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In this paper, we propose a distributed model predictive control (DMPC) scheme for linear time-invariant constrained systems which admit a separable structure. To exploit the merits of distributed computation algorithms, the stabilizing…

Optimization and Control · Mathematics 2018-03-22 Georgios Darivianakis , Annika Eichler , John Lygeros

This paper addresses the challenge of ensuring robustness in the presence of system perturbations for symbolic control techniques. Given a discrete-time control system that is related to its symbolic model by an alternating simulation…

Systems and Control · Electrical Eng. & Systems 2025-07-17 Youssef Ait Si , Antoine Girard , Adnane Saoud

The control Lyapunov function (CLF) approach to nonlinear control design is well established. Moreover, when the plant is control affine and polynomial, sum-of-squares (SOS) optimization can be used to find a polynomial controller as a…

Optimization and Control · Mathematics 2024-09-16 Jason J. Bramburger , Steven Dahdah , James Richard Forbes

We present a robust generalization of the synthetic control method for comparative case studies. Like the classical method, we present an algorithm to estimate the unobservable counterfactual of a treatment unit. A distinguishing feature of…

Econometrics · Economics 2017-11-21 Muhammad Jehangir Amjad , Devavrat Shah , Dennis Shen

Control synthesis from temporal logic specifications has gained popularity in recent years. In this paper, we use a model predictive approach to control discrete time linear systems with additive bounded disturbances subject to constraints…

Systems and Control · Computer Science 2016-05-24 Sadra Sadraddini , Calin Belta

The optimal control of a mechanical system is of crucial importance in many realms. Typical examples are the determination of a time-minimal path in vehicle dynamics, a minimal energy trajectory in space mission design, or optimal motion…

Optimization and Control · Mathematics 2008-10-09 S. Ober-Bloebaum , O. Junge , J. E. Marsden

In this paper, we present a distributed model predictive control (DMPC) scheme for dynamically decoupled systems which are subject to state constraints, coupling state constraints and input constraints. In the proposed control scheme,…

Systems and Control · Electrical Eng. & Systems 2024-08-17 Adrian Wiltz , Fei Chen , Dimos V. Dimarogonas

This paper proposes a robust self-triggered distributed model predictive control (DMPC) scheme for a family of Discrete-Time linear systems with local (uncoupled) and global (coupled) constraints. To handle the additive disturbance,…

Systems and Control · Electrical Eng. & Systems 2020-12-17 Zhengcai Li

We present a new domain-agnostic synthesis technique for generating programs from input-output examples. Our method, called metric program synthesis, relaxes the well-known observational equivalence idea (used widely in bottom-up…

Programming Languages · Computer Science 2022-10-12 John Feser , Isil Dillig , Armando Solar-Lezama

This paper presents a control synthesis algorithm for dynamical systems to satisfy specifications given in a fragment of linear temporal logic. It is based on an abstraction-refinement scheme with nonuniform partitions of the state space. A…

Systems and Control · Computer Science 2018-04-13 Oscar Lindvall Bulancea , Petter Nilsson , Necmiye Ozay

Most control synthesis methods under temporal logic properties require a model of the system, however, identifying such a model can be a challenging task. In this work, we develop a direct data-driven control synthesis method for temporal…

Systems and Control · Electrical Eng. & Systems 2024-04-05 Birgit C. van Huijgevoort , Chris Verhoek , Roland Tóth , Sofie Haesaert

This paper provides new insights into the asymptotic properties of the synthetic control method (SCM). We show that the synthetic control (SC) weight converges to a limiting weight that minimizes the mean squared prediction risk of the…

Econometrics · Economics 2022-11-23 Xiaomeng Zhang , Wendun Wang , Xinyu Zhang

Modal synthesis is an important area of physical modeling whose exploration in the past has been held back by a large number of control parameters, the scarcity of general-purpose design tools and the difficulty of obtaining the…

Sound · Computer Science 2007-05-23 Ilia Bisnovatyi

Discrete diffusion models have emerged as powerful tools for high-quality data generation. Despite their success in discrete spaces, such as text generation tasks, the acceleration of discrete diffