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Remote robust state estimation for nonlinear systems 非线性系统的远程鲁棒状态估计

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

Automatica

Pub Date : 2025-12-19 DOI: 10.1016/j.automatica.2025.112795

Alexander Yu. Pogromsky , Alexey S. Matveev

This paper addresses the problem of robust remote state estimation for uncertain nonlinear discrete-time systems when sensor data are transmitted through a digital communication channel of finite bit-rate capacity. The goal is to determine the minimal channel rate required to guarantee a prescribed estimation accuracy in the presence of bounded model uncertainty. We derive an explicit, tractable lower bound on the channel bit rate that ensures this accuracy for any admissible uncertainty level. The bound highlights the fundamental role of the accuracy-to-uncertainty ratio in remote estimation. The analysis relies on a quadratic dissipation inequality describing system uncertainty within the framework of incremental input-to-state stability, leading to a constructive Lyapunov-based characterization. The proposed conditions admit a closed-form analytical expression for a class of systems, including the uncertain Lozi map, which serves as an illustrative example.

本文研究了不确定非线性离散系统的鲁棒远程状态估计问题，当传感器数据通过有限比特率容量的数字通信信道传输时。目标是确定在存在有界模型不确定性的情况下保证规定估计精度所需的最小信道速率。我们推导了一个明确的、易于处理的信道比特率下界，以确保在任何可接受的不确定性水平下都具有这种准确性。该边界突出了精度与不确定度比在远程估计中的基本作用。该分析依赖于在增量输入到状态稳定性框架内描述系统不确定性的二次耗散不等式，从而导致基于李雅普诺夫的建设性表征。对于一类系统，包括不确定Lozi映射，所提出的条件允许一个封闭形式的解析表达式，作为一个说明性的例子。

引用次数: 0

Maximum-system-reliability control allocation for spacecraft with redundant actuators 具有冗余作动器的航天器最大系统可靠性控制分配

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

Automatica

Pub Date : 2025-12-19 DOI: 10.1016/j.automatica.2025.112779

Jianchun Zhang , Xiang Yu , Jianzhong Qiao , Lei Guo

On-orbit useful lifetime is a critical metric for spacecraft missions, for which we propose a maximum-system-reliability control allocation scheme for spacecraft with redundant actuators. The dynamic reliability model for the redundant actuator system is formulated, incorporating an online parameter estimation method initialized with offline estimates. On this basis, we define a control allocation optimization problem that maximizes the one-step system reliability prediction. To enable efficient online computation, a recursive optimization algorithm is introduced. Theoretical analysis proves that the proposed approach can extend the useful lifetime of the redundant actuator system with any failure mode. A comparative example of spacecraft attitude stabilization validates the feasibility, generality, and superiority of the proposed method.

在轨使用寿命是航天器任务的一个关键指标，针对这一指标，提出了一种具有冗余作动器的航天器最大系统可靠性控制分配方案。建立了冗余作动器系统的动态可靠性模型，采用离线估计初始化的在线参数估计方法。在此基础上，我们定义了一个使一步系统可靠性预测最大化的控制分配优化问题。为了实现高效的在线计算，引入了递归优化算法。理论分析表明，该方法可以延长任意失效模式下冗余作动器系统的使用寿命。以航天器姿态稳定为例，验证了该方法的可行性、通用性和优越性。

引用次数: 0

Distributed algorithms for solving linear algebraic equations: An optimal control perspective 求解线性代数方程的分布式算法：最优控制视角

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

Automatica

Pub Date : 2025-12-19 DOI: 10.1016/j.automatica.2025.112772

Juntao Li , Cong Liang , Deyuan Meng

Designing superior distributed algorithms for solving linear algebraic equations (LAEs) plays a crucial role in engineering and computer science fields. This paper proposes two discrete distributed algorithms for solving LAEs from the perspective of optimal control. By benefiting from the devised error system and constructed performance index, the presented algorithms can converge R-linearly to a solution of LAEs without solving algebraic Riccati equations. In particular, the full-row rank requirements on sub-matrices are eliminated in row partitioning framework. Moreover, the need for communication exchange among all agents within the same cluster is alleviated, and only one state variable is updated in the row-wise arbitrary column partitioning framework. Simulation results demonstrate that the proposed distributed algorithms outperform non-optimal control design algorithms in terms of convergence performance.

