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Probability-guaranteed distributed set-membership filtering over sensor networks: A stochastic communication protocol case Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-19 Hui Yu, Dongjie Peng, Cai Chen, Dongyan Chen, Cong Han
This study is focused on the probability-guaranteed distributed set-membership (PDSM) filtering problem for a class of nonlinear systems with distributed delays, uniform quantization and stochastic communication protocol (SCP) over sensor networks. Also, the system noise is allowed to be unknown-but-bounded (UBB). To minimize and prevent the collision of data, SCP can be effectively implemented in
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Nonlinear discrete-time Halanay inequality with forcing term Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-19 Maria Teresa Grifa, Pierdomenico Pepe
In this work, a novel nonlinear Halanay inequality with forcing term is provided for the discrete-time case. Uniform convergence of involved functions to a suitable neighborhood of the origin is shown, whose amplitude depends on the amplitude of the forcing term, in the spirit of the input-to-state stability notion.
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Mixed [formula omitted] robust formation tracking control of linear multi-agent system using output information Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-17 Arnab Pal, Asim Kr. Naskar
This paper investigates a mixed robust formation tracking control problem for linear multi-agent systems (MAS) in presence of disturbances and measurement noises in the agent model. An output based dynamic controller is proposed for each agent, which minimizes the mixed performance measure, and ensures formation tracking under directed network topology. With the help of the unified framework representation
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Constrained monotone mean–variance investment-reinsurance under the Cramér–Lundberg model with random coefficients Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-15 Xiaomin Shi, Zuo Quan Xu
This paper studies an optimal investment-reinsurance problem for an insurer (she) under the Cramér–Lundberg model with monotone mean–variance (MMV) criterion. At any time, the insurer can purchase reinsurance (or acquire new business) and invest in a security market consisting of a risk-free asset and multiple risky assets whose excess return rate and volatility rate are allowed to be random. The trading
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Adaptive safety-critical control for a class of nonlinear systems with parametric uncertainties: A control barrier function approach Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-13 Yujie Wang, Xiangru Xu
This paper presents a novel approach for the safe control design of systems with parametric uncertainties in both drift terms and control-input matrices. The method combines control barrier functions and adaptive laws to generate a safe controller through a nonlinear program with an explicitly given closed-form solution. The proposed approach verifies the non-emptiness of the admissible control set
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Total-activity conservation of probabilistic Boolean networks and its applications Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-12 Haitao Li, Lingling Wu
Conservation law is a basic property of biological networks, which exhibits the total-activity conservation in Boolean networks (BNs). This article analyzes the total-activity conservation of probabilistic Boolean networks (PBNs) based on the algebraic state space representation approach. The concept of total-activity conservation is proposed for PBNs, and a vector-based criterion is presented to verify
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Geometric semistability for ultimately bounded semistability of discrete-time dynamical systems Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-12 Junsoo Lee
This paper focuses on analyzing the geometric semistability and ultimately bounded semistability of discrete-time dynamical systems with a continuum of equilibria. Semistability is a property of a dynamical system where the solutions converge to Lyapunov stable equilibrium points, which are determined by the initial conditions of the system. In this paper, a rigorous framework for geometric semistability
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Finite region stability and networked predictive control for 2-D nonlinear time-delayed systems with quantization, packet dropouts and random disturbances Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-11 Da Pan, Dan Peng
