Article
Automation & Control Systems
Brenner S. Rego, Joseph K. Scott, Davide M. Raimondo, Guilherme V. Raffo
Summary: This paper introduces new methods for improving set-valued state estimation of nonlinear systems by adding a consistency step using system invariants to reduce conservatism, and significant improvements to constrained zonotopes for tighter enclosures. Numerical results demonstrate that the resulting methods can provide significantly tighter enclosures than existing methods while maintaining comparable efficiency.
Article
Automation & Control Systems
Brenner S. Rego, Diego Locatelli, Davide M. Raimondo, Guilherme Raffo
Summary: This note introduces a new method for joint state and parameter estimation of discrete-time systems using constrained zonotopes. By extending previous set-based state estimation methods to include parameter identification, the existing dependencies between states and model parameters are maintained, resulting in a more accurate estimation scheme. The refinement of state and parameter enclosure using generalized intersections, properly captured by constrained zonotopes, is also highlighted. The advantages of this new approach are demonstrated through two numerical examples.
Article
Automation & Control Systems
Matthias Althoff, Jagat Jyoti Rath
Summary: The study evaluates and compares a variety of guaranteed state estimators for linear time-invariant systems, focusing on scalability, accuracy, and real-time applicability. The performance of most guaranteed state estimators is significantly influenced by the selected set representation, with zonotopes emerging as a popular choice for their exact and efficient computation of key operations. Comparisons are made with ellipsoids and constrained zonotopes as set representations for state estimation of autonomous vehicles.
Article
Automation & Control Systems
Trevor J. Bird, Herschel C. Pangborn, Neera Jain, Justin P. Koeln
Summary: This article introduces a new set representation called the hybrid zonotope, which is equivalent to the union of 2N constrained zonotopes by adding N binary zonotope factors. The main contribution is a closed-form solution for exact forward reachable sets of discrete-time, linear hybrid systems modeled as mixed logical dynamical systems. The proposed approach captures the worst-case exponential growth in the number of convex sets required to represent the nonconvex reachable set while exhibiting only linear growth in the complexity of the hybrid zonotope set representation. Numerical examples demonstrate its ability to compactly represent nonconvex reachable sets with an exponential number of features. Furthermore, it is shown to be closed under linear mappings, Minkowski sums, generalized intersections, and halfspace intersections.
Article
Automation & Control Systems
Carmelina Ierardi, Luis Orihuela, Isabel Jurado
Summary: This paper presents a distributed set-membership estimator for linear full-coupled systems affected by bounded disturbances, using multi-hop staircase decomposition and zonotopes description. The observer gains can be designed in distributed steps via simple algebraic equations, reducing computational requirements.
Article
Automation & Control Systems
Ahmad Al-Mohamad, Vicenc Puig, Ghaleb Hoblos
Summary: This paper proposes a robust recursive zonotopic set-membership approach for remaining useful life forecasting of linear parameter-varying systems with degraded components. The approach formulates the degraded components as a system-level prognostics problem and reformulates it as a linear parameter-varying model. It adopts joint estimation of states and parameters in a zonotopic set-membership scheme with optimal tuning based on linear matrix inequality. The approach is applied to predict the failure precursors of degraded systems and tested on a DC-DC converter case study with unknown degradation behaviors, demonstrating its estimation and forecasting accuracy.
Article
Automation & Control Systems
Amr Alanwar, Victor Gassmann, Xingkang He, Hazem Said, Henrik Sandberg, Karl H. Johansson, Matthias Althoff
Summary: The set-based estimation is highly valued for its ability to ensure state enclosures in safety-critical systems. However, the need to outsource set-based operations to a central aggregator node for collecting measurements from distributed sensors raises privacy concerns. To address this, we propose set-based estimation protocols using partially homomorphic encryption to protect the privacy of measurements and estimations. We demonstrate the effectiveness of our protocols by localizing a real mobile quadcopter using ultra-wideband wireless devices.
EUROPEAN JOURNAL OF CONTROL
(2023)
Article
Automation & Control Systems
Vignesh Raghuraman, Justin P. Koeln
Summary: A hierarchical Model Predictive Control (MPC) formulation is proposed for coupled discrete-time linear systems with state and input constraints. The two-level hierarchical controller reduces the computational cost associated with MPC and achieves hierarchical coordination using adjustable tubes. Zonotopes are used to optimize the size of these adjustable tubes and ensure constraint satisfaction.
