Data informativity is a crucial property to ensure the consistency of the prediction error estimate. This property has thus been extensively studied in the open-loop and in the closed-loop cases, but has only been briefly touched upon in the dynamic network case. In this paper, we consider the prediction error identification of the modules in a row of a dynamic network using the full input approach

The inverse linear-quadratic optimal control problem is a system identification problem whose aim is to recover the quadratic cost function and hence the closed-loop system matrices based on observations of optimal trajectories. In this paper, the discrete-time, finite-horizon case is considered, where the agents are also assumed to be homogeneous and indistinguishable. The latter means that the agents

This paper studies the relationship between the differential privacy of initial values and the observability for general linear dynamical systems with Gaussian process and sensor noises, where certain initial values are privacy-sensitive and the rest is assumed to be public. First of all, necessary and sufficient conditions are established for preserving the differential privacy and unobservability

This paper studies the problem of optimal deception attacks on remote state estimation, where an interval χ2 detector is deployed to reveal anomalies. The information-based attack policy that can bypass the anomaly detector and cause the maximum estimation quality degradation is derived. For both attacks with strict and relaxed stealthiness, the optimal compromised measurements can be designed with

We consider sliding-mode control systems subject to unmatched perturbations. Classical first-order sliding-mode techniques are capable to compensate unmatched perturbations if differentiations of the output of sufficiently high order are included in the sliding variable. For such perturbations it is commonly assumed that they do not affect the relative degree of the system. In this contribution we

Electric vehicle charging facilities offer their capacity constrained electric charge and parking to users for a fee. As electric vehicle adoption grows, so too does the potential for excessive resource utilization. In this paper, we study how prices set by the charging facility impact the likelihood that specified resource utilization levels are exceeded. Specifically, we present probabilistic bounds

We study a class of cooperative multi-agent optimization problems, where each agent is associated with a local action vector and a local cost, and the goal is to cooperatively find the joint action profile that minimizes the average of the local costs. We consider the setting where gradient information is not readily available, and the agents only observe their local costs incurred by their actions

Without necessarily assuming that switching sequences are fixed, a dynamic optimization method is proposed for optimal control of state-dependent switched systems. First, a parameterization method is developed to parameterize the switching instants and control vectors to facilitate the calculation of the gradient information, and then the original problem becomes a finite-dimensional mixed discrete–continuous

The notion of reproducing kernel Hilbert space (RKHS) has emerged in system identification during the past decade. In the resulting framework, the impulse response estimation problem is formulated as a regularized optimization defined on an infinite-dimensional RKHS consisting of stable impulse responses. The consequent estimation problem is well-defined under the central assumption that the convolution

The problem of differentiating a function with bounded second derivative in the presence of bounded measurement noise is considered in both continuous-time and sampled-data settings. Fundamental performance limitations of causal differentiators, in terms of the smallest achievable worst-case differentiation error, are shown. A robust exact differentiator is then constructed via the adaptation of a

This paper considers the problem of linear quadratic tracking control (LQTC) with a discounted cost function for unknown systems. The existing design methods often require the discount factor to be small enough to guarantee the closed-loop stability. However, solving the discounted algebraic Riccati equation (ARE) may lead to ill-conditioned numerical issues if the discount factor is too small. By

This paper is dedicated to the switched systems suffering asynchronous denial-of-service (DoS) attacks that compromise sensor–controller and controller–actuator channels independently. By taking into account the energy constraints, the duration of DoS attacks has different maximum bounds for different channels. To eliminate the negative effect of DoS attacks, an active control strategy consisting of

This note presents some further results concerning the identification of the nonlinear state-space model (NSSM) based on the meaningful conclusions in the above paper. We use the heavy-tailed Student’s t-distribution to model the system noises and the parameter estimation problem is solved via the expectation maximization (EM) algorithm wherein the decomposition of t-distribution as well as the particle

This paper aims to deal with the control analysis and synthesis problem of data-driven learning, regardless of unknown plant models and iteration-varying uncertainties. For the tracking of any desired target, a Kalman state–space approach is presented to transform it into two robust stability problems, which bridges a connection between data-driven control and model-based control. The proposed approach

The task of inducing, via continuous static state-feedback control, an asymptotically stable heteroclinic orbit in a nonlinear control system is considered in this paper. The main motivation comes from the problem of ensuring convergence to a so-called point-to-point maneuver in an underactuated mechanical system. Namely, to a smooth curve in its state–control space which is consistent with the system

This paper addresses the output feedback stabilization of an ODE–PDE cascade. The PDE takes the form of a 1-D reaction–diffusion equation. The output of the ODE enters into the PDE via a Dirichlet/Neumann/Robin boundary condition. It is assumed that both the output of the ODE and the output of the PDE, selected as a boundary Dirichlet trace, are available for feedback control. The proposed control

This paper investigates the disturbance decoupled secure state estimation problem of a linear system in the presence of sparse sensor attacks and unknown disturbances, where disturbance decoupled state estimation means that the resulting estimate errors do not depend on the value of disturbances. First, the solvability of the disturbance decoupled secure state estimation problems is analyzed by introducing

This paper deals with general bilinear feasibility problems. A nonlinear transformation is introduced that reformulates a general bilinear feasibility problem as a Linear Matrix Inequality (LMI) problem augmented with a single non-convex quadratic constraint. The single non-convex quadratic constraint has a regular concave constraint function. Due to the LMI part of this formulation, it is easier to

In power systems, one wishes to regulate the aggregate demand of an ensemble of distributed energy resources (DERs), such as controllable loads and battery energy storage systems. We propose a notion of predictability and fairness, which suggests that the long-term averages of prices or incentives offered should be independent of the initial states of the operators of the DER, the aggregator, and the

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In this issue of IEEE Control Systems , we speak with Hong Chen, a distinguished professor and the dean of the College of Electronic and Information Engineering at Tongji University in Shanghai, and Randy Freeman, a professor of electrical and computer engineering at Northwestern University in Evanston, IL, USA.

Presents information on the 2022 American Control Conference.

Presents the front cover for this issue of the publication.

Presents the table of contents for this issue of the publication.

Deep learning is impacting control in many ways, if not all deep. For more than a decade, it has reinstated the state-space concept as a central and unifying modeling principle. The magical equation x+ = f ( x, u ) currently dominates IEEE Control Systems Society publications, workshops, and conferences. Once confined to specialized circles of dynamic programming and nonlinear control, it has emerged

Autonomous vehicle technology is advancing rapidly. Their control capabilities often rely on high-bandwidth state estimation incorporating inertial measurements. High-performance state estimation incorporates inertial measurement error models through the process of state augmentation to enable on-the-fly instrument calibration. The feature article “Inertial Measurement Unit Error Modeling Tutorial”

“An exciting journey has started for me!” In this way, I began my inaugural “President’s Message” column [1] .

In this issue, “25 Years Ago” revisits the article “Controlling Buildings: A New Frontier in Feedback,” by B.F. Spencer Jr. and Michael K. Sain in IEEE Control Systems Magazine , vol. 17, no. 6, pp. 19–35, 1997. Below is an excerpt from the article.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Presents information on the CSS Technical Committee on Control Education.

Presents information on the Technical Committee on Discrete Event System.

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Emerging mobility systems, for example, connected and automated vehicles (CAVs), shared mobility, and electric vehicles, mark a paradigm shift in which myriad opportunities exist for users to better monitor transportation network conditions and make optimal operating decisions to improve safety and reduce pollution, energy consumption, and travel delays [1] . As we move to increasingly complex emerging

Q. How did your education and early career lead to your initial and continuing interest in the control field?

Q. How did your education and early career lead to your initial and continuing interest in the control field?

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Autonomous vehicle technology is rapidly advancing (see “Summary”). A key enabling factor is the advancing capabilities and declining cost of computing and sensing systems that enable sensor fusion for awareness of the vehicle’s state and surroundings (see “Nontechnical Article Summary”). For control purposes, the vehicle’s state must be estimated accurately, reliably, at a sufficiently high sample

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

The surge of interest in machine learning has led to increased emphasis on the value of accurate, efficient surrogate models. The book is divided into four parts. Part 1, consisting of Chapters 1 and 2, introduces the reader to the basic ideas underlying general model reduction and provides the relevant system-theoretic background needed for the remainder of the book. Part 2, consisting of Chapters

Presents the recipients of CSS TC Outstanding Student Paper Prize awards.

Presents information on the IEEE Conference on Control Technology and Applications.

Presents information on the 2022 International Conference on Unmanned Aircraft Systems.

Presents the CSS calendar of events and meetings.

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

Reports on the Minutes of the Control Systems Society Board of Governors Meeting June 7, 2022.

Reports on the IEEE CSS Board of Governors Meeting June 7, 2022.

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With society's wide-scale adoption of information technology, significant information about borrowers is distributed across various parties, information that can be jointly used to improve credit scoring. However, use of such information faces many challenges, such as the problems of preserving privacy and information redundancy. To address these challenges in leveraging multi-source information for

Ensuring the credibility of online consumer reviews (OCRs) is a growing societal concern. However, the problem of fake reviewers on online platforms significantly influences e-commerce authenticity and consumer trust. Existing studies for fake reviewer detection mainly focus on deriving novel behavioral and linguistic features. These features require extensive human labor and expertise, placing a heavy

We consider feedback control systems where sensor readings and actuator commands may be compromised by an attacker intending to damage the system. We study this problem at the supervisory layer of the control system, using discrete event systems techniques. The attacker can edit the outputs from the sensors of the system before they reach the supervisory controller as well as it can edit actuator commands

In this paper a methodology to identify several points of the frequency response of a system using a single experiment is proposed. The identification is performed using the information obtained from an asymmetric relay feedback experiment. The frequency response points that are estimated correspond to the fundamental oscillation frequency induced by the asymmetric relay and its harmonics. The method

This paper considers the linear–quadratic (LQ) leader–follower Stackelberg differential game for Markov jump-diffusion stochastic differential equations (SDEs). We first obtain the open-loop type optimal solutions for the leader and the follower by establishing the general stochastic maximum principle for (indefinite) LQ control with Markovian jumps. Then we obtain the state-feedback representation

In this paper, for a linear system with unknown input, a novelty unknown input observer (UIO) which can produce the asymptotic system state estimation and unknown input reconstruction simultaneously via interval observer is developed. Firstly, under the assumption that the boundary of the unknown input is known, the interval estimation of the output vector is obtained by designing an interval observer

Constraints on the feedback structure arise in many control systems due to implementing cost, hardware limitations and operational reliability. The parameter space method aims to solve the robust structured controller design problems based on a convex reformulation technique. Despite its attractiveness, the structural constraints are limited to be either decentralized or linear dependence among entries

In this paper, second-order multi-agent systems with intentionally induced delay are studied, which cannot achieve consensus with a non-delay position-based protocol. Under the proposed distributed protocol with the current and outdated position states, the crossing frequencies and crossing delays of the related quasipolynomial of the delayed systems are identified. By determining the crossing directions

This paper proposes Asynchronous Triggered Gradient Tracking, i.e., a distributed optimization algorithm to solve consensus optimization over networks with asynchronous communication. As a building block, we devise the continuous-time counterpart of the recently proposed (discrete-time) distributed gradient tracking called Continuous Gradient Tracking. By using a Lyapunov approach, we prove exponential

This work is concerned with the event-triggered sliding mode control (SMC) problem for 2D FMII systems. Firstly, the partially ordered sequence is defined, and then, a bidirectional dynamic event-triggered mechanism is introduced into the S/C channel to reduce the unnecessary transmission. The evolutionary directions of both the triggered sequences and dynamic variables are consistent with the evolution

This paper studies the edge controllability of signed networks, where the dynamics taking place on edges and the interaction type over each edge can be cooperative or antagonistic. First, the edge controllable subspace is studied quantitatively from the graph-theoretic perspective. And the lower and upper bounds for the dimension of edge controllable subspace are derived, respectively. Second, the

The Proof-of-Stake (PoS) protocol is booming in blockchain networks because of excessive energy consumption and slow block generation associated with the Proof-of-Work (PoW) protocol. In terms of transaction settlement, does the PoS protocol perform better than PoW? We build a transaction settlement model based on the PoS blockchain, describing how the staking income and costs affect settlement performance