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Sampled-data event-triggered control with sampling-independent positive guarantees on inter-event times Automatica (IF 4.8) Pub Date : 2024-06-24 Hao Yu, Tongwen Chen
To fit with a digital environment in networked control systems, sampled-data event-triggered control (ETC) has been proposed where the event-triggering mechanisms sense and process information only at discrete sampling instants (not necessarily periodically). One deficiency in the previous study on sampled-data ETC is the lack of analysis on transmission performance, which yields the potential occurrence
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Analysis of sampled-data hybrid integrator-gain systems: A discrete-time approach Automatica (IF 4.8) Pub Date : 2024-06-24 Bardia Sharif, Dirk Alferink, Marcel Heertjes, Hendrik Nijmeijer, Maurice Heemels
Hybrid integrator-gain systems (HIGS) are hybrid control elements used to overcome fundamental performance limitations of linear time-invariant feedback control, and have enjoyed recent successes in engineering applications such as high-precision motion systems. However, despite the relevance of digital implementations, the creation of sampled-data versions of HIGS and their formal analysis have not
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Characterization of eventual conditional invariance for hybrid dynamical systems Automatica (IF 4.8) Pub Date : 2024-06-10 Mohamed Maghenem, Hyejin Han, Ricardo G. Sanfelice
Sufficient conditions to guarantee eventual conditional invariance (ECI) for hybrid dynamical systems are formulated. Roughly speaking, eventual conditional invariance encodes the property of solutions that, when they start from a given set of initial conditions, they reach a target set after a finite amount of time and remain in it for future time. The sufficient conditions for ECI presented in this
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A non-Gaussian Bayesian filter using power and generalized logarithmic moments Automatica (IF 4.8) Pub Date : 2024-05-28 Guangyu Wu, Anders Lindquist
In this paper, we propose a consistent non-Gaussian Bayesian filter for which the system state is a continuous function. The distributions of the true system states, and those of the system and observation noises, are only assumed Lebesgue integrable with no prior constraints on what function classes they fall within. This type of filter has significant merits in both theory and practice, in that it
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Adaptive intrusion tolerant control for a class of uncertain nonlinear cyber–physical systems with full-state constraints Automatica (IF 4.8) Pub Date : 2024-05-27 Zhaoyang Cuan, Yingying Ren, Da-Wei Ding
In this paper, we investigate the tracking control issue for a kind of state-constrained nonlinear cyber–physical systems (CPSs) with exogenous interferences, which are subject to deception attacks started in controller–actuator (C–A) channel. Firstly, we design a nonlinear state dependent function (NSDF) which only relies on the restricted states to deal with the asymmetric state constraints. Furthermore
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A nonsmooth analysis and synthesis for semiglobal input delay tolerance of nonlinear systems without LES Automatica (IF 4.8) Pub Date : 2024-05-27 Congran Zhao, Wei Lin
This research focuses on the input delay tolerance problem for yet possibly non-locally Lipschitz continuous nonlinear systems that are not locally exponentially stabilizable (LES) by any smooth feedback. Using the Lyapunov–Razumikhin method, nonsmooth analysis/synthesis tools and homogeneity with respect to a family of dilations, we show that global asymptotic stabilizability (GAS) by nonsmooth homogeneous
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Model-based control of switched linear systems under network communication Automatica (IF 4.8) Pub Date : 2024-05-25 Jun Fu, Tai-Fang Li, Tao Yang, Bin Lu
Model-based control strategy is introduced for improving the closed-loop performance of switched systems under network communication in this paper. In traditional networked control system, a Zero-Order Hold (ZOH) is often used at the controller side to realize continuous feedback control. However, to use a ZOH usually decreases control accuracy since the state will be held invariably during each sampling
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Asymptotically efficient Quasi-Newton type identification with quantized observations under bounded persistent excitations Automatica (IF 4.8) Pub Date : 2024-05-25 Ying Wang, Yanlong Zhao, Ji-Feng Zhang
This paper is concerned with the optimal identification problem of dynamical systems in which only quantized output observations are available under the assumption of fixed thresholds and bounded persistent excitations. Based on a time-varying projection, a weighted Quasi-Newton type projection (WQNP) algorithm is proposed. With some mild conditions on the weight coefficients, the algorithm is proved