Article
Automation & Control Systems
Zhihao Zhang, Zhenhua Wang, Ye Wang, Yi Shen, Yipeng Liu
Summary: This paper investigates reachable set estimation for bilinear discrete-time systems with time-varying delays considering state feedback and unknown-but-bounded disturbance. A novel method based on the zonotopic technique is proposed, and its effectiveness is demonstrated through a numerical example.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2021)
Article
Chemistry, Multidisciplinary
Han Qing Yang, Jun Wei Wu, Rui Wen Shao, Zheng Xing Wang, Hui Xu, Yuan Gao, Qiang Cheng, Tie Jun Cui
Summary: A computational-metasurface-based equation solver is proposed, which deals with complex matrix equations at quasi-light speed and yields real-time solutions. This work provides a promising technique to overcome some shortcomings in existing designs, and lays the first stone of the bridge toward programmable wave-space computers.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Computer Science, Information Systems
Hailong Tan, Bo Shen, Qi Lid, Tingwen Huang
Summary: This paper studies the problem of zonotopic set-membership estimation (SME) for time-varying systems subject to dynamical biases and uniform quantization. A mathematical method is proposed to estimate the state of the system by analyzing the dynamics of biases and states. An auxiliary zonotope is constructed to minimize the estimation error, and an external approximation is used to reduce the computational burden. The effectiveness of the proposed method is demonstrated through simulations.
INFORMATION SCIENCES
(2024)
Article
Automation & Control Systems
Zhongyang Fei, Liu Yang, Xi-Ming Sun, Shunqing Ren
Summary: This article proposes a novel set-membership state estimation method based on zonotopes for switched systems subject to unknown-but-bounded disturbance with average dwell time switching. It builds an intersection zonotope by testing the consistency between the system model and measured output, and addresses the issue of disturbance attenuation performance through constructing semitime-dependent P-radius functions. A numerical example is presented to illustrate the effectiveness of the proposed approach.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Computer Science, Artificial Intelligence
Zhongyi Zhao, Zidong Wang, Lei Zou, Yun Chen, Weiguo Sheng
Summary: This paper studies the distributed fusion estimation problem for a class of nonlinear networked systems with unknown-but-bounded (UBB) noises. It proposes a zonotopes-based distributed fusion estimator by designing local estimators and fusion methods. The effectiveness of the proposed method is illustrated through a numerical example.
INFORMATION FUSION
(2023)
Article
Automation & Control Systems
Junbo Tan, Sorin Olaru, Feng Xu, Xueqian Wang
Summary: This article proposes a new method for designing online optimal input sequences for robust active fault diagnosis using set-theoretic methods. The method reshapes the input sequence based on real-time information to improve the diagnosability of the system. By solving nonconvex fractional programming problems and utilizing Lagrange duality, the optimal input is explicitly obtained.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Chemistry, Analytical
Krzysztof Kutt, Dominika Drazyk, Szymon Bobek, Grzegorz J. Nalepa
Summary: This article proposes using personality assessment to adapt affective intelligent systems and verifies the potential of this adaptation mechanism through experiments linking personality traits to psychophysiological signals and reactions to complex stimulus environments.
Article
Automation & Control Systems
Xiaoyu Luo, Chengcheng Zhao, Chongrong Fang, Jianping He
Summary: This paper investigates the problem of false data injection attacks in multi-agent dynamical systems and proposes FDI attack set selection algorithms to maximize the convergence error by finding the optimal subset of compromised agents.
Article
Automation & Control Systems
Nitin K. Singh, Abhisek K. Behera
Summary: In this paper, a twisting observer is proposed for robustly estimating the states of a second-order uncertain system. The observer approximates the unknown sign term for the non-measurable state with a delayed output-based switching function, and achieves the desired steady-state accuracy by controlling the delay parameter. The application of the observer to output feedback stabilization is also discussed.
Article
Automation & Control Systems
Alexander Aleksandrov
Summary: This paper investigates the absolute stability problem for positive Persidskii systems with delay, proposes a special construction method for diagonal Lyapunov-Krasovskii functionals, and derives a criterion for the existence of such functionals guaranteeing the absolute stability, as well as obtaining sufficient conditions for a family of time-delay Persidskii systems to construct a common diagonal Lyapunov-Krasovskii functional. The efficiency of the developed approaches is demonstrated through four examples.
Article
Automation & Control Systems
Noureddine Toumi, Roland Malhame, Jerome Le Ny
Summary: This paper addresses large multi-agent dynamic discrete choice problems using a linear quadratic mean field games framework. The model incorporates the features where agents have to reach a predefined set of possible destinations within a fixed time frame and running costs can become negative to simulate crowd avoidance. An upper bound on the time horizon is derived to prevent agents from escaping to infinity in finite time. The existence of a Nash equilibrium for infinite population and its epsilon-Nash property for a large but finite population are established. Simulations are conducted to explore the model behavior in various scenarios.
