The axiomatic fully probabilistic design (FDP) of decision strategies strictly extends Bayesian decision making (DM) theory. FPD also models the closed decision loop by a?joint probability density (pd) of all inspected random variables, referred as behaviour. FPD expresses DM aims via an ideal pd of behaviours, unlike the usual DM. Its optimal strategy minimises Kullback–Leibler divergence (KLD) of

The application of regulatory technology (RegTech) for monitoring comprehensive data sources has gained increased importance. Nevertheless, previous research neglects that the output of RegTech applications has to be explainable and non-discriminatory. Within this study, we propose design principles and features for a RegTech approach which provides automated assessments of financial consumer complaints

Crowd testing has been increasingly adopted as a marketing strategy for e-retailers. However, scant academic research empirically addresses the performance of crowd testing from either the platform's or crowd testers' perspectives. This study aims to investigate the determinants of the usefulness of crowd testing reports in order to theoretically demonstrate the significance of crowd testing strategy

This paper deals with continuous-time system identification of multiple-input single-output (MISO) fractional differentiation models. When differentiation orders are assumed to be known, coefficients are estimated using the simplified refined instrumental variable method for continuous-time fractional models extended to the MISO case. For unknown differentiation orders, a two-stage optimization algorithm

Decision-makers in foreign policy and national security are constantly confronted with an adversarial, networked environments. In such an environment, the “entities” (i.e., political establishments and military organizations) to whom those decision-makers are answerable are connected through a web of friendly and adversarial relationships. By a “networked political behavior” means that one’s behavior

In this paper we consider the problem of transmission power allocation for remote estimation of a dynamical system in the case where the estimator is able to simultaneously receive packets from multiple interfering sensors, as it is possible e.g. with the latest wireless technologies such as 5G and WiFi. To this end we introduce a general model where packet arrival probabilities are determined based

With an increasing demand for ensuring the reliability and efficiency of distributed and interactive systems, the model-checking technique has been studied extensively, for which a game-based modeling of the system and a logical specification of the desired properties are two essential parts. Existing studies mainly focused on ideal systems that always guarantee optimal responses and have not considered

To further understand the underlying mechanism of various reinforcement learning (RL) algorithms and also to better use the optimization theory to make further progress in RL, many researchers begin to revisit the linear–quadratic regulator (LQR) problem, whose setting is simple and yet captures the characteristics of RL. Inspired by this, this work is concerned with the model-free design of stochastic

A slight extension of the global Bernard–Praly gradient adaptive observer – originally presented for nonsalient-pole surface Permanent Magnet Synchronous Motors (PMSMs) and recently proved to own local exponential convergence properties under well-known observability conditions – is here designed and proposed for Interior Permanent Magnet Synchronous Motors (IPMSMs) (with relatively small saliency)

This paper focuses on the development of an online data-driven model-based inverse reinforcement learning (MBIRL) technique for linear and nonlinear deterministic systems. Input and output trajectories of an agent under observation, attempting to optimize an unknown reward function, are used to estimate the reward function and the corresponding unknown optimal value function, online and in real-time

This paper is devoted to an N-person partial differential game whose dynamics of the state variable is described by a hyperbolic differential equation with certain boundary and initial conditions while the objective of each player is given by a finite horizon accumulated payoff functional with discounting. We extend the concept of a closed-loop Nash equilibrium for a partial differential game with

Opacity is an important information-flow security property that characterizes the plausible deniability of a dynamic system for its “secret” against eavesdropping attacks. As an information-flow property, the underlying observation model is the key in the modeling and analysis of opacity. In this paper, we investigate the verification of current-state opacity for discrete-event systems under Orwellian-type

Designing stable feedback controllers that stabilize a given plant, known as strong stabilization, has been explored in the literature by using several algorithmic construction procedures. Many of these methods rely on step-by-step interpolation or solving an auxiliary H∞ control problem, or a set of LMIs. This paper gives an explicit construction of simple strongly stabilizing controllers for plants

We propose a method to efficiently estimate the eigenvalues of any arbitrary (potentially weighted or directed) network of interacting dynamical agents in the presence of control inputs from dynamical observations. These observations are discrete, temporal measurements of the evolution of the aggregated outputs from a subset of agents (potentially one) during a finite time horizon. Notably, we do not

In this paper, a novel adaptive hybrid impedance control for a dual-arm robot is proposed to cooperatively manipulate unknown objects. The proposed adaptive hybrid control scheme could be employed to improve the control performance of motion tracking and internal force regulation when dual-arm cooperative robot grasp an unknown object. Along with the analysis of human motion in the process of transferring

Optical Parametric Oscillators (OPOs) have wide applications in quantum optics for generating squeezed states and developing advanced technologies. When the phase or/and the amplitude of the pumping field for an OPO have fluctuations due to fault signals, time-varying uncertainties will be introduced in the dynamic parameters of the system. In this paper, we investigate how to design a fault-tolerant

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

This issue of IEEE Control Systems celebrates the 50th anniversary of the two-part dissipativity article published by Jan Willems in 1972. To celebrate this event, Arjan van der Schaft assembled six articles for this issue, celebrating the first part of the dissipativity article [1] . Another set of seven articles will be published in the next issue to celebrate more, particularly, the second part

This IEEE Control Systems issue celebrates the 50th anniversary of the publication of Jan Willems’ two publications laying the foundations of dissipativity theory. “From the Editor” elaborates on reasons to celebrate this event. Guest Editor Arjan van der Schaft has assembled six articles for the first special issue devoted to the first part of the dissipativity article: “Compositional Design and Verification

I love control theory. I love the concept of feedback. I love applications of control theory. I especially love the mathematical rigor that comes with formulating problems in control, the odor of a freshly cooked proof, and the thrill of implementing an algorithm in a real device or application. I have also been extremely fortunate to have spent my entire life putting into practice the things that

Successful industrial applications and favorable comparisons with conventional alternatives have motivated the development of a large number of schemes for neural-network-based control. Each scheme is usually composed of several independent functional features, which makes it difficult to identify precisely what is new in the scheme. Help from available overviews is therefore often inadequate, since

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

The main goal of this article is to design torque controls for a common model of a playground swing: the model of swinging in the sitting position proposed by Case and Swanson [1] , with damping added for more realism (see “Summary”). The addition of damping makes the problem much more complex from the analytic standpoint. Modeling human control of playground swings has a venerable history going back

In this issue of IEEE Control Systems , we speak with Travis E. Gibson, an instructor of pathology at Brigham and Women’s Hospital and Harvard Medical School; Andrew Lamperski, an assistant professor of electrical and computer engineering at the University of Minnesota; Rifat Sipahi, a professor at Northeastern University in Boston; and Tansel Yucelen, an associate professor of mechanical engineering

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?

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

Q. What are your research interests?

The two-part article, “Dissipative Dynamical Systems,” by Jan C. Willems, was received by the Archive for Rational Mechanics and Analysis on January 19, 1972, with publication in the same year (vol. 45, Part I: pp. 321–351, Part II: pp. 352–393). Part I of the article was also included in Control Theory: Twenty-Five Seminal Articles (1932–1981) , T. Ba?ar, Ed. New York: Wiley-IEEE Press, 2001, pp.

There were several moments in my research when I started exploring new topics and did not expect to use dissipativity tools. Each time, I was wrong: sooner or later, I would encounter a problem for which, in my mind, there was no better approach. Judging from the other articles in this issue and the wealth of problems they address, I believe the impact of dissipativity in control theory is still growing

Passivity-based control (PBC) and the related energy-shaping control have a rich history in robotics going back to the 1980s. The kinematics and dynamics of robot manipulators and Lagrangian systems in general are highly complex, and the realization that they satisfy a passivity property was crucial to the development of rigorous robust and adaptive control laws, beginning in the mid-1980s and continuing

The close link between dissipativity and optimal control is already apparent in Willems’ first articles on the subject. Particularly, [1] (which appeared one year before his famous dissipativity articles [2] , [3] ) already contains much insight on this connection for linear quadratic (LQ) optimal control problems (see “Summary”). Around the same time, the role of a passivity-like variant of dissipativity

Energy-related concepts, such as passivity, dissipation, and energy storage, are appealing and widely appreciated in the study of physical systems. The theory of dissipativity (see “Summary”) enables such properties in abstract system descriptions and can lead to significant progress in the study of dynamic properties and stabilization. The key early result is the celebrated Kalman–Yakubovich–Popov

Half a century ago, and a few years after receiving his Ph.D. degree in electrical engineering at the Massachusetts Institute of Technology, Jan Willems published articles on dissipative dynamical systems [30] , [31] . In retrospect, the conceptual thinking and elegant generalization of the basic physical properties behind the notion of dissipation can be viewed as a distinctive stage in the field

Dissipativity, introduced by Jan C. Willems, has attracted significant interest from researchers in the systems and control area. Dissipativity theory (see “Summary”) is an energy-based framework for the analysis and design of systems using an input–output approach. Dissipativity is an efficient mathematical tool to formulate well-known physical phenomena in systems sciences and provides insight into

By Wassim M. Haddad

This book covers optimization problems involving uncertain parameters for which stochastic models are available. These problems occur in almost all areas of science and engineering. This revision of the previous edition presents a modern theory of stochastic programming, including expanded coverage of sample complexity, risk measures, and distributionally robust optimization. The interchangeability

Presents the recipients of IEEE Control Systems Society awards in 2021.