In this paper, we focus on the finite region stability (FRS) and networked predictive control (NPC) problems for two-dimensional (2-D) networked control systems (NCS) with time delays, quantization errors, packet losses and random disturbances described by the Roesser model. The random packet dropouts and disturbances are modeled as Bernoulli process, and the sufficient conditions of FRS and finite
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Iterative learning control with inverse model updated with quadratic optimization Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-10 Yusuke Fujimoto
This paper discusses a new iterative learning control method which employs inverse model of the system updated every iteration with quadratic optimization. The proposed method constructs an inverse model without estimating forward model, and the inverse model is described by finite impulse response model. These points enable the proposed method to guarantee the convergence and monotonic improvement
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Almost sure exponential stability and stochastic stabilization of impulsive stochastic differential delay equations Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-06 Xin Liu, Pei Cheng, Yao Cui
In this paper, we mainly study the almost sure exponential stability of impulsive stochastic differential delay equations (ISDDEs) with bounded variable delays. The main technique is to compare ISDDEs with corresponding impulsive stochastic differential equations (ISDEs) without delay, to obtain the upper bound of delays that ISDDEs can maintain stability by accurate calculation. The results show that
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Stability analysis for nonautonomous impulsive hybrid stochastic delay systems Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-04 Huabin Chen, Peng Shi, Cheng-Chew Lim
In this paper, the problems on the existence and uniqueness, and the input-to-state stability for the global solution of nonlinear nonautonomous impulsive stochastic delay systems with Markovian switching are considered. The existence and uniqueness for the global solution of such systems is studied by using the Lyapunov function, the theory of stochastic analysis, and the function of the impulsive
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Finite-time interval stabilization for time-varying stochastic delayed systems via interval matrix method by piecewise controllers Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-03 Guici Chen, Huimin Zeng, Jinrong Yang, Junhao Hu
This paper presents a comprehensive study addressing the problem of finite-time interval stabilization (FTIS) for two distinct types of systems: linear time-invariant stochastic delayed systems (LTISDSs) and linear time-varying stochastic delayed systems (LTVSDSs). To begin, the definition of FTIS is established, which is based on employing piecewise state feedback controllers. Subsequently, a time-varying
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Decompositions of nonlinear input–output systems to zero the output Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-03 W. Steven Gray, Kurusch Ebrahimi-Fard, Alexander Schmeding
Consider an input–output system where the output is the tracking error given some desired reference signal. It is natural to consider under what conditions the problem has an exact solution, that is, the tracking error is exactly the zero function. If the system has a well defined relative degree and the zero function is in the range of the input–output map, then it is well known that the system is
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On the spectral radius properties of a key matrix in periodic impulse control Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-02 Swati Patel, Patrick De Leenheer
In this work, we consider the periodic impulse control of a system modeled as a set of linear differential equations. We define a matrix that governs the qualitative behavior of the controlled system. This matrix depends on the period and effects of the control interventions. We investigate properties of the spectral radius of this matrix and in particular, how it depends on the period of the interventions
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One dimensional BSDEs with critical integrable terminal values and infinite time horizon Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-02 Kazuki Adachi, Bin Xie
We mainly study the existence and uniqueness of solutions to one-dimensional backward stochastic differential equations with terminal values satisfying a critical integrability and infinite time horizon. The main result is established under the assumption that the generator exhibits a time-varying monotonicity in and uniform continuity in and the terminal value is required to satisfy the critical -integrability
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Decentralized stochastic linear-quadratic optimal control with risk constraint and partial observation Syst. Control Lett. (IF 2.6) Pub Date : 2024-04-02 Hui Jia, Yuan-Hua Ni