Article
Automation & Control Systems
Philippe Schuchert, Vaibhav Gupta, Alireza Karimi
Summary: This paper presents the design of fixed-structure controllers for the As2 and Asw synthesis problem using frequency response data. The minimization of the norm of the transfer function between the exogenous inputs and performance outputs is approximated through a convex optimization problem involving Linear Matrix Inequalities (LMIs). A general controller parametrization is used for continuous and discrete-time controllers with matrix transfer function or state-space representation. Numerical results show that the proposed data-driven method achieves performance equivalent to model-based approaches when a parametric model is available.
Correction
Automation & Control Systems
Zhijun Guo, Gang Chen
Article
Automation & Control Systems
Matteo Della Rossa, Thiago Alves Lima, Marc Jungers, Raphael M. Jungers
Summary: This paper presents new stabilizability conditions for switched linear systems with arbitrary and uncontrollable underlying switching signals. The study focuses on two specific settings: the robust case with completely unknown and unobservable active mode, and the mode-dependent case with controller depending on the current active switching mode. The technical developments are based on graph-theory tools and path-complete Lyapunov functions framework, enabling the design of robust and mode-dependent piecewise linear state-feedback controllers using directed and labeled graphs.
Article
Automation & Control Systems
Elena Petri, Romain Postoyan, Daniele Astolfi, Dragan Nesic, W. P. M. H. (Maurice) Heemels
Summary: This study investigates a scenario where a perturbed nonlinear system transmits its output measurements to a remote observer via a packet-based communication network. By designing both the observer and the local transmission policies, accurate state estimates can be obtained while only sporadically using the communication network.
Article
Automation & Control Systems
Jonas Krook, Robi Malik, Sahar Mohajerani, Martin Fabian
Summary: 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. The approach constructs a finite-state abstraction of the original system and synthesises a controller for the abstraction. It introduces the robust stutter bisimulation relation to account for disturbances and uncertainty, ensuring that related states have similar effects under the same controller. The paper demonstrates that the existence of a controller for the abstracted system implies the existence of a controller for the original system enforcing the linear temporal logic formula.
Article
Automation & Control Systems
Clement Chahbazian, Karim Dahia, Nicolas Merlinge, Benedicte Winter-Bonnet, Aurelien Blanc, Christian Musso
Summary: The paper derives a recursive formula of the Fisher information matrix on Lie groups and applies it to nonlinear Gaussian systems on Lie groups for testing. The proposed recursive CRLB is consistent with state-of-the-art filters and exhibits representative behavior in estimation errors. This paper provides a simple method to recursively compute the minimal variance of an estimator on matrix Lie groups, which is fundamental for implementing robust algorithms.
Article
Automation & Control Systems
Yiheng Fu, Pouria Ramazi
Summary: This study investigates the characteristics of decision fluctuations in heterogeneous populations and explores the uncertainties in imitation behavior. The findings are important for understanding the bounded rationality nature of imitation behaviors.
Article
Automation & Control Systems
Lars A. L. Janssen, Bart Besselink, Rob H. B. Fey, Nathan van de Wouw
Summary: This paper introduces a mathematical relationship between the accuracy of reduced-order linear-time invariant subsystem models and the stability and accuracy of the resulting reduced-order interconnected linear time-invariant model. This result can be used to directly translate the accuracy characteristics of the reduced-order subsystem models to the accuracy properties of the interconnected reduced-order model, or to translate accuracy requirements on the interconnected system model to accuracy requirements on subsystem models.
Article
Automation & Control Systems
Piyush Gupta, Vaibhav Srivastava
Summary: We study the optimal fidelity selection for a human operator servicing tasks in a queue, considering the trade-off between high-quality service and penalty due to increased queue length. By modeling the operator's cognitive dynamics and task fidelity, we determine the optimal policy and value function numerically, and analyze the structural properties of the optimal fidelity policy.
Article
Automation & Control Systems
Lukas Schwenkel, Alexander Hadorn, Matthias A. Mueller, Frank Allgoewer
Summary: In this work, the authors study economic model predictive control (MPC) in periodic operating conditions. They propose a method to achieve optimality by multiplying the stage cost by a linear discount factor, which is easy to implement and robust against online changes. Under certain assumptions, they prove that the resulting linearly discounted economic MPC achieves optimal asymptotic average performance and guarantees practical asymptotic stability of the optimal periodic orbit.
Article
Automation & Control Systems
Taher Ebrahim, Sankaranarayanan Subramanian, Sebastian Engell
Summary: We propose a robust nonlinear model predictive control algorithm for dynamic systems with mixed degrees of freedom. This algorithm optimizes both continuous and discrete manipulated variables, enhancing closed-loop performance. Our approach relies on a computationally efficient relaxation and integrality restoration strategy and provides sufficient conditions to establish recursive feasibility and guarantee robust closed-loop stability. The effectiveness of the approach is demonstrated through two nonlinear simulation examples.