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Event-Triggered Sampling Problem for Exponential Stability of Stochastic Nonlinear Delay Systems Driven by Le ´vy Processes IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2024-08-22 Quanxin Zhu
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Global Asymptotic Stabilization of the Double Integrator System with Output Saturation IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2024-08-22 Yuhui Li, Yuanlong Li, Zongli Lin
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Coarse-graining Complex Networks for Control Equivalence IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2024-08-22 Daniele Toller, Mirco Tribastone, Max Tschaikowski, Andrea Vandin
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Cooperation Detection and Tracking of Underwater Target via Aerial-Surface-Underwater Vehicles IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2024-08-22 Jing Yan, Jingsheng Lin, Xian Yang, Cailian Chen, Xinping Guan
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Krasovskii Passivity for Sampled-Data Stabilization and Output Consensus IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2024-08-22 Yu Kawano, Alessio Moreschini, Michele Cucuzzella
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Robust Data-Driven Control of Discrete-Time Linear Systems with Errors in Variables IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2024-08-22 Jared Miller, Tianyu Dai, Mario Sznaier
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Decay Rate Assignment through Multiple Spectral Values in Delay Systems IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2024-08-21 Islam Boussaada, Guilherme Mazanti, Silviu-Iulian Niculescu, Wim Michiels
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Event-Triggered State Interval Estimation and Fault-Tolerant Control for Multi-Agent Systems Under Deception Attacks IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2024-08-21 Meng Zhou, Haicheng Li, Tonglai Xue, Jing Wang, Tarek Raïssi
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Distributed Momentum Based Multi-Agent Optimization with Different Constraint Sets IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2024-08-19 Xu Zhou, Zhongjing Ma, Suli Zou, Kostas Margellos
This paper considers a class of consensus optimization problems over a time-varying communication network wherein each agent can only interact with its neighbours. The target is to minimize the summation of all local and possibly non-smooth objectives in the presence of different constraint sets per agent. To achieve this goal, we propose a novel distributed heavy-ball algorithm that combines the subgradient
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Data-Driven Minimum Entropy Control for Stochastic Nonlinear Systems Using the Cumulant-Generating Function IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2022-09-20 Qichun Zhang, Jianhua Zhang, Hong Wang
This article presents a novel minimum entropy control algorithm for a class of stochastic nonlinear systems subjected to non-Gaussian noises. The entropy control can be considered as an optimization problem for the system randomness attenuation, but the mean value has to be considered separately. To overcome this disadvantage, a new representation of the system stochastic properties was given using
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Reduced Order Modeling of Diffusively Coupled Network Systems: An Optimal Edge Weighting Approach IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2022-08-22 Xiaodong Cheng, Lanlin Yu, Dingchao Ren, Jacquelien M.A. Scherpen
This article studies reduced-order modeling of dynamic networks with strongly connected topology. Given a graph clustering of an original large-scale network, we construct a quotient graph with less number of vertices, where the edge weights are parameters to be determined. The model of a reduced network is thereby obtained with parameterized system matrices, and then, an edge weighting procedure is
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Minimization of Sensor Activation in Decentralized Discrete Event Systems IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-11-01 Xiang Yin, Stephane Lafortune
We investigate the problem of dynamic sensor activation for decentralized decision making in partially observed discrete-event systems, where the system is monitored by a set of agents. The sensors of each agent can be turned on/off online dynamically according to a sensor activation policy. We define a general decentralized decision-making problem called the decentralized state disambiguation problem
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Approximate Projection Methods for Decentralized Optimization with Functional Constraints IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-10-01 Soomin Lee, Michael M. Zavlanos
We consider distributed convex optimization problems that involve a separable objective function and nontrivial functional constraints, such as linear matrix inequalities. We propose a decentralized and computationally inexpensive algorithm, which is based on the concept of approximate projections. Our algorithm is one of the consensus-based methods in that, at every iteration, each agent performs
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Observability and Controllability Analysis of Linear Systems Subject to Data Losses IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-10-01 Raphael M. Jungers, Atreyee Kundu, W. P. M. H. Heemels
We provide algorithmically verifiable necessary and sufficient conditions for fundamental system theoretic properties of discrete-time linear, systems subject to data losses. More precisely, the systems in our modeling framework are subject to disruptions (data losses) in the feedback loop, where the set of possible data loss sequences is captured by an automaton. As such, the results are applicable