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Distributed-delay input shaper with Bernstein polynomial kernel function Automatica (IF 4.8) Pub Date : 2024-05-25 Tarunraj Singh, Jaroslav Bušek, Tomáš Vyhlídal
The focus of this paper is on the design of distributed delay multi-mode input shapers which emphasize smooth transients and reveal a favorable placement of the shaper zeros. The shaper is linearly parameterized using Bernstein polynomials as the kernel functions. The nonnegative magnitude of the Bernstein polynomials over the support of the shaper allows the formulation of convex constraints to design
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Output-feedback adaptive boundary control of coupled equidiffusive parabolic PDE systems Automatica (IF 4.8) Pub Date : 2024-05-25 Runsheng Guo, Jianbin Qiu, Tong Wang, Kangkang Sun
This paper investigates the output-feedback adaptive boundary control issue of the -dimensional coupled parabolic PDE system (PPDES) with the same diffusivity parameters and the unknown spatially varying parameters. To further simplify the target system, the coupled PPDES is converted into its observer canonical form via a backstepping transformation. To estimate system states, an observer is constructed
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Federated reinforcement learning for robot motion planning with zero-shot generalization Automatica (IF 4.8) Pub Date : 2024-05-25 Zhenyuan Yuan, Siyuan Xu, Minghui Zhu
This paper considers the problem of learning a control policy for robot motion planning with zero-shot generalization, i.e., no data collection and policy adaptation is needed when the learned policy is deployed in new environments. We develop a federated reinforcement learning framework that enables collaborative learning of multiple learners and a central server, i.e., the Cloud, without sharing
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Dealing with collinearity in large-scale linear system identification using Gaussian regression Automatica (IF 4.8) Pub Date : 2024-05-25 Wenqi Cao, Gianluigi Pillonetto
We consider estimation of large-scale linear dynamic systems fed with correlated and possibly poor exciting inputs. We develop a Bayesian strategy where any impulse response is a zero-mean Gaussian process with stable spline covariance to encode BIBO stability. We design a variation of Gibbs sampling to deal efficiently with collinearity: beyond considering blocks forming a partition of the parameter
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Parameter tuning of modified adaptive backstepping controller for strict-feedback nonlinear systems Automatica (IF 4.8) Pub Date : 2024-05-23 Xiaoping Liu, Ning Li, Cungen Liu, Jun Fu, Huanqing Wang
Most research on control of nonlinear systems using backstepping concentrates on construction of feedback controllers to achieve stability and/or steady-state tracking performance. Little research considers systematic methods for tuning nonlinear feedback controllers to guarantee the transient performance. This paper investigates how parameters of a backstepping controller can be determined to achieve
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Accelerating the convergence rate of consensus for second-order multi-agent systems by memory information Automatica (IF 4.8) Pub Date : 2024-05-21 Jiahao Dai, Jing-Wen Yi, Li Chai
The consensus problem of second-order multi-agent systems (MASs) has been widely studied due to its applications in various areas. This paper utilizes the agents’ memory information to accelerate the convergence rate of consensus for discrete-time second-order MASs. For the case of one-tap memory, explicit formulas for the optimal convergence rate and control parameters are derived by using a novel
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Data-driven model reduction by two-sided moment matching Automatica (IF 4.8) Pub Date : 2024-05-19 Junyu Mao, Giordano Scarciotti
In this brief paper, we propose a time-domain data-driven method for model order reduction by two-sided moment matching for linear systems. An algorithm that asymptotically approximates a key interpolation matrix from time-domain samples of the so-called two-sided interconnection is provided. Exploiting this estimated interpolation matrix, we determine the unique reduced-order model of order , which
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On hyperexponential stabilization of a chain of integrators in continuous and discrete time Automatica (IF 4.8) Pub Date : 2024-05-18 Jian Wang, Konstantin Zimenko, Denis Efimov, Andrey Polyakov
A time-varying state feedback is presented that guarantees stability and a hyperexponential rate of convergence of all trajectories to the origin for a chain of integrators. It is shown that this convergence property is uniform with respect to matched bounded external disturbances. An implicit time-discretization scheme of the closed-loop system is given, which preserves all main properties of the