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

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This paper is concerned with an optimal impulse control problem under a hybrid diffusion (or, regime switching) model, where the state of the system consists of a number of diffusions coupled by a continuous-time finite-state Markov chain. The objective is to minimize the expected discounted cost from exerting the impulse control in the infinite horizon. Based on the dynamic programming principle (DPP)

This paper provides an overview of the research conducted in the context of structural (or structured) systems. These are parametrized models used to assess and design system theoretical properties without considering a specific realization of the parameters (which could be uncertain or unknown). The research in structural systems led to a principled approach to a variety of problems, into what is

This paper investigates a class of motion planning problems where multiple unicycle robots desire to safely reach their respective goal regions with minimal traveling times. We present a distributed algorithm which integrates decoupled optimal feedback planning and distributed conflict resolution. Collision avoidance and finite-time arrival at the goal regions are formally guaranteed. Further, the

Solving the Lexicographic Bottleneck Assignment Problem (LexBAP) typically relies on centralised computation with order O(n4) complexity. We consider the Sequential Bottleneck Assignment Problem (SeqBAP), which yields a greedy solution to the LexBAP and discuss the relationship between the SeqBAP, the LexBAP, and the Bottleneck Assignment Problem (BAP). In particular, we reexamine tools used to analyse

In this paper, we focus on the stabilization of nonlinear stochastic systems with output delay. Based on the predictive scheme and event-triggering mechanism (ETM), a novel event-triggered predictive control is proposed to exponentially stabilize such stochastic systems. Moreover, this novel control law allows non-uniform sampled measurements and large delays involved in the output. Simultaneously

A crane control system is proposed where the crane payload follows a desired position trajectory with ultimately bounded pendulum motion. The proposed control system includes a Lyapunov-based damping controller, which stabilizes the dynamics of the payload by increasing the damping of the pendulum motion. The crane with the resulting stabilized dynamics is controlled with a tracking controller based

This paper studies the problem of generalized Nash equilibrium seeking in population games under general affine equality and convex inequality constraints. In particular, we design a novel payoff dynamics model to steer the decision-making agents to a generalized Nash equilibrium of the underlying game, i.e., to a self-enforceable state where the constraints are satisfied and no agent has incentives

Opacity is an important information security property. Given a discrete event system, a set of secret states, and an intruder who observes the system evolution through an observation mask, the system is said to be K-step opaque if the intruder is not able to ascertain that the system is or was in a secret state at some time within K steps, namely within the observation of K events. If the intruder

Markovian network equilibrium generalizes the classical Wardrop equilibrium in network games. At a Markovian network equilibrium, each player of the game solves a Markov decision process instead of a shortest path problem. We propose two novel extensions of Markovian network equilibrium by considering (1) variable demand, which offers the players a quitting option, and (2) multi-commodity flow, which

This paper proposes a consensus-based formation tracking scheme for multi-robot systems utilizing the Negative Imaginary (NI) theory. The proposed scheme applies to a class of networked robotic systems that can be modelled as a group of single integrator agents with stable uncertainties connected via an undirected graph. NI/SNI property of networked agents facilitates the design of a distributed Strictly

This paper deals with the technical formulation and implementation details of an algorithm that provides an estimate of the probability density function of the state of a nonlinear dynamical system from discrete time measurements. In contrast to other state estimation methods that propagate the conditional moments, the proposed filter is shown to propagate and update the full probability density function

Structural balance theory characterizes stable configurations of signed interpersonal appraisal networks. Existing models explaining the convergence of appraisal networks to structural balance either diverge in finite time, or could get stuck in jammed states, or converge to only complete graphs. In this paper, we study the open problem of how non-complete appraisal networks converge to structural

Recently, the problem of robust diagnosis against loss of event observations has been proposed in the literature, where it is assumed that some sensors, or communication channels between sensors and diagnosers, are subject to failures. In these works, permanent or intermittent failures are considered, and models of the plant subject to these failures are obtained. One characteristic of the robust diagnosis

Formulating cyber-security problems with attackers and defenders as a partially observable stochastic game has become a trend recently. Among them, the one-sided two-player zero-sum partially observable stochastic game (OTZ-POSG) has emerged as a popular model because it allows players to compete for multiple stages based on partial knowledge of the system. All existing work on OTZ-POSG has focused

Linear temporal logic (LTL) formulae are widely used to provide high level behavioral specifications on mobile robots. We propose a decentralized route-planning method for a networked team of mobile robots to satisfy a common (global) LTL specification. The global specification is assumed to be a conjunction of multiple formulae, each of which is treated as a task to be assigned to one or more vehicles

In this paper, we consider the privacy preservation problem in continuous-time average consensus algorithms with strongly connected and balanced graphs, against either internal honest-but-curious agents or external eavesdroppers. A novel algorithm is proposed, which adds edge-based perturbation signals to the process of consensus computation. Our algorithm can be divided into two phases: a coordinated

Even-though data concatenation is a well-known technique for identifying Linear Time-Invariant models from multiple records, the study of the asymptotic properties of the estimator continues to be limited. Therefore, we investigated consistency and asymptotic normality as the number or records tend to infinity, with focus on the identification of discrete-time parametric models for single-input single-output