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Entropy and Minimal Bit Rates for State Estimation and Model Detection IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-10-01 Daniel Liberzon, Sayan Mitra
We study a notion of estimation entropy for continuous-time nonlinear systems, formulated in terms of the number of system trajectories that approximate all other trajectories up to an exponentially decaying error. We also consider an alternative definition of estimation entropy, which uses approximating functions that are not necessarily trajectories of the system, and show that the two entropy notions
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Numerical Optimal Control with Periodicity Constraints in the Presence of Invariants IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Sebastien Gros, Mario Zanon
Periodic optimal control problems (POCPs) based on dynamic models holding invariants are often problematic to treat using standard numerical methods. The difficulty stems from a failure of standard constraint qualifications and typically hinders the convergence of the numerical solver, or even defeats it. Optimization problems having weak constraint qualifications can be treated using dedicated solvers
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Passivity-Based Design for Event-Triggered Networked Control Systems IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Arash Rahnama, Meng Xia, Panos J. Antsaklis
In this paper, we introduce a passivity-based design framework for event-triggered networked control systems. We consider the effects of network-induced time delays, signal quantization, and data loss in communication links between the plant and controller and show $L_2$ -stability and robustness for the control design. We introduce simple asynchronous triggering conditions that do not rely on the
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Gradient-Based Myopic Allocation Policy: An Efficient Sampling Procedure in a Low-Confidence Scenario IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Yijie Peng, Chun-Hung Chen, Michael C. Fu, Jian-Qiang Hu
In this note, we study a simulation optimization problem of selecting the alternative with the best performance from a finite set, or a so-called ranking and selection problem, in a special low-confidence scenario. The most popular sampling allocation procedures in ranking and selection do not perform well in this scenario, because they all ignore certain induced correlations that significantly affect
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Time-Inconsistent Mean-Field Stochastic LQ Problem: Open-Loop Time-Consistent Control IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Yuan-Hua Ni, Ji-Feng Zhang, Miroslav Krstic
This paper is concerned with the open-loop time-consistent solution of time-inconsistent mean-field stochastic linear-quadratic (LQ) optimal control. Different from standard stochastic linear-quadratic problems, both the system matrices and the weighting matrices are depending on the initial times, and the conditional expectations of the control and state enter quadratically into the cost functional
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Dynamic Models of Appraisal Networks Explaining Collective Learning IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Wenjun Mei, Noah E. Friedkin, Kyle Lewis, Francesco Bullo
This paper proposes models of learning processes in teams of individuals who collectively execute a sequence of tasks and whose actions are determined by individual skill levels and networks of interpersonal appraisals and influence. The closely-related proposed models have increasing complexity, starting with a centralized manager-based assignment and learning model, and finishing with a social model
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Decentralized Supervisory Control of Networks of Nonlinear Control Systems IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Giordano Pola, Pierdomenico Pepe, Maria Domenica Di Benedetto
In this paper, we propose decentralized control of networks of discrete-time nonlinear control systems, enforcing complex specifications expressed in terms of regular languages, within any desired accuracy. As discussed in the paper, regular languages are useful to model a rather wide variety of complex specifications for control systems. The design of decentralized controllers is based on formal methods
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Infinite Time Horizon Maximum Causal Entropy Inverse Reinforcement Learning IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Zhengyuan Zhou, Michael Bloem, Nicholas Bambos
Inverse reinforcement learning (IRL) attempts to use demonstrations of “expert” decision making in a Markov decision process to infer a corresponding policy that shares the “structured, purposeful” qualities of the expert's actions. In this paper, we extend the maximum causal entropy framework, a notable paradigm in IRL, to the infinite time horizon setting. We consider two formulations (maximum discounted
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Navigation Functions for Convex Potentials in a Space with Convex Obstacles IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Santiago Paternain, Daniel E. Koditschek, Alejandro Ribeiro
Given a convex potential in a space with convex obstacles, an artificial potential is used to navigate to the minimum of the natural potential while avoiding collisions. The artificial potential combines the natural potential with potentials that repel the agent from the border of the obstacles. This is a popular approach to navigation problems because it can be implemented with spatially local information