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Practical prescribed-time active fault-tolerant control for mixed-order heterogeneous multiagent systems: A fully actuated system approach Automatica (IF 4.8) Pub Date : 2024-05-18 Yonghao Ma, Ke Zhang, Bin Jiang
Attaining consensus tracking within a given short time frame for uncertain heterogeneous systems in the framework of the fully actuated system approach is highly desirable and challenging. This study introduces a general practical prescribed-time stability criterion and develops a practical prescribed-time active fault-tolerant control protocol for mixed-order heterogeneous multiagent systems, considering
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Integrated adaptive consensus protocol design for linear multi-agent systems with relative output information Automatica (IF 4.8) Pub Date : 2024-05-18 Yinxiang Zhao, Qishao Wang, Yuezu Lv, Yang Yu
This paper studies the fully distributed consensus protocol design problem for linear multi-agent systems based on relative output information. An integrated adaptive law is designed to adjust the feedback control gain matrix based on the estimation of the consensus error among neighboring agents. Compared with the fixed feedback matrix in the existing adaptive consensus protocols, the proposed integrated
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Distributed control of a mobile robot multi-agent system for Nash equilibrium seeking with sampled neighbor information Automatica (IF 4.8) Pub Date : 2024-05-18 Dimitra Kalyva, Haris E. Psillakis
In this paper, we consider the distributed control design problem for Nash equilibrium (NE) seeking of a multi-agent mobile robot system using only sampled neighbor measurements. To this end, we define new continuously differentiable variables, the so-called S-GRANE variables, that smoothly incorporate the sampled neighbor information within a sampling period. It is proven that the NE seeking problem
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Identification of Wiener state–space models utilizing Gaussian sum smoothing Automatica (IF 4.8) Pub Date : 2024-05-18 Angel L. Cedeño, Rodrigo A. González, Rodrigo Carvajal, Juan C. Agüero
In this paper, we address the problem of system identification for Wiener state–space models. Our approach is based on the Maximum Likelihood method and the Expectation–Maximization algorithm. In the problem of interest, we model the output nonlinearity as a piecewise polynomial function and we jointly estimate the parameters of the linear system with the coefficients of each polynomial section. In
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Reconstructing indistinguishable solutions via a set-valued KKL observer Automatica (IF 4.8) Pub Date : 2024-05-18 Pauline Bernard, Mohamed Maghenem
KKL observer design consists in finding a smooth change of coordinates transforming the system dynamics into a linear filter of the output. The state of the original system is then reconstructed by implementing this filter from any initial condition and left-inverting the transformation, under a property. In this paper, we consider the case where the latter assumption does not hold, namely when distinct
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Consensus and multi-consensus for discrete-time LTI systems Automatica (IF 4.8) Pub Date : 2024-05-17 Filippo Cacace, Mattia Mattioni, Salvatore Monaco, Dorothée Normand-Cyrot
Existing consensus control algorithms for networked discrete-time linear systems have slow convergence to consensus trajectories due to limitations on the magnitude of the consensus gain. In this work we propose and analyze a new predictor-based consensus control protocol that recovers the positive features of the continuous-time counterpart in terms of arbitrary rate of convergence to the consensus
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Adaptive practical fixed-time synchronized tracking control of ASV with prescribed performance Automatica (IF 4.8) Pub Date : 2024-05-17 Yudi Wang, Guangdeng Zong, Xudong Zhao, Yang Yi
This paper investigates the problem of adaptive practical fixed-time synchronized tracking control of autonomous surface vehicle (ASV) systems with model uncertainties and external disturbances. In order to force the tracking error to a required range, a piecewise continuous finite-time prescribed performance function (FTPPF) is employed. A sliding mode controller incorporating FTPPF is built based
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Balancing homophily and prejudices in opinion dynamics: An extended Friedkin–Johnsen model Automatica (IF 4.8) Pub Date : 2024-05-17 Giorgia Disarò, Maria Elena Valcher
In this paper we propose an extended version of the Friedkin–Johnsen (FJ) model where we analyze the effects that a homophily-based influence matrix has on the opinion formation process. In particular, we assume that the influence matrix varies over time, and its entries (that represent the appraisals that individuals have of the other individuals) update based on the comparison between their opinions