设计求解线性代数方程的分布式算法在工程和计算机科学领域具有重要的意义。本文从最优控制的角度出发，提出了求解LAEs的两种离散分布算法。利用所设计的误差系统和所构建的性能指标，所提出的算法可以在不求解代数Riccati方程的情况下，将r -线性收敛到LAEs的解。特别地，在行划分框架中消除了子矩阵的全行秩要求。此外，减少了同一集群内所有代理之间的通信交换需求，并且在逐行任意列分区框架中只更新一个状态变量。仿真结果表明，该算法在收敛性能上优于非最优控制设计算法。

引用次数: 0

Nonlinear moving horizon estimation for robust state and parameter estimation 非线性运动水平估计的鲁棒状态和参数估计

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

Automatica

Pub Date : 2025-12-19 DOI: 10.1016/j.automatica.2025.112790

Julian D. Schiller, Matthias A. Müller

We propose a moving horizon estimation scheme to estimate the states and the unknown constant parameters of general nonlinear uncertain discrete-time systems. The proposed framework and analysis explicitly do not involve the a priori verification of a particular excitation condition for the parameters. Instead, we use online information about the actual excitation of the parameters at any time during operation and ensure that the regularization term in the cost function is always automatically selected appropriately. This ensures that the state and parameter estimation error is bounded for all times, even if the parameters are never (or only rarely) excited during operation. Robust exponential stability of the state and parameter estimation error emerges under an additional uniform condition on the maximum duration of insufficient excitation. The theoretical results are illustrated by a numerical example.

针对一般非线性不确定离散系统的状态和未知常数参数，提出了一种移动视界估计方法。所提出的框架和分析明确不涉及对参数的特定激励条件的先验验证。相反，我们在运行过程中随时使用有关参数实际激励的在线信息，并确保成本函数中的正则化项总是自动选择适当的。这确保了状态和参数估计误差在任何时候都是有界的，即使参数在操作期间从未（或很少）被激发。在最大不充分激励持续时间的附加均匀条件下，状态和参数估计误差具有鲁棒指数稳定性。通过数值算例对理论结果进行了说明。

引用次数: 0

Distributed local-constraint-satisfied strategy for noncooperative games of autonomous general linear players and its application to smart grids 自主一般线性参与人非合作博弈的分布式局部约束满足策略及其在智能电网中的应用

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

Automatica

Pub Date : 2025-12-19 DOI: 10.1016/j.automatica.2025.112791

Zhenhua Deng, Cong Liu

This paper studies constrained noncooperative games (NGs), which take the general linear dynamics of players into account. In the formulation, each player has local convex set constraints, and all players are restricted by coupling nonlinear inequality constraints. Notably, the majority of existing results for NGs with physical systems do not involve local constraints, let alone general convex sets. Besides, nearly all of related results cannot guarantee local constraints to be satisfied all the time, because physical players cannot control their decisions directly due to system dynamics. Here we develop a distributed adaptive strategy on the basis of gradient descent, projection operators, primal–dual methods and state feedback. The strategy is fully distributed. We analyze the strategy via variational analysis and Lyapunov theory. With our strategy, the players seek the exact variational generalized Nash equilibrium (v-GNE), and always satisfy local constraints, in contrast to existing results. Lastly, our method is applied to the electricity market games of doubly-fed induction generators.

本文研究了考虑参与者一般线性动态的约束非合作博弈。在公式中，每个参与者都有局部凸集约束，所有参与者都受到耦合非线性不等式约束的约束。值得注意的是，对于物理系统的大多数现有结果都不涉及局部约束，更不用说一般凸集了。此外，几乎所有的相关结果都不能保证始终满足局部约束，因为物理参与者由于系统动力学的原因不能直接控制他们的决策。本文提出了一种基于梯度下降、投影算子、原始对偶方法和状态反馈的分布式自适应策略。战略是完全分布的。本文通过变分分析和李亚普诺夫理论对该策略进行了分析。与现有的结果相比，该策略的参与者寻求精确的变分广义纳什均衡（v-GNE），并且总是满足局部约束。最后，将该方法应用于双馈感应发电机的电力市场博弈。

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引用次数: 0

CBF-based safety design for adaptive control of uncertain nonlinear strict-feedback systems 基于cbf的不确定非线性严格反馈系统自适应控制安全设计