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Gaussian Process Quadrature Moment Transform IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Jakub Pruher, Ondrej Straka
Computation of moments of transformed random variables is a problem appearing in many engineering applications. The current methods for moment transformation are mostly based on the classical quadrature rules, which cannot account for the approximation errors. Our aim is to design a method for moment transformation of Gaussian random variables, which accounts for the error in the numerically computed
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Stability Analysis for Continuous-Time Switched Systems with Stochastic Switching Signals IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Xiaotai Wu, Yang Tang, Jinde Cao, Xuerong Mao
This paper is concerned with the stability problem of randomly switched systems. By using the probability analysis method, the almost surely globally asymptotical stability and almost surely exponential stability are investigated for switched systems with semi-Markovian switching, Markovian switching, and renewal process switching signals, respectively. Two examples are presented to demonstrate the
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Control Strategies for Non-zero Set-point Regulation of Linear Impulsive Systems IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Pablo S. Rivadeneira, Antonio Ferramosca, Alejandro H. Gonzalez
Despite its potential use in several meaningful problems linear impulsive systems have not been extensively studied to account for dynamics in which the equilibria are out of the origin. In this work a novel characterization of the system equilibria and invariant regions—derived from the definition of two underlying discrete-time systems—is given, and based on this characterization, an unconstrained
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Optimal Computing Budget Allocation to Select the Non-dominated Systems - a Large Deviations Perspective IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Juxin Li, Weizhi Liu, Giulia Pedrielli, Loo Hay Lee, Ek Peng Chew
We consider the optimal computing budget allocation problem to select the nondominated systems on finite sets under a stochastic multi-objective ranking and selection setting. This problem has been addressed in the settings of correct selection guarantee when all the systems have normally distributed objectives with no correlation within and between solutions. We revisit this problem from a large deviation
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Switching Stochastic Nonlinear Systems with Application to an Automotive Throttle IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Alessandro N. Vargas, Eduardo F. Costa, Leonardo Acho, Joao B. R. do Val
This paper presents results to assure the almost sure stability of switching stochastic nonlinear systems. The switching rule governing the parameters of the system is driven by independent and identically distributed random variables. In this scenario, we prove that the switching nonlinear system is almost surely stable when appropriate matrices have spectral radius less than one. The result is particularly
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Tracking a Diffusing Three-Dimensional Source via Nonholonomic Extremum Seeking IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Trevor T. Ashley, Sean B. Andersson
One method for autonomously exploring unknown environments is to treat the environment as a scalar potential field. In this scenario, one or more robots acquire measurements of the field (e.g., radiation, temperature, or carbon dioxide concentrations) and use those measurements to guide their path as they explore. An important behavior robots may need is that of extremum seeking—that is, the ability
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Quasi-Continuous MIMO Sliding-Mode Control IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Arie Levant, Boris Shustin
High-order sliding-mode (HOSM) control is called quasi-continuous (QC), if it remains continuous everywhere except the HOSM set, where the sliding variables and their derivatives vanish. Such sliding-mode (SM) control features less chattering. Homogeneous QC SM control is designed for the general uncertain multi-input multi-output case and provides any predefined control smoothness level outside of
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Stochastic Feedback Based Kalman Filter for Nonlinear Continuous-Discrete Systems IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-09-01 Jiaolong Wang, Jihe Wang, Dexin Zhang, Xiaowei Shao
For continuous-discrete filtering with unpredictable approximation errors, by proposing the novel stochastic feedback scheme, this note elaborates a closed-loop adaptive Kalman filter for nonlinear continuous-discrete systems. In conventional filters, unknown approximation errors might arise due to the integration/discretization and linearization of continuous model, and ruin the optimality of Kalman
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Design of Feedback Control Laws for Information Transfer in Spintronics Networks IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Sophie G. Schirmer,Edmond A. Jonckheere,Frank C. Langbein
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Quasi-Time-Dependent Controller and Filter Design for Discrete-Time Switched System with Mode-dependent Average Dwell Time IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Zhongyang Fei, Shuang Shi, Zhenhuan Wang, Ligang Wu