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Extremum seeking of general nonlinear static maps: A time-delay approach Automatica (IF 4.8) Pub Date : 2024-05-17 Gaofeng Pan, Yang Zhu, Emilia Fridman, Zhengguang Wu
In this paper, we extend a newly developed time-delay approach of extremum seeking (ES) from quadratic maps to general nonlinear maps, which substantially expands the scope of application of the time-delay method. The gradient-based ES in the case of single-variable and multi-variable nonlinear static maps are considered. Different from the recent literature, the time-delay method in this paper is
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Incipient fault detection with probability transformation and statistical feature analysis Automatica (IF 4.8) Pub Date : 2024-05-16 Hongquan Ji, Wenqing Zhao, Nan Sheng
Incipient fault detection (IFD) is important to the normal operation of modern complicated industrial systems, keeping people safe and preventing property damage. In recent years, multivariate statistical process monitoring has become one of the hottest research directions in process control and fault diagnosis. However, traditional fault detection indices in statistical process monitoring do not perform
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Statistically consistent inverse optimal control for discrete-time indefinite linear–quadratic systems Automatica (IF 4.8) Pub Date : 2024-05-16 Han Zhang, Axel Ringh
The Inverse Optimal Control (IOC) problem is a structured system identification problem that aims to identify the underlying objective function based on observed optimal trajectories. This provides a data-driven way to model experts’ behavior. In this paper, we consider the case of discrete-time finite-horizon linear–quadratic problems where: the quadratic cost term in the objective is not necessarily
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Minimum entropy filtering for a single output non-Gaussian stochastic system using state transformation Automatica (IF 4.8) Pub Date : 2024-05-15 Qichun Zhang, Zhengtao Ding, Hong Wang
This paper presents a novel filter design for the single-output stochastic non-linear systems subjected to non-Gaussian noises and the proposed assumptions. Based on a state transformation, the unmeasurable states of the systems can be estimated where non-linear terms in the systems have been eliminated. It has been shown that the estimation error is linearly dynamical regarding to the presented vector-valued
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Safety reinforcement learning control via transfer learning Automatica (IF 4.8) Pub Date : 2024-05-14 Quanqi Zhang, Chengwei Wu, Haoyu Tian, Yabin Gao, Weiran Yao, Ligang Wu
Reinforcement learning (RL) has emerged as a promising approach for modern control systems. However, its success in real-world applications has been limited due to the lack of safety guarantees. To address this issue, the authors present a novel transfer learning framework that facilitates policy training in a non-dangerous environment, followed by transfer of the trained policy to the original dangerous
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Further results on state estimation of multi-agent systems under homologous attacks Automatica (IF 4.8) Pub Date : 2024-05-14 Mingming Shi, Xiaoyi Guan, Ka-Fai Cedric Yiu, Bin Li, Ai-Guo Wu
This note presents our recent results on state estimation of multi-agent systems under homologous attacks. We first present a sufficient and necessary condition on agents’ dynamics such that agents states can be reconstructed under the considered attack with finite time measurements. Violating the condition prohibits the estimation of agents’ states, regardless of the length of time measurements collected
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General stabilization approach of the low-order controller for both SISO systems and MIMO systems with multiple time delays Automatica (IF 4.8) Pub Date : 2024-05-13 Xinyi Yu, Peixuan Ding, Linlin Ou, Weidong Zhang
The stabilization of the system with multiple time delays is much more difficult than that of the rational system since the delay multiplicity complicates the system analysis. For an arbitrarily-given linear time-invariant (LTI) multiple time-delay plant, the stabilization problems of the PID controllers are solved in this paper. Necessary and sufficient conditions for the stability of general single-input
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Generalized Halanay inequality and its application to delay differential inclusions Automatica (IF 4.8) Pub Date : 2024-05-09 Zhenxing Zhang, Huabin Chen, Honglin Zhu