This paper addresses a risk-constrained decentralized stochastic linear-quadratic optimal control problem with one remote controller and one local controller, where the risk constraint is posed on the cumulative state weighted variance in order to reduce the oscillation of system trajectory. In this model, local controller can only partially observe the system’s state, and sends the estimate of state
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A Q-learning algorithm for Markov decision processes with continuous state spaces Syst. Control Lett. (IF 2.6) Pub Date : 2024-03-26 Jiaqiao Hu, Xiangyu Yang, Jian-Qiang Hu, Yijie Peng
We propose an online algorithm for solving a class of continuous-state Markov decision processes. The algorithm combines classical Q-learning with an asynchronous averaging procedure, which allows Q-function estimates at sampled state–action pairs to be adaptively updated based on observations collected along a single sample trajectory. These estimates are then used to iteratively construct an interpolation-based
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Infinite horizon LQG Graphon Mean Field Games: Explicit Nash values and local minima Syst. Control Lett. (IF 2.6) Pub Date : 2024-03-26 Rinel Foguen-Tchuendom, Shuang Gao, Peter E. Caines, Minyi Huang
In this study, we generalize the analysis of infinite horizon linear quadratic Gaussian (LQG) Mean Field Games within the framework of Graphon Mean Field Games (GMFG) introduced in Caines and Huang (2018) over finite horizons. Graphon Mean Field Games (GMFGs) are non-uniform generalizations of Mean Field Games where the non-uniformity of agents is characterized by the nodes on which they are located
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Event-triggered boundary control of an unstable reaction diffusion PDE with input delay Syst. Control Lett. (IF 2.6) Pub Date : 2024-03-21 Florent Koudohode, Nicolas Espitia, Miroslav Krstic
In chemical, biological, or population (epidemiological) processes the feedback action may be considerably delayed by time-consuming chemical measurements or biological tests. With such large delays on the control action in mind, and motivated by the fact that in some of these systems only piecewise-constant inputs can be applied between time instants at which measurements trigger changes in control
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Adaptive observer and control of spatiotemporal delayed neural fields Syst. Control Lett. (IF 2.6) Pub Date : 2024-03-19 Lucas Brivadis, Antoine Chaillet, Jean Auriol
An adaptive observer is proposed to estimate the synaptic distribution between neurons asymptotically from the measurement of a part of the neuronal activity and a delayed neural field evolution model. The convergence of the observer is proved under a persistency of excitation condition. Then, the observer is used to derive a feedback law ensuring asymptotic stabilization of the neural fields. Finally
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Safe Region Multi-Agent Formation Control With Velocity Tracking Syst. Control Lett. (IF 2.6) Pub Date : 2024-03-18 Ayush Rai, Shaoshuai Mou
This paper provides a solution to the problem of safe region formation control with reference velocity tracking for a second-order multi-agent system without velocity measurements. Safe region formation control is a control problem where the agents are expected to attain the desired formation while reaching the target region and simultaneously ensuring collision and obstacle avoidance. To tackle this
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Novel parameter estimation method for the systems with colored noises by using the filtering identification idea Syst. Control Lett. (IF 2.6) Pub Date : 2024-03-14 Ling Xu, Feng Ding, Xiao Zhang, Quanmin Zhu
Compared with the systems with white noise disturbances, the parameter identification of the systems with colored noises (i.e., correlated noises) is more difficult. In this letter, we use the model transformation to study the identification problem for the systems with colored noises by using the filtering identification idea. The basic idea is to transform a system with colored noise into two identification
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Highly-efficient filtered hierarchical identification algorithms for multiple-input multiple-output systems with colored noises Syst. Control Lett. (IF 2.6) Pub Date : 2024-03-14 Haoming Xing, Feng Ding, Xiao Zhang, Xiaoli Luan, Erfu Yang
Multiple-input multiple-output (MIMO) systems have extensive applications in industrial processes and systems engineering. This letter applies the filtering identification idea to establish a filtered identification model and investigate a filtered auxiliary model-based recursive least squares (F-AM-RLS) algorithm for parameter identification of MIMO systems with colored noises. To improve the computational