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

Automatica

Pub Date : 2025-12-19 DOI: 10.1016/j.automatica.2025.112782

Liwei An , Can Zhao , Guang-Hong Yang

This paper studies the problem of adaptive tracking control for nonlinear strict-feedback systems with parametric uncertainties and safety constraints. A co-design strategy of control barrier functions (CBFs) and barrier Lyapunov functions (BLFs) is proposed, which inherits the robustness and stability of traditional adaptive backstepping controllers. First, a safe virtual control signal is generated by the CBF-induced quadratic programming (QP), which is the suboptimal and smooth solution of the QP with a shifting function. Then, a BLF-based backstepping controller is designed by following the safe virtual control signal. It is shown that the co-design can minimize the damage to the original tracking performance on the premise of safety guarantees. The distinguishing point of the safety design over the existing results is to avoid constructing the high-order CBFs that lead to conservative feasible sets of inputs for ensuring high-relative-degree safety constraints. The simulation results show that the proposed scheme achieves better tracking performance compared with the existing high-order CBF-based method.

研究了具有参数不确定性和安全约束的非线性严格反馈系统的自适应跟踪控制问题。提出了一种控制障碍函数（cbf）和障碍李雅普诺夫函数（blf）的协同设计策略，继承了传统自适应反演控制器的鲁棒性和稳定性。首先，利用cbf诱导的二次规划（QP）生成一个安全的虚拟控制信号，该信号是带移位函数的二次规划的次优光滑解。然后，根据安全虚拟控制信号设计了基于blf的反步控制器。研究表明，在保证安全的前提下，协同设计能最大限度地降低对原有跟踪性能的破坏。安全设计与现有结果的区别在于避免构建高阶cbf，从而导致保守的可行输入集，以确保高相对程度的安全约束。仿真结果表明，与现有的基于高阶cbf的方法相比，该方法具有更好的跟踪性能。

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引用次数: 0

Stationary Stackelberg equilibrium in two-person zero-sum stochastic Stackelberg games 二人零和随机Stackelberg对策中的平稳Stackelberg均衡

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

Automatica

Pub Date : 2025-12-19 DOI: 10.1016/j.automatica.2025.112758

Kaiyun Xie , Junlin Xiong

This paper investigates the existence and computability of the stationary Stackelberg equilibrium (SSE) in two-person zero-sum stochastic Stackelberg games (SSGs). First, an operator-based approach is developed to illustrate that such games admit a fixed-point equilibrium (FPE). It is further proven that the FPE strategy pair constitutes an SSE. Building on this foundation, a value iteration (VI) algorithm is proposed to compute the SSE strategies. However, due to the curse of dimensionality, the exact computation of SSE strategies involves high computational complexity. To address this issue, an

ϵ

-sacrifice strategy is introduced to approximate the leader’s SSE strategy by performing finite iterations, with the degree of approximation quantified by

ϵ

. The relationship between

ϵ

and the number of iterations

n

is established, ensuring a trade-off between computational efficiency and strategic performance. An information flow control example demonstrates the efficiency of the designed strategies.

研究了二人零和随机Stackelberg对策中平稳Stackelberg均衡（SSE）的存在性和可计算性。首先，提出了一种基于算子的方法来说明这种博弈承认不动点均衡（FPE）。进一步证明了FPE策略对构成SSE。在此基础上，提出了一种计算SSE策略的值迭代（VI）算法。然而，由于维度的诅咒，SSE策略的精确计算涉及到很高的计算复杂度。为了解决这个问题，引入ϵ-sacrifice策略，通过执行有限迭代来近似领导者的SSE策略，近似程度由λ量化。建立了λ和迭代次数n之间的关系，确保了计算效率和策略性能之间的权衡。一个信息流控制实例验证了所设计策略的有效性。

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引用次数: 0

Distributed control to steer dynamical systems to the generalized Nash equilibria for monotone aggregative games with operational constraints 带操作约束的单调聚集对策的分布式控制

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

Automatica

Pub Date : 2025-12-19 DOI: 10.1016/j.automatica.2025.112794

Ming Li , Zhaojian Wang , Mengshuo Jia , Feng Liu , Bo Yang , Xinping Guan

In this paper, we propose a distributed feedback controller to steer a multi-agent dynamical system to the generalized Nash equilibrium (GNE) for an aggregative game with only a monotone pseudo-gradient. First, a monotone aggregative game among the agents is formulated, which considers operational constraints in both the transient process and the steady state. Then, a distributed controller based on primal–dual gradient dynamics is designed for each agent to steer the system to track the GNE of the predefined game autonomously. The controller relaxes the requirement of the strictly/strongly monotone pseudo-gradient. At the same time, the hard limits of the control input are satisfied both at equilibrium and during the transient process. We further prove that the closed-loop system is asymptotically stable and its equilibrium attains the GNE. Finally, a practical example of frequency control on IEEE 68-bus system verifies the effectiveness of the proposed method.