This paper is concerned with dynamic output feedback control for a class of switched systems with mode-dependent average dwell-time switching. By constructing a quasi-time-dependent Lyapunov function, the issues of global uniform asymptotic stability and $\ell _{2}$-gain analysis for the switched system are addressed first. Then, a set of reduced-order output feedback controllers is designed, which
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Event-Triggered Second-Moment Stabilization of Linear Systems under Packet Drops IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Pavankumar Tallapragada, Massimo Franceschetti, Jorge Cortes
This paper deals with the stabilization of linear systems with process noise under packet drops between the sensor and the controller. Our aim is to ensure exponential convergence of the second moment of the plant state to a given bound in finite time. Motivated by considerations about the efficient use of the available resources, we adopt an event-triggering approach to design the transmission policy
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Exponential Stability of Two-Dimensional Homogeneous Monotone Systems with Bounded Directional Delays IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Le Van Hien, Hieu Trinh
One-dimensional (1-D) monotone systems have received considerable attention recently due to their wide applicability and interesting mathematical properties. One of these special properties is that, for LTI monotone systems, exponential stability is insensitive to time-delays. Some extensions to 1-D nonlinear monotone systems based on conditions of homogeneity have also been reported. In this paper
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Optimal Mechanisms for Robust Coordination in Congestion Games IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Philip N. Brown, Jason R. Marden
Uninfluenced social systems often exhibit suboptimal performance; a common mitigation technique is to charge agents specially-designed taxes, influencing the agents' choices and thereby bringing aggregate social behavior closer to optimal. In general, the efficiency guaranteed by a particular taxation methodology is limited by the quality of information available to the tax-designer. If the tax-designer
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L2-gain for Hybrid Linear Systems with Periodic Jumps: A Game Theoretic Approach for Analysis and Design IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Corrado Possieri, Mario Sassano
In this paper, the disturbance attenuation problem is formulated and solved for a class of linear hybrid systems in the presence of periodic jumps. The results are achieved, both in the finite and infinite horizon cases, by borrowing ideas from the theory of dynamic games. In the considered formulation, independent disturbances affecting the continuous-time and the discrete-time components of the hybrid
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Near-Optimal Scheduling for Petri Net Models with Forbidden Markings IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Dimitri Lefebvre
This paper is about control design for discrete event systems modeled with Petri nets. It addresses the problems of reachability and of firing sequence design. The untimed and timed cases are successively studied by searching control sequences from an initial marking to a reference one with length or duration that approach the minimal value, avoiding forbidden states and nonpromising branches. The
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Dynamic Distributed Control for Networks With Cooperative-Antagonistic Interactions IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Deyuan Meng
For cooperative–antagonistic networks, the distributed control problem is solved owing to all static interactions among vertices, expressed conveniently by a communication graph whose edge weights are constant or time-varying numbers. The question asked in this paper is: whether and how can distributed control be achieved in the presence of dynamic interactions that are modeled as edge weights in terms
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The Role of Convexity on Saddle-Point Dynamics: Lyapunov Function and Robustness IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Ashish Cherukuri, Enrique Mallada, Steven Low, Jorge Cortes
This paper studies the projected saddle-point dynamics associated to a convex–concave function, which we term saddle function. The dynamics consists of gradient descent of the saddle function in variables corresponding to convexity and (projected) gradient ascent in variables corresponding to concavity. We examine the role that the local and/or global nature of the convexity–concavity properties of
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Event-based Boundary Control of a Linear $2\times2$ Hyperbolic System via Backstepping Approach IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Nicolas Espitia, Antoine Girard, Nicolas Marchand, Christophe Prieur
In this paper, we introduce an event-based boundary control for a $2\times 2$ coupled linear hyperbolic system. We use a well-established backstepping controller which stabilizes the system along with a dynamic triggering condition which determines when the controller must be updated. The main contributions rely on the definition of an event-based controller under which global exponential stability
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Multi-Pattern Output Consensus in Networks of Heterogeneous Nonlinear Agents with Uncertain Leader: a Nonlinear Regression Approach IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Giacomo Casadei, Daniele Astolfi
In this paper, we consider the problem of consensus of a network of heterogeneous nonlinear agents on a family of different desired trajectories generated by an uncertain leader. We design a set of local reference generators and local controllers, which guarantees that the agents achieve consensus robustly on all possible trajectories inside this family. The design of the local reference generators
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Distributed Algorithms for Solving Convex Inequalities IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Kaihong Lu, Gangshan Jing, Long Wang
In this note, a distributed subgradient-based algorithm is proposed for continuous-time multi-agent systems to search a feasible solution to convex inequalities. The algorithm involves each agent achieving a state constrained by its own inequalities while exchanging local information with other agents under a time-varying directed communication graph. With the validity of a mild connectivity condition
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Model Reference Adaptive Control of 2 x 2 Coupled Linear Hyperbolic PDEs IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Henrik Anfinsen, Ole Morten Aamo
We solve a model reference adaptive control problem for a class of linear $ 2 \times 2$ hyperbolic partial differential equations (PDEs) with uncertain system parameters subject to harmonic disturbances, from a single boundary measurement anticollocated with the actuation. This is done by transforming the system into a canonical form, from which filters are designed so that the states can be expressed
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Asymptotic Consensus on the Average of a Field for Time-Varying Nonlinear Networks under Almost Periodic Connectivity IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Sabato Manfredi, David Angeli
The paper presents new results on asymptotic consensus for continuous time nonautonomous nonlinear networks under almost-periodic interactions. We introduce such consensus algorithms in order to estimate the average of a measured field, despite the presence of limited agents’ interaction (herein represented by almost periodic connectivity). To this end, a suitable notion of integral connectivity is
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H2 Analysis of LTI Systems via Conversion to Externally Positive Systems IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Yoshio Ebihara
Motivated by recent advances in the study of linear time-invariant (LTI) positive systems, we explore analysis techniques of general, not necessarily positive, LTI systems using positive system theory. Even though a positive system is characterized by its peculiar property that its impulse response is nonnegative, we often deal with nonnegative impulse responses even in general LTI system analysis
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Performance Optimization for Timed Weighted Marked Graphs under Infinite Server Semantics IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Zhou He, Zhiwu Li, Alessandro Giua
This paper deals with the performance optimization of resource allocation systems with the aim of maximizing the system's throughput under a given budget for acquiring resources. Resources are assumed to be renewable, i.e., they are not consumed by the operations and become available again after they have been released. The systems under consideration are modeled by a subclass of timed Petri nets called
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$H_2$ Output-Feedback Control with Finite Multiple Measurement Information IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Choon Ki Ahn, Peng Shi, Hongyi Li
This paper proposes a new $H_2$ output-feedback control with finite multiple measurement information for discrete-time systems with disturbances. This control is called an $H_2$ finite multiple measurement output-feedback control (H2FMMOFC). The new control ascertains the $H_2$ performance for disturbances and the equivalence to the $H_2$ state-feedback control without disturbances on a finite measurement
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Bounds on the Smallest Eigenvalue of a Pinned Laplacian Matrix IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Saeed Manaffam, Aman Behal
In this note, we study a networked system with single/multiple pinning. Given a weighted and undirected network, we derive lower and upper bounds on its algebraic connectivity with respect to the reference signal. The bounds are derived by partitioning the network in terms of distance of each node from the pinning set. Upper and lower bounds for two networks with differing topologies are computed to
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Global Asymptotic Stability of a PID Control System with Coulomb Friction IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Andrea Bisoffi, Mauro Da Lio, Andrew R. Teel, Luca Zaccarian
For a point mass subject to Coulomb friction in feedback with a PID controller, we consider a model based on a differential inclusion comprising all the possible magnitudes of static friction during the stick phase and having unique solutions. We study the set of all equilibria and we establish its global asymptotic stability using a discontinuous Lyapunov-like function, and a suitable LaSalle's invariance
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A Cascades Approach to Formation-Tracking Stabilization of Force-Controlled Autonomous Vehicles IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Mohamed Maghenem, Antonio Loria, Elena Panteley
We present a cascades-based controller for the problem of formation-tracking control in a group of autonomous vehicles. We consider general models composed of a velocity kinematics equation and a generic force-balance equation. For each vehicle, a local controller ensures tracking of a reference generated by a leader vehicle. One or many vehicles may have access to the reference trajectories; each
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On Kalman-Consensus Filtering with Random Link Failures over Sensor Networks IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Qinyuan Liu, Zidong Wang, Xiao He, D. H. Zhou
This paper is concerned with the distributed state estimation problem over wireless sensor networks. The communication links are unreliable that are subject to random link failures modeled as a set of independent Bernoulli processes. To estimate the plant state collaboratively, a Kalman-consensus filtering approach is developed where the sensors spread the local information obtained from the Kalman
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Matrix Optimal Mass Transport: a Quantum Mechanical Approach IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Yongxin Chen, Tryphon T. Georgiou, Allen Tannenbaum
In this paper, we describe a possible generalization of the Wasserstein-2 metric, originally defined on the space of scalar probability densities, to the space of Hermitian matrices with trace one and to the space of matrix-valued probability densities. Our approach follows a control-theoretic optimization formulation of the Wasserstein-2 metric, having its roots in fluid dynamics, and utilizes certain
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Distance-based Control of Kn Formations in General Space with Almost Global Convergence IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Myoung-Chul Park, Zhiyong Sun, Brian D. O. Anderson, Hyo-Sung Ahn
In this paper, we propose a distance-based formation control strategy for a group of mobile agents to achieve almost global convergence to a target formation shape provided that the formation is represented by a complete graph, and each agent is governed by a single-integrator model. The fundamental idea of achieving almost global convergence is to use a virtual formation of which the dimension is
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Leader-Following Consensus of Multiple Uncertain Euler-Lagrange Systems Subject to Communication Delays and Switching Networks IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Maobin Lu, Lu Liu
This technical note focuses on the leader-following consensus problem of multiple uncertain Euler–Lagrange systems subject to communication delays and switching networks. By integrating the feedforward control approach with the adaptive control approach, a new adaptive distributed controller is developed. As opposed to the existing literature, our result has its distinct advantages in that it can accommodate
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Two Sided Boundary Stabilization of Heterodirectional Linear Coupled Hyperbolic PDEs IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Jean Auriol, Florent Di Meglio
We solve the problem of stabilizing a general class of linear first-order hyperbolic systems using actuation at both boundaries of the spatial domain. We design a novel Fredholm transformation similarly to backstepping approaches to derive a boundary controller and a boundary observer enabling stabilization by output feedback. This yields an explicit full-state feedback law that achieves the theoretical
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Feedback Particle Filter on Riemannian Manifolds and Matrix Lie Groups IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Chi Zhang, Amirhossein Taghvaei, Prashant G. Mehta
This paper is concerned with the problem of continuous-time nonlinear filtering of stochastic processes evolving on connected Riemannian manifolds without boundary. The main contribution of this paper is to derive the feedback particle filter (FPF) algorithm for this problem. In its general form, the FPF is shown to provide an intrinsic description of the filter that automatically satisfies the geometric
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A Multivariable Stochastic Tracking Controller for Robot Manipulators without Joint Velocities IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Samer S. Saab, Paul Ghanem
The objective of this paper is to design a discrete-time multivariable controller for a class of robot manipulators without using joint velocities while possessing tracking ability and yielding smooth torque signals. The structure of the control law is a proportional derivative (PD) controller plus gravity compensation with some plausible partial compensation of the friction and Coriolis/centripetal
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Comments on "On stabilization of 2D Roesser Models" IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Olivier Bachelier, Wojciech Paszke, Nima Yeganefar, Driss Mehdi
In this note, we clarify the statement given in the above paper, claiming that the condition for state feedback stabilisation tends to necessity. Actually, it is possible to find examples for which the above-mentioned condition introduces a very weak conservatism and hence is not necessary. The source of the conservatism has been identified. Furthermore, we also realized that the condition could be
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Boundary Feedback Stabilization of a Class of Coupled Hyperbolic Equations with Non-local Terms IEEE Trans. Autom. Control (IF 6.2) Pub Date : 2018-08-01 Lingling Su, Jun-Min Wang, Miroslav Krstic
This paper solves the problem of boundary feedback stabilization of a class of coupled ordinary differential equations–hyperbolic equations with boundary, trace, and integral nonlocal terms. Using the backstepping approach, the controller is designed by formulating an integral operator, whose kernel is required to satisfy a coupled hyperbolic partial integral differential equation. By applying the