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Dynamic output feedback control of switched systems: A dynamic event-triggered sampling control scheme Syst. Control Lett. (IF 2.6) Pub Date : 2024-03-08 Zhengbao Cao, Jun Fu
A dynamic event-triggered sampling scheme for dynamic output feedback control for a class of switched systems is proposed, where the triggering mechanism can exclude the Zeno phenomenon even if the state of the switched systems is within the output kernel space, and subsystems of the resulting closed-loop switched systems are not necessarily required to be stable. The proposed method can guarantee
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Feedback rectifiable pairs and stabilization of switched linear systems Syst. Control Lett. (IF 2.6) Pub Date : 2024-03-07 M.C. Honecker, H. Gernandt, K. Wulff, C. Trunk, J. Reger
We address the feedback design problem for switched linear systems. In particular we aim to design a switched state-feedback such that the resulting closed-loop subsystems share the same eigenstructure. To this effect we formulate and analyse the feedback rectification problem for pairs of matrices. We present necessary and sufficient conditions for the feedback rectifiability of pairs for two subsystems
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High-order Krylov subspace model order reduction methods for bilinear time-delay systems Syst. Control Lett. (IF 2.6) Pub Date : 2024-03-06 Gao-Yuan Cheng, Zhen Miao, Yao-Lin Jiang
Model order reduction methods via high-order Krylov subspace for bilinear time-delay systems are developed in this paper. The proposed methods are based on the expansion of the Taylor series or Laguerre series. The obtained reduced systems can not only match certain expansion coefficients but also preserve the structure of the original system. We also briefly discuss the two-sided projection reduction
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Stochastic LQ optimal control for Markov jumping systems with multiplicative noise using reinforcement learning Syst. Control Lett. (IF 2.6) Pub Date : 2024-03-05 Linwei Ye, Zhonggai Zhao, Fei Liu
The stochastic linear quadratic (LQ) problem of discrete-time linear Markov jumping systems with multiplicative noise is investigated in this paper. Two reinforcement learning algorithms, one model-based and one model-free, are designed. The algorithms can be readily adapted to handle nonlinear cases by employing an appropriate function approximator. In the linear case, the network structure is designed
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Further results on optimal local and remote control with packet losses and transmission delay Syst. Control Lett. (IF 2.6) Pub Date : 2024-03-04 Yujiao Song, Qingyuan Qi, Yue Sun
In this article, the finite horizon optimal local and remote control (LRC) problem is further investigated for the case that both the packet losses (PL) and the transmission delays (TD) occur over the unreliable uplink channel from the local controller to the remote controller. In terms of the variational technique and the dynamic programming approach, the LRC problem with PL and TD is solved for the
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Assignment of spectrum for time-varying linear control systems via kinematic equivalence Syst. Control Lett. (IF 2.6) Pub Date : 2024-03-04 Pham The Anh, Adam Czornik, Thai Son Doan, Nguyen Thi Thu Suong
In this note, we consider a uniformly completely controllable linear system. For this system, we show the existence of a linear state feedback such that the corresponding closed-loop system is kinematically equivalent to a linear time-invariant system whose spectrum is a prior set of distinct real numbers.
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Finite-step alternating approximately bi-similar symbolic model for Markov jump systems Syst. Control Lett. (IF 2.6) Pub Date : 2024-03-04 Yongzhuang Liu, Yang Song
Establishing a bi-similar abstraction (symbolic model) of control systems has been demonstrated as a viable approach for implementing temporal logic tasks on control systems. Previous research primarily focused on logic tasks over an infinite time horizon. However, practical scenarios often involve control tasks defined within finite time intervals. Hence, this paper addresses the finite-time bi-similar
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Discrete time risk sensitive control problem Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-29 Łukasz Stettner
In the paper adapting Krein Rutman theory we show the existence of solutions to the long run risk sensitive control problem for controlled discrete time Markov processes over locally compact separable metric space. The problem of uniqueness of solutions to suitable Bellman equation is also considered.
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A distributed protocol for finite-time supremum or infimum dynamic consensus: The directed graph case Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-29 Antonio Furchì, Martina Lippi, Alessandro Marino, Andrea Gasparri
This paper proposes a distributed protocol for tracking the global maximum supremum (or minimum infimum) of a set of exogenous time-varying signals. Specifically, each agent has only access to one of these signals and, by implementing the proposed protocol, it is able to track in finite-time the maximum supremum (or the minimum infimum) of the exogenous time-varying signals in a distributed fashion
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Quantized iterative learning control for nonlinear multi-agent systems with initial state error Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-28 Ting Zhang, Ning Li, Jiaxi Chen
This paper proposed a consensus problem for nonlinear multi-agent systems (MAS) with logarithmic quantization and arbitrary initial states. By introducing the quantization, digital communication between signals is realized and the requirement of utilizing the digital channel more effective is also achieved. In order to eliminate the initial state errors introduced by the assumption of any initial value
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Complete type functional approach to input to state stability of time-delay systems Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-28 Marco A. Gomez, Sabine Mondié
This note addresses the study of input to state stability of nonlinear time-delay systems that are linearizable in the first approximation. It is established that, under mild conditions, the so-called complete type functional of the associated linear systems with delay is a Local Input to State Lyapunov–Krasovskii functional. Moreover, this complete type functional, which is fully defined by the delay
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Exact controllability for a Rayleigh beam with piezoelectric actuator Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-23 Yubo Bai, Christophe Prieur, Zhiqiang Wang
In this paper, exact controllability problem for a Rayleigh beam with piezoelectric actuator is considered. Controllability results show that the space of controllable initial data depends on the regularity of the control and the location of the actuator. Two different spaces of control, and , correspond to two different controllability properties, -controllability and -controllability, respectively
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Exact representation and efficient approximations of linear model predictive control laws via HardTanh type deep neural networks Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-22 Daniela Lupu, Ion Necoara
Deep neural networks have revolutionized many fields, including image processing, inverse problems, text mining and more recently, give very promising results in systems and control. Neural networks with hidden layers have a strong potential as an approximation framework of predictive control laws as they usually yield better approximation quality and smaller memory requirements than existing explicit
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Learning-based optimal control of linear time-varying systems over large time intervals Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-22 Vasanth Reddy, Almuatazbellah Boker, Hoda Eldardiry
We solve the problem of two-point boundary optimal control of linear time-varying systems with unknown model dynamics using reinforcement learning. Leveraging singular perturbation theory techniques, we transform the time-varying optimal control problem into two time-invariant subproblems. This allows using an off-policy iteration method to learn the controller gains. We show that the performance of
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Event-triggered neural adaptive tracking control for output constrained nonlinear multi-agent systems with unmodeled dynamics and unknown signs Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-22 Feisheng Yang, Zhucheng Liu, Yu Zhao
This paper studies the distributed cooperative control problem of uncertain non-strict feedback nonlinear multi-agent systems including time-varying output constraints, unmodeled state dynamics and unknown control directions. By introducing two universally constrained functions and using error coordinate transformation, the output constraints are effectively handled. Meanwhile, the convergence of cooperative
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Reinforcement learning for linear exponential quadratic Gaussian problem Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-21 Jing Lai, Junlin Xiong
This paper addresses the infinite-horizon linear exponential quadratic Gaussian problem for a class of stochastic systems with additive noise. A model-free generalized policy iteration reinforcement learning algorithm is proposed to estimate the kernel matrices and update the control gains using the data along system trajectories. The estimation errors of the kernel matrices are proven to be bounded
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Performance-variable decomposition in retrospective cost adaptive control of linear time-varying systems Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-19 Sneha Sanjeevini, Dennis S. Bernstein
This paper develops a discrete-time, linear time-varying (DTLTV) framework for analyzing the retrospective performance variable used in retrospective cost adaptive control (RCAC). This is done by first developing expressions for transforming between DTLTV state–space models and DTLTV input–output models. These expressions are then used to derive an additive decomposition of the retrospective performance
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Reinforcement learning for distributed transient frequency control with stability and safety guarantees Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-19 Zhenyi Yuan, Changhong Zhao, Jorge Cortés
This paper proposes a reinforcement learning-based approach for optimal transient frequency control in power systems with stability and safety guarantees. Building on Lyapunov stability theory and safety-critical control, we derive sufficient conditions on the distributed controller design that ensure the stability and transient frequency safety of the closed-loop system. Our idea of distributed dynamic
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Simultaneous input and state estimation with multi-step delay for linear stochastic systems based on infinity filtering and smoothing Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-19 Bo Ding, Zhengyu Ren, Huajing Fang
This paper presents a novel method for simultaneous unknown input and state estimation (UISE) with multi-step delay for linear stochastic systems with rank-deficient direct feed-through matrix. The augmented Kalman filter and smoothing are established with an input model, where the input signal follows a specific probability distribution with finite covariance. Then, in light of the established properties
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Deadzone-adapted disturbance suppression control for global practical IOS and zero asymptotic gain to matched uncertainties Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-17 Iasson Karafyllis, Miroslav Krstic
For control-affine nonlinear systems with a disturbance and unknown parameters satisfying a matching condition but not having a known bound, we introduce a direct adaptive control scheme with three design elements: (a) nonlinear damping, (b) single-gain adjustment, and (c) deadzone in the update law. Combining these three ingredients for the first time, we guarantee the following previously unattained
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Reinforcement learning in non-Markovian environments Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-16 Siddharth Chandak, Pratik Shah, Vivek S. Borkar, Parth Dodhia
Motivated by the novel paradigm developed by Van Roy and coauthors for reinforcement learning in arbitrary non-Markovian environments, we propose a related formulation and explicitly pin down the error caused by non-Markovianity of observations when the Q-learning algorithm is applied to this formulation. Based on this observation, we propose that the criterion for agent design should be to seek good
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Robust output regulation for uncertain nonlinear minimum phase systems under unknown control direction Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-15 Yizhou Gong, Fanglai Zhu, Yang Wang
This paper investigates the problem of disturbance rejection for SISO uncertain nonlinear minimum phase systems perturbed by an external disturbance under the framework of robust output regulation. The model parameters of the systems in question are uncertain, including the control direction. In addition, the external disturbance can be structured or unstructured but bounded. Towards this end, a novel
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Existence of open-loop equilibria in differential games with impulsive effects suffered by logic choice Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-14 Yuting Xue, Jitao Sun, Yu Zhang
This paper proposes a novel class of differential games where one player adopts piecewise constant strategies and the other implements impulse suffered by logic choice. To the best of our knowledge, the discussion in this paper has been the first try to investigate differential games with impulsive effects suffered by logic choice. Based on semi-tensor product, impulsive effects suffered by logic choice
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Forward–backward stochastic evolution equations in infinite dimensions and application to LQ optimal control problems Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-12 Maozhong Xu, Maoning Tang, Qingxin Meng
This paper focuses on the study of forward–backward stochastic evolution equations (FBSEEs), which are a class of nonlinear fully coupled forward–backward stochastic differential equations (FBSDEs), in infinite dimensions. Drawing inspiration from various linear-quadratic (LQ) optimal control problems, we apply a set of domination-monotonicity conditions that are more relaxed compared to general conditions
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Non-overshooting control of nonlinear pure-feedback systems Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-09 F, u, j, i, n, , J, i, a
In this paper, the non-overshooting tracking control problem of nonlinear pure-feedback systems is studied. From the model, nonlinear pure-feedback systems are more general than nonlinear strict-feedback systems. In this way, the nonlinear pure-feedback system can express the physical system that the strict-feedback system cannot. Therefore, it is more meaningful to study the nonlinear pure-feedback
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Composite hierarchical hybrid anti-disturbance control for Markovian jump systems with event-triggered disturbance Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-08 Xiuming Yao, Xinyu Wen
This paper addresses the hybrid control for Markovian jump systems subject to multiple disturbances. One disturbance is an energy bounded signal, while the other is an event-triggered sinusoidal disturbance with unknown frequencies and amplitudes. Based on the framework of disturbance observer, we firstly propose novel proportional integral cascaded observers to estimate the unknown sinusoidal disturbance
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Distributed constrained optimization for multi-agent networks with communication delays under time-varying topologies Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-07 Yuanyuan An, Aiping Wang, Xufeng Zhang, Feng Xiao
