以从最优控制的角度进行阐述和分析。本文提出了一种用于分类问题的resnet和神经ode训练的耗散公式。具体来说，我们将交叉熵（标签平滑）的一种变体视为损失函数和阶段成本的正则化。基于我们的训练耗散公式，我们证明了ResNets和神经ode的训练ocp都表现出收费公路现象。我们用两个螺旋和MNIST数据集的数值结果来说明这一发现。至关重要的是，我们的训练公式确保在第一层实现数据从输入到输出的转换。在构成收费公路的以下层中，数据保持在平衡状态，因此这些层对学习到的转换没有贡献。原则上，这些层可以在训练后进行修剪，从而使网络只具有必要的层数，从而简化超参数的调优。

引用次数: 0

Non-overshooting output shaping for switched linear systems under arbitrary switching using eigenstructure assignment 基于特征结构赋值的任意开关线性系统非超调输出整形

IF 5.9 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Automatica

Pub Date : 2026-01-21 DOI: 10.1016/j.automatica.2026.112831

Kai Wulff , Maria Christine Honecker , Robert Schmid , Johann Reger

We consider the analytical control design for switched linear multiple-input multiple-output (MIMO) systems subject to arbitrary switching signals. A state feedback controller design method is proposed to obtain an eigenstructure assignment ensuring that the closed-loop switched system is globally asymptotically stable, and the outputs achieve the non-overshooting tracking of a step reference. Our analysis indicates whether non-overshooting or even monotonic tracking is achievable for the given system and considered outputs, and provides a choice of possible eigenstructures to be assigned to the constituent subsystems. We derive a structural condition that verifies the feasibility of the chosen assignment. A constructive algorithm to obtain suitable feedback matrices is provided, and the method is illustrated with numerical examples.

研究了受任意开关信号影响的切换线性多输入多输出（MIMO）系统的解析控制设计。提出了一种状态反馈控制器设计方法来获得特征结构分配，保证闭环切换系统全局渐近稳定，输出实现阶跃参考的非超调跟踪。我们的分析表明，对于给定的系统和考虑的输出，是否可以实现非超调或甚至单调跟踪，并提供了分配给组成子系统的可能特征结构的选择。我们推导了一个结构条件来验证所选赋值的可行性。给出了一种构造算法来获取合适的反馈矩阵，并用数值算例说明了该方法。

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