在本文中，我们提出了一种分布式反馈控制器来引导多智能体动态系统在只有单调伪梯度的聚集对策下达到广义纳什均衡（GNE）。首先，建立了agent间的单调聚合对策，同时考虑了瞬态过程和稳态过程的操作约束。然后，为每个智能体设计基于原对偶梯度动力学的分布式控制器，引导系统自主跟踪预定义博弈的GNE；该控制器放宽了对严格/强单调伪梯度的要求。同时，在平衡态和暂态过程中都满足控制输入的硬极限。进一步证明了闭环系统是渐近稳定的，其平衡点达到了GNE。最后，通过IEEE 68总线系统的频率控制实例验证了所提方法的有效性。

引用次数: 0

Trajectory-informed machine learning for quantum optimal control of uncertain systems 不确定系统量子最优控制的轨迹信息机器学习

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

Automatica

Pub Date : 2025-12-19 DOI: 10.1016/j.automatica.2025.112756

Ali Wadi, Kyriakos G. Vamvoudakis

In this paper, we introduce a trajectory-informed machine learning framework to address the infinite-horizon optimal control problem for uncertain quantum-mechanical systems. Our approach is inspired by physics-informed neural networks (PINNs), but is based on trajectories rather than points. Moreover, our methodology does not require knowledge of the drift term of the system’s dynamics. It also uses a finite-horizon formulation for the quantum optimal control (QOC) problem that can guarantee a unique solution to the derived Hamilton–Jacobi–Bellman (HJB) equation, which is currently not achievable with traditional PINNs. We finally provide a rigorous mathematical justification, demonstrating that the solution uniformly converges and approximates the infinite-horizon HJB for a sufficiently large finite horizon. We have validated our proposed QOC approach through simulations on the spin-

1 / 2

particle quantum system.

在本文中，我们引入了一个轨迹信息的机器学习框架来解决不确定量子力学系统的无限视界最优控制问题。我们的方法受到物理信息神经网络（pinn）的启发，但基于轨迹而不是点。此外，我们的方法不需要系统动力学漂移项的知识。它还使用了量子最优控制（QOC）问题的有限视界公式，可以保证导出的Hamilton-Jacobi-Bellman （HJB）方程的唯一解，这是目前传统pin n无法实现的。最后给出了严格的数学证明，证明了在足够大的有限视界下，解一致收敛并近似于无限视界HJB。我们通过自旋1/2粒子量子系统的模拟验证了我们提出的QOC方法。

引用次数: 0

Non-invasive chaos control based on 2-contraction stabilizability 基于2-收缩稳定性的无创混沌控制

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

Automatica

Pub Date : 2025-12-19 DOI: 10.1016/j.automatica.2025.112778

David Angeli , Davide Martini , Giacomo Innocenti , Alberto Tesi

In this paper a non-invasive approach to chaos control based on

k

-Contraction Theory is developed. Specifically, some recent results on 2-contractive nonlinear systems are suitably extended to design a feedback controller capable to remove attractors with positive Lyapunov exponents of the open loop system, without altering the equilibrium points. First, 2-contraction stabilizability of linear control systems is discussed, showing that it can be checked by solving some linear matrix inequalities. Then, a novel technique based on 2-contraction stabilizability is devised for computing the gain matrix of a derivative feedback controller ensuring that the controlled system has the same equilibrium points of the uncontrolled one but no longer displays attractors with positive Lyapunov exponents. Finally, the classical Lorenz system is employed to illustrate the features of the proposed technique.

本文提出了一种基于k-收缩理论的无创混沌控制方法。具体地说，适当地推广了最近关于2-收缩非线性系统的一些结果，设计了一种能够在不改变平衡点的情况下去除开环系统中具有正Lyapunov指数的吸引子的反馈控制器。首先，讨论了线性控制系统的2-收缩镇定性，表明它可以通过求解一些线性矩阵不等式来检验。然后，设计了一种基于2收缩稳定性的导数反馈控制器增益矩阵计算方法，保证被控系统与非控系统具有相同的平衡点，但不再显示具有正Lyapunov指数的吸引子。最后，利用经典洛伦兹系统说明了该技术的特点。

引用次数: 0

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