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This paper presents a framework of learning parameter space for event-triggered control. In particular, our goal is to find a set of parameters for the event-triggered condition, such that certain specifications on safety and convergence…

Optimization and Control · Mathematics 2020-10-20 Kazumune Hashimoto

We consider the problem of estimating the states of a distributed network of nodes (targets) through a team of cooperating agents (sensors) persistently visiting the nodes so that an overall measure of estimation error covariance evaluated…

Systems and Control · Electrical Eng. & Systems 2021-10-14 Shirantha Welikala , Christos G. Cassandras

This work presents an event-triggered switching control framework for a class of nonlinear underactuated multi-channel systems with input constraints. These systems are inspired by cooperative manipulation tasks involving underactuation,…

Systems and Control · Electrical Eng. & Systems 2025-12-01 Dongjae Lee , Dimos V. Dimarogonas , H. Jin Kim

The design of the performance index, also referred to as cost or reward shaping, is central to both optimal control and reinforcement learning, as it directly determines the behaviors, trade-offs, and objectives that the resulting control…

Systems and Control · Electrical Eng. & Systems 2025-10-14 Ayush Rai , Shaoshuai Mou , Brian D. O. Anderson

This paper presents a mathematical approach for improving the performance of a control system by modifying the time delay at certain operating conditions. This approach converts a continuous time loop into a discrete time loop. The formula…

Systems and Control · Computer Science 2015-03-03 Salem Alkhalaf

This article studies the control ideas of the optimal backstepping technique, proposing an event-triggered optimal tracking control scheme for a class of strict-feedback nonlinear systems with non-affine and nonlinear faults. A simplified…

Optimization and Control · Mathematics 2024-06-13 Ling Wang , Xin Wang , Ziming Wang

Event-triggered and self-triggered control have been proposed in recent years as promising control strategies to reduce communication resources in Networked Control Systems (NCSs). Based on the notion of set-invariance theory, this note…

Optimization and Control · Mathematics 2018-01-18 Kazumune Hashimoto , Dimos V. Dimarogonas , Shuichi Adachi

This paper investigates the design of self-triggered control for networked control systems (NCS), where the dynamics of the plant is unknown apriori. To deal with the nature of the self-triggered control, in which state measurements are…

Systems and Control · Electrical Eng. & Systems 2022-02-22 Wang Zhijun , Kazumune Hashimoto , Wataru Hashimoto , Shigemasa Takai

We present a data-based approach to design event-triggered state-feedback controllers for unknown continuous-time linear systems affected by disturbances. By an event, we mean state measurements transmission from the sensors to the…

Systems and Control · Electrical Eng. & Systems 2022-08-25 Claudio De Persis , Romain Postoyan , Pietro Tesi

This paper proposes an event-triggered polynomial control method for trajectory tracking by unicycle robots. In this method, each control input between two consecutive events is a polynomial and its coefficients are chosen to minimize the…

Systems and Control · Electrical Eng. & Systems 2025-04-07 Harini V , Anusree Rajan , Bharadwaj Amrutur , Pavankumar Tallapragada

Scheduling the maintenance based on the condition, respectively the degradation level of the system leads to improved system's reliability while minimizing the maintenance cost. Since the degradation level changes dynamically during the…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-11-30 Pegah Rokhforoz , Olga Fink

Recent studies have shown that adaptively regulating the sampling rate results in significant reduction in computational resources in embedded software based control. Selecting a uniform sampling rate for a control loop is robust, but…

Systems and Control · Computer Science 2015-06-30 Rajorshee Raha , Soumyajit Dey , Partha Pratim Chakrabarti , Pallab Dasgupta

This paper investigates an aperiodic distributed model predictive control approach for multi-agent systems (MASs) in which parameterized synchronization constraints is considered and an innovative self-triggered criterion is constructed.…

Systems and Control · Electrical Eng. & Systems 2024-05-21 Qianqian Chen , Shaoyuan Li

This paper studies the synchronization of stochastic linear systems which are subject to a general class of noises, in the sense that the noises are bounded in covariance but might be correlated with the states of agents and among each…

Systems and Control · Electrical Eng. & Systems 2022-05-16 Jiaqi Yan , Yilin Mo , Hideaki Ishii

This paper addresses the design of an event-triggered, data-based, and performance-oriented adaption method for model predictive control (MPC). The performance of such a strategy strongly depends on the accuracy of the prediction model,…

Systems and Control · Electrical Eng. & Systems 2026-03-13 Samuel Mallick , Laura Boca de de Giuli , Alessio La Bella , Azita Dabiri , Bart De Schutter , Riccardo Scattolini

Time-triggered and event-triggered control strategies for stabilization of an unstable plant over a rate-limited communication channel subject to unknown, bounded delay are studied and compared. Event triggering carries implicit…

Optimization and Control · Mathematics 2017-10-10 Mohammad Javad Khojasteh , Pavankumar Tallapragada , Jorge Cortes , Massimo Franceschetti

Methods for split conformal prediction leverage calibration samples to transform any prediction rule into a set-prediction rule that complies with a target coverage probability. Existing methods provide remarkably strong performance…

Machine Learning · Statistics 2025-10-15 Santiago Mazuelas

A conceptual design methodology is proposed for event-triggered based power system wide area damping controller. The event-triggering mechanism is adopted to reduce the communication burden between origin of the remote signal and the wide…

Optimization and Control · Mathematics 2016-01-05 Mahendra Bhadu , Niladri Sekhar Tripathy , I. N. Kar , Nilanjan Senroy

We investigate the performance and sampling variability of estimated forecast combinations, with particular attention given to the combination of forecast distributions. Unknown parameters in the forecast combination are optimized according…

Methodology · Statistics 2022-06-07 Ryan Zischke , Gael M. Martin , David T. Frazier , D. S. Poskitt

Despite the extensive literature on training loss functions, the evaluation of generalization on the validation set remains underexplored. In this work, we conduct a systematic empirical and statistical study of how the validation criterion…

Machine Learning · Computer Science 2026-02-26 Andrea Apicella , Francesco Isgrò , Andrea Pollastro , Roberto Prevete
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