Medical decision making increasingly relies on machine learning algorithms to analyze complex patient data and provide recommendations. However, the lack of interpretability in “black box” models has limited their adoption in clinical practice, which demands transparency and justification. Echo State Networks (ESNs), a recurrent neural network architecture, have shown promise for medical Decision Support

We design, implement, and evaluate a decision support system that combines fine-grained signals derived from news and social media with bitcoin prices using a Long Short-Term Memory (LSTM) neural network. Through this artifact, we construct a portfolio to trade bitcoin in three stages. In the first stage, signals and prices are used as inputs for the LSTM model to predict bitcoin prices. In the second

This paper addresses the problem of input-to-state stabilization for heat equation with external input via boundary control strategy. Following Polyakov et al., 2017, based on the backstepping approach, a switching boundary control law depending on the system state is designed. By estimating the upper bound of kernel functions, switching levels are determined and commutation law is further constructed

Consensus in multi-agent dynamical systems is prone to be sabotaged by the adversary, which has attracted much attention due to its key role in broad applications. In this paper, we study a new false data injection (FDI) attack design problem, where the adversary with limited capability aims to select a subset of agents and manipulate their local multi-dimensional states to maximize the consensus convergence

This work investigates the absolute stability problem for positive Persidskii systems with delay. Right-hand sides of these systems are linear combinations of nonlinearities of a sector type. A special construction of diagonal Lyapunov–Krasovskii functionals is proposed and a criterion for the existence of such functionals guaranteeing the absolute stability is derived. Furthermore, sufficient conditions

Internet technology allows e-tailers to provide installment payment services, allowing consumers to purchase products without immediate payment. In addition, retailers can apply intelligent pricing strategies and provide price-guarantee strategies to encourage consumers to buy in advance. This study uses a dynamic mechanism design to explore the interplay between pricing and financing strategies. Specifically

During viral pandemics, governments throughout the world face many complicated and important decisions, such as whether and how to implement a shutdown. In response to shutdown measures that are enacted by governments, citizens are then forced to make decisions regarding whether to comply (and stay home) or violate (and leave their residence for non-essential reasons). To the best of our knowledge

This paper approaches large multi-agent dynamic discrete choice problems, such as those arising in crowd evacuation or micro-robotic-based exploration of unknown terrain, via a linear quadratic mean field games framework (LQ-MFG). Two particular features distinguish the proposed LQ-MFG: (i) agents have to reach within a fixed finite time one of a predefined set of possible destinations, which depend

The operation of autonomous systems is inherently constrained by their surrounding environment, which is often time-varying and unknown a priori, necessitating perception using sensors. Hence, control strategies for autonomous systems must take into account the uncertainty of the perceived environment in making decisions, while information acquired by sensors often depends on how the system is operated

People often make decisions differently, even when faced with the same decision-making scenario and objectives, due to their varying abilities to access, process, and comprehend information relevant to the decisions at hand. To reconcile these differing perspectives and arrive at a unified decision, various approaches such as crowd-sourced systems have been developed to tap into the collective intelligence

The frequency response data of a system is used to design fixed-structure controllers for the ?2 and ?∞ synthesis problem. The minimization of the two and infinity norm of the transfer function between the exogenous inputs and performance outputs is approximated by a convex optimization problem involving Linear Matrix Inequalities (LMIs). A very general controller parametrization is used for continuous

The recursive posterior Cramér–Rao Lower Bound (CRLB) introduced by Tichavsky et al. (1998) is an efficient tool to estimate the minimum variance of an estimator. Lately, filters and observers on matrix Lie groups have raised interest in control and nonlinear estimation. However, the recursive CRLB applies to variables belonging to the Euclidean space, and a recursive formulation on matrix Lie groups

In this paper, we propose the twisting observer for robustly estimating the states of a second-order uncertain system. It is well-known that the twisting algorithm achieves the second-order sliding mode condition using the sign information of both the plant states. When all the states are not available, the twisting algorithm cannot be extended to the estimation problem directly. Hence, our proposed

Abstract not available

Consumers' preservice tipping behavior serves as a window to reflect their economic and social perception and desire for high service quality but is rarely discussed in tipping literature, compared with postservice tipping. The on-demand feature in the online-to-offline context complicates the fulfillment performance and consumers' preservice tipping behavior, including whether to tip (i.e., tip giving)

This paper is devoted to a mixed leadership stochastic differential game on a finite horizon in feedback information mode, where the control variables enter into the diffusion term of the state equation. A verification theorem for the feedback Stackelberg–Nash equilibrium is obtained by using a system of coupled and fully nonlinear parabolic partial differential equations. A necessary condition for