In this work, by using a generalized Halanay inequality, a regular Lyapunov function and the theory of nonsmooth analysis, we investigate the uniformly ultimate boundedness of the zero solution for nonautonomous delay differential inclusions. The sufficient condition is presented in integral form, which is different from the ones given in some related literature. We also provide different characterizations
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Small-gain criteria for mean-square stability of random delay systems Automatica (IF 4.8) Pub Date : 2024-05-09 Jianqi Chen, Junfeng Wu, Jie Chen
This paper studies stability problems of discrete-time linear time-invariant (LTI) systems subject to random time delays. Leveraging on a general mean-square, small-gain type stability condition for feedback systems containing structured stochastic multiplicative uncertainties, we derive mean-square small-gain stability conditions for LTI random delay systems, in which the delays may arise at random
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Iterative distributed model predictive control for heterogeneous systems with non-convex coupled constraints Automatica (IF 4.8) Pub Date : 2024-05-09 Jinxian Wu, Li Dai, Yuanqing Xia
This paper investigates the distributed model predictive control (DMPC) problem for multiple dynamically-decoupled heterogeneous linear systems subject to both local state and input constraints and coupled non-convex constraints (e.g., collision avoidance constraints). To solve the resulting non-convex optimal control problem (OCP) at each time step, successive convex approximation (SCA) technique
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Consistency analysis of refined instrumental variable methods for continuous-time system identification in closed-loop Automatica (IF 4.8) Pub Date : 2024-05-09 Rodrigo A. González, Siqi Pan, Cristian R. Rojas, James S. Welsh
Refined instrumental variable methods have been broadly used for identification of continuous-time systems in both open and closed-loop settings. However, the theoretical properties of these methods are still yet to be fully understood when operating in closed-loop. In this paper, we address the consistency of the simplified refined instrumental variable method for continuous-time systems (SRIVC) and
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A constrained control framework for unmanned aerial vehicles based on Explicit Reference Governor Automatica (IF 4.8) Pub Date : 2024-05-09 Gaetano Tartaglione, Marco M. Nicotra, Roberto Naldi, Emanuele Garone
This paper tackles the constrained control problem of unmanned aerial vehicles with planar multirotors. The proposed solution splits the constrained control problem into two separate tasks, i.e. stabilization and constraint enforcement. It is shown that the problems addressed by each individual layer is much simpler than the original combined problem. For the unconstrained control of UAVs we consider
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On topological conditions for enabling transient control in leader–follower networks Automatica (IF 4.8) Pub Date : 2024-05-09 Fei Chen, Dimos V. Dimarogonas
We derive necessary and sufficient conditions for leader–follower multi-agent systems such that we can further apply prescribed performance control to achieve the desired formation while satisfying certain transient constraints. A leader–follower framework is considered in the sense that a group of agents with external inputs are selected as leaders in order to drive the group of followers in a way
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Robust internal models with a star-shaped attractor are linear Automatica (IF 4.8) Pub Date : 2024-05-04 Michelangelo Bin, Daniele Astolfi, Lorenzo Marconi
In linear regulation theory, it is well-known that embedding in the control loop a suitable internal model of the exogenous disturbances and references permits to achieve perfect regulation of the desired variables robustly with respect to parametric uncertainties in the plant’s equations. However, it was recently proved that this principle does not extend, in general, to nonlinear systems or non-parametric
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Learning nonlinear dynamics in synchronization of knowledge-based leader-following networks Automatica (IF 4.8) Pub Date : 2024-05-04 Shimin Wang, Xiangyu Meng, Hongwei Zhang, Frank L. Lewis
Knowledge-based leader-following synchronization of heterogeneous nonlinear multi-agent systems is a challenging problem since the leader’s dynamic information is unknown to any follower node. This paper proposes a learning-based fully distributed observer for a class of nonlinear leader systems, which can simultaneously learn the leader’s dynamics and states. This class of leader dynamics is rather
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Sparse sensor selection for distributed systems: An [formula omitted]-relaxation approach Automatica (IF 4.8) Pub Date : 2024-05-03 Yuxing Zhong, Nachuan Yang, Lingying Huang, Guodong Shi, Ling Shi