In this paper, a distributed constrained optimization problem for discrete-time multi-agent systems with time-varying directed graphs is studied and a distributed projection subgradient algorithm is proposed. Furthermore, we investigate the scenario involving time delays in agent interactions and use an augmented matrix method to deal with delays. Specifically, we introduce virtual nodes along with
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[formula omitted] model order reduction: A relative error setting Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-06 Umair Zulfiqar, Xin Du, Qiu-Yan Song, Muwahida Liaquat, Victor Sreeram
In dynamical system theory, the process of obtaining a reduced-order approximation of the high-order model is called model order reduction. The closeness of the reduced-order model to the original model is generally gauged by using system norms of additive or relative error systems. The relative error is a superior criterion to the additive error in assessing accuracy in many applications like reduced-order
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Feasibility governor for MPC with disturbance preview information Syst. Control Lett. (IF 2.6) Pub Date : 2024-02-06 Jordan Leung, Ilya Kolmanovsky
This paper presents a feasibility governed preview MPC (PMPC) strategy for the control of constrained linear systems with previewed disturbances. The feasibility governor (FG) minimally modifies the supplied reference command so that the predicted terminal state of the PMPC policy remains in a robustly control invariant terminal set. As a result, recursively feasibility of the combined FG-PMPC strategy
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Repulsive Markovian models for opinion dynamics Syst. Control Lett. (IF 2.6) Pub Date : 2024-01-31 Carl-Johan Heiker, Elisa Gaetan, Laura Giarré, Paolo Falcone
We consider the problem of modeling a decision-making process in a network of stochastic agents, each described as a Markov chain. Two approaches for describing disagreement among agents as social forces are studied. These forces modulate the rates at which agents transition between decisions. We define conditions between the two disagreement models and derive a method for obtaining two model instances
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On the convergence of degenerate risk sensitive filters Syst. Control Lett. (IF 2.6) Pub Date : 2024-01-29 Mattia Zorzi, Shenglun Yi
We propose a degenerate risk sensitive filter which is an extension of the risk sensitive filtering paradigm to the case in which the evolution of the covariance matrix of the prediction error can be singular. We show that the corresponding risk sensitive Riccati iteration, describing the evolution of the covariance matrix of the prediction error, converges if the risk sensitivity parameter and the
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On the stability of distance-based formation control with minimally globally rigid graphs Syst. Control Lett. (IF 2.6) Pub Date : 2024-01-28 Farid Sahebsara, Marcio de Queiroz
Flip ambiguities are a notorious issue with distance-based formation control over minimally rigid graphs, owing to the presence of multiple equilibrium points in the closed-loop formation dynamics. This paper introduces a method for proving the stability of such controllers over minimally rigid graphs to avoid these ambiguities in 2D. The proposed method involves embedding the 2D formation in 3D and
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Pseudo-Bautin bifurcation for a non-generic family of 3D Filippov systems Syst. Control Lett. (IF 2.6) Pub Date : 2024-01-25 José Manuel Islas, Juan Castillo, Fernando Verduzco
We consider the non-generic family of piecewise linear systems, with a discontinuity plane that have two parallel tangency lines, such that the region between them is the sliding region. It is known that the change of stability of the sliding region gives rise to the called pseudo-Hopf bifurcation. The stability of the crossing limit cycle that emerges from this bifurcation mechanism is characterized
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Value iteration for LQR control of unknown stochastic-parameter linear systems Syst. Control Lett. (IF 2.6) Pub Date : 2024-01-24 Wenwu Fan, Junlin Xiong
This paper focuses on the linear-quadratic optimal control problem for unknown stochastic-parameter linear systems using reinforcement learning methods. Based on the second moments of random system matrices, a model-based value iteration algorithm is proposed to solve the problem and is proved to be convergent by using the contraction mapping theorem. For the case without knowing any information about
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Second-order necessary condition for partially observed stochastic system with random jumps Syst. Control Lett. (IF 2.6) Pub Date : 2024-01-22 Tian Chen, Zongyuan Huang, Zhen Wu
In this paper, we investigate the singular optimal control problem for partially observed stochastic control system with random jumps. In our model, the control variable is allowed to enter all coefficients of the state equation and observation equation and the control domain is assumed to be convex. In this case, we obtain the integral-type second-order necessary condition for singular optimal control
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Insights on equidistributed real spectral values in second-order delay systems: Perspectives in partial pole placement Syst. Control Lett. (IF 2.6) Pub Date : 2024-01-22 Timothée Schmoderer, Islam Boussaada, Silviu-Iulian Niculescu, Fazia Bedouhene
In this work, we show that the coexistence of the maximal number of real spectral values of generic single-delay retarded second-order differential equations guarantees the realness of the rightmost spectral value. From a control theory standpoint, this entails that a delayed proportional-derivative (PD) controller can stabilize a delayed second-order differential equation. By assigning the maximum