We investigate the scenario where a perturbed nonlinear system transmits its output measurements to a remote observer via a packet-based communication network. The sensors are grouped into N nodes and each of these nodes decides when its measured data is transmitted over the network independently. The objective is to design both the observer and the local transmission policies in order to obtain accurate

This paper proposes a method to synthesise controllers for cyber-physical systems subjected to disturbances, such that the controlled system satisfies specifications given as linear temporal logic formulas. To solve this problem, a finite-state abstraction of the original system is first constructed, and then a controller is synthesised for the abstraction. Due to the disturbances and uncertainty in

This paper presents novel stabilizability conditions for switched linear systems with arbitrary and uncontrollable underlying switching signals. We distinguish and study two particular settings: (i) the robust case, in which the active mode is completely unknown and unobservable, and (ii) the mode-dependent case, in which the controller depends on the current active switching mode. The technical developments

This paper designs observer gains to optimize the minimal robust positively invariant set and uses this set for robust fault detection. First, the sizes of the minimal robust positively invariant set and corresponding minimal residual set are computed based on the Frobenius norm size (i.e., Frobenius radius) of zonotopes. Second, by formulating the size minimization problem as a solvable optimization

This paper investigates an equilibrium-based multi-agent optimal consumption and portfolio problem incorporating uncertainties on fundamental risks, where multiple agents have heterogeneous (conservative, neutral, aggressive) views on the risks represented by Brownian motions. Each agent maximizes its expected utility on consumption under its subjective probability measure. Specifically, we formulate

We propose and examine two inherently symmetric (0,1)-matrix completion problems with majorization ordered objectives, which provides a unique perspective for electric vehicle charging, portfolio optimization, and multi-agent cooperation. Our work elevates the seminal study by Gale and Ryser from feasibility to optimality in partial order programming (POP), referring to optimization with partially

We present a robust nonlinear model predictive control (NMPC) algorithm for dynamic systems with mixed degrees of freedom, i.e., continuous and discrete manipulated variables. The discrete variables are often excluded from the NMPC layer and determined at a supervisory layer, which typically leads to suboptimal solutions. In contrast, the proposed controller optimizes both classes of degrees of freedom

This paper presents a novel backstepping formation control strategy for multiple Euler–Lagrange (EL) systems. To enhance parallel communication capability, the communication channels for systems’ position vectors and filters’ states are independent. Subsequently, the corresponding dynamic event-triggered mechanisms are designed specifically for them to reduce the frequency of interactive communication

This paper studies the distributed formation control problem of second-order multi-agent systems (MASs) with limited communication ranges and collision avoidance constraints. A novel connectivity preservation and collision-free distributed control algorithm is proposed by combining prescribed performance control (PPC) and exponential zeroing control barrier Lyapunov functions (EZCBFs). In particular

In e-commerce, product photos are a major component of product presentations that aid consumers' understanding of products. In this study, we investigate the impact of the background of product photos on consumers' interest. Drawing upon the attention theories of visual perception, we propose a contrast-composition-distraction framework to understand the product photo background's impact. We conduct

Drawing on information technology-enabled organizational capabilities theory, we argue that how and when social media use affects marketing performance depending on the mediating role of social customer relationship management (CRM) capability and the moderating role of guanxi. Using a sample of 194 Chinese agricultural firms, we employed a combination of complementary techniques: advanced analysis

This paper examines how weak synaptic coupling can achieve rapid synchronization in heterogeneous networks. The assumptions aim at capturing the key mathematical properties that make this possible for biophysical networks. In particular, the combination of nodal excitability and synaptic coupling are shown to be essential to the phenomenon.

Many complex engineering systems consist of multiple subsystems that are developed by different teams of engineers. To analyse, simulate and control such complex systems, accurate yet computationally efficient models are required. Modular model reduction, in which the subsystem models are reduced individually, is a practical and an efficient method to obtain accurate reduced-order models of such complex

This paper presents discrete-time distributed algorithms to achieve time-varying output formation tracking of heterogeneous linear multi-agent systems subject to time-varying faults and directed graphs. To overcome the impacts caused by unknown faults and directed graphs, a discrete-time adaptive distributed output observer-based control architecture is established to guarantee time-varying output

Proportional–integral–derivative (PID) controller is the most widely used form of feedback control by far. However, a satisfactory theory is still lacking to explain the rationale of the widespread PID control, and the gap between theory and practice of PID needs to be filled by control scientists. It is worth noting that a recent work (Zhao and Guo, 2022) proved that the classical PID controller has

We consider a model of a microfluidic process under Zweifac–Fung effect, which gives rise to a second-order nonlinear, non-affine system with control input that affects the plant both without delay and with an input-dependent delay defined implicitly through an integral of the past input values (that arises from a transport process with transport speed being the control input itself). We construct

This paper deals with model predictive control (MPC) for nonlinear systems using linear-parameter varying (LPV) embedding of the nonlinear dynamics (LPVMPC). The proposed LPVMPC can incorporate information of the future evolution of the scheduling parameter over the MPC prediction horizon with uncertainty bounds, which are used to construct anticipated scheduling tubes for robustification. Therefore

This is August, and I am returning from a few days far away from work. During those few days, I did my best to stay away from e-mails, to read on paper rather than on screen, to write with pen rather than with a keyboard, to stay outside rather than inside. Holy days. Days of respiration. Days of encounters.