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Scenario based optimisation over uncertain system identification models Automatica (IF 4.8) Pub Date : 2024-05-02 Xiaopuwen Wang, Erik Weyer
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An automata theoretic approach to observer design for switched linear systems Automatica (IF 4.8) Pub Date : 2024-04-29 Georges Aazan, Antoine Girard, Luca Greco, Paolo Mason
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Adaptive optimal tracking control of networked linear systems under two-channel stochastic dropouts Automatica (IF 4.8) Pub Date : 2024-04-27 Yi Jiang, Lu Liu, Gang Feng
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Set inversion and box contraction on Lie groups using interval analysis Automatica (IF 4.8) Pub Date : 2024-04-27 Nicolas Merlinge
Set inversion and box contraction consist in finding guaranteed solutions to an equation where variables belong to bounded sets. These problems are classic in Euclidean spaces and can be solved using interval analysis. However, they quickly become complex when dealing with non-Euclidean manifolds. This paper investigates set inversion and box contraction problems when variables belong to generic Lie
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Consistent estimators for nonlinear vessel models Automatica (IF 4.8) Pub Date : 2024-04-25 Fredrik Ljungberg, Martin Enqvist
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Back-and-forth nudging moving horizon estimation for discrete-time linear systems Automatica (IF 4.8) Pub Date : 2024-04-24 Junyao Xie, Biao Huang
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Sampled-data controller synthesis using dissipative linear periodic jump-flow systems with design applications Automatica (IF 4.8) Pub Date : 2024-04-24 Luuk Marceau Spin, M.C.F. (Tijs) Donkers
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Thompson sampling for networked control over unknown channels Automatica (IF 4.8) Pub Date : 2024-04-24 Wanchun Liu, Alex S. Leong, Daniel E. Quevedo
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Dissipative feedback switching for quantum stabilization Automatica (IF 4.8) Pub Date : 2024-04-24 Weichao Liang, Tommaso Grigoletto, Francesco Ticozzi
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A robust adaptive velocity observer for mechanical systems transformed in cascade form Automatica (IF 4.8) Pub Date : 2024-04-20 Jose Guadalupe Romero
This note presents a adaptive velocity observer for mechanical systems whose dynamic model motion does not allow for the cancellation of gyroscopic forces after coordinates transformation. Its design consists of three components: (i) for a class of systems, we propose a decomposition to render its model in cascade form; (ii) we give necessary and sufficient conditions to include unknown external disturbances
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Online convex optimization using coordinate descent algorithms Automatica (IF 4.8) Pub Date : 2024-04-19 Yankai Lin, Iman Shames, Dragan Nešić
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Exponential convergence of time-of-arrival based network clock synchronization under practical assumptions Automatica (IF 4.8) Pub Date : 2024-04-19 Ruixin Wen, Eric Schoof, Airlie Chapman
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Converse negative imaginary theorems Automatica (IF 4.8) Pub Date : 2024-04-18 Sei Zhen Khong, Di Zhao, Alexander Lanzon
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Global prescribed-time output feedback control of a class of uncertain nonlinear systems by linear time-varying feedback Automatica (IF 4.8) Pub Date : 2024-04-18 Kang-Kang Zhang, Bin Zhou, Guang-Ren Duan
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Local stabilization conditions for discrete-time switched affine systems Automatica (IF 4.8) Pub Date : 2024-04-18 Ghania Khodja, Christophe Fiter, Laurentiu Hetel, Thierry Floquet
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Neuron growth control and estimation by PDE backstepping Automatica (IF 4.8) Pub Date : 2024-04-18 Cenk Demir, Shumon Koga, Miroslav Krstic
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Minimum jointly structural input and output selection Automatica (IF 4.8) Pub Date : 2024-04-18 Guilherme Ramos, A. Pedro Aguiar, Sérgio Pequito
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Multi-agreements in social networks based on LaSalle invariance principle and positive definiteness Automatica (IF 4.8) Pub Date : 2024-04-18 Ti-Chung Lee, Ying Zhang, Iven Mareels
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Sampled-data observer design for Linear Kuramoto–Sivashinsky systems with non-local output Automatica (IF 4.8) Pub Date : 2024-04-18 Iasson Karafyllis, Tarek Ahmed-Ali
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Geometric PID controller for stabilization of nonholonomic mechanical systems on Lie groups Automatica (IF 4.8) Pub Date : 2024-04-18 Rama Seshan Chandrasekaran, Ravi N. Banavar, Arun D. Mahindrakar, D.H.S. Maithripala