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Learning algorithms have become an integral component to modern engineering solutions. Examples range from self-driving cars and recommender systems to finance and even critical infrastructure, many of which are typically under the purview of control theory. While these algorithms have already shown tremendous promise in certain applications [1] , there are considerable challenges, in particular, with

This issue of IEEE Control Systems is the second of two special issues devoted to data-driven control. The guest editor for these issues is Florian D?rfler, and he was helped by our Associate Editor Daniel Quevedo.

The way we have structured our conferences for as long as I have been an active participant in the IEEE Control Systems Society (CSS) is some variation of the formula of each talk being 20 min long; each session consisting of six presentations, with around 25 (this fluctuates a bit) parallel sessions; and three such blocks per day, with the conferences lasting three days. This translates to 1,350 presentations

In this issue, “25 Years Ago” revisits the article “Sensor-Based Microassembly of Hybrid MEMS Devices” by Bradley Nelson, Yu Zhou, and Barmeshwar Vikramaditya in IEEE Control Systems Magazine , vol. 18, no. 6, pp. 35–45. Below is an excerpt from the article.

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In this issue of IEEE Control Systems , we speak with Marc Bodson, who is a professor of electrical and computer engineering at the University of Utah, Salt Lake City, UT, USA; Shun-ichi Azuma, who is a professor at Kyoto University, Kyoto, Japan; and Serdar Yüksel, who is a professor in the Department of Mathematics and Statistics, Queen’s University, Kingston, ON, Canada.

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?

A recurring question that all authors of this special issue encounter is, “Why not go with models?” Two terms need to be clarified: In this context, a model is understood as a parametric system representation often endowed with an interpretable structure, for example, a state-space representation with a readily discernible F = m · a equation. Further, the term data-driven control , as we employ it

Roughly speaking, systems and control theory deals with the problem of making a concrete physical system behave according to certain desired specifications. To achieve this desired behavior, the system can be interconnected with a physical device, called a controller. The problem of finding a mathematical description of such a controller is called the control design problem .

In many control applications, model-based design has become the standard practice due to the obvious advantages of a convenient, understandable description of the process and the possibility of a continuous validation of the controlled system at all stages of development [1] .

Q. How would you pitch your Ph.D. research briefly? How would you describe the significance and relevance of your results?

Q. How would you pitch your Ph.D. dissertation in one paragraph?

In this issue, we speak with Iman Shames and Robert Mahony about the Control, Information, Intelligence, Communication, Automation, Decision, and Autonomy (CIICADA) Laboratory of the Australian National University. This research laboratory continues the legacy of international research excellence established by Profs. Brian Anderson and John Moore, and provides expertise targeted at Australia’s technological

The book situates itself in a unique niche “between proportional-integral-derivative (PID) and model predictive control (MPC),” as a compromise between the tradeoffs and advantages of each. The book emphasizes state-space techniques but goes beyond the standard presentation of these ideas to consider their application in more traditional industrial settings, where consideration must be given to MIMO

This year, the Technical Committee (TC) Outstanding Student Paper Prizes continued, with seven TCs awarding prizes. These prizes aim to recognize young talent associated with a technical area and promote student membership and participation in the TCs. The prizes are awarded by each TC to a student who is the primary author of a paper at the previous year’s IEEE Conference on Decision and Control (CDC)

Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.

Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.

Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.

Walter Murray Wonham died on Sunday, 14 May 2023 at the age of 88, leaving a series of legacies in control theory (see “Control Theory Legacies”). He died unexpectedly at home in Toronto, Ontario, Canada, and was active in research, graduate teaching and supervision until the day of his death.

Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.

Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.

In this paper, a hierarchical design framework is proposed for distributed control of multi-agent systems. Different from the traditional distributed design philosophy that directly couples the agents’ cooperation and individual regulations, the proposed framework decouples these regulations and separates the distributed control design into two layers, i.e., the layer of reference signal generator

In this paper, a timestamp-based projected gradient play is proposed for Nash equilibrium seeking over communication networks for strongly monotone games. Its difference from the well-known consensus-based Nash equilibrium seeking method is that each player’s local estimate of other players’ actions is updated through a timestamp-based broadcasting protocol instead of typical consensus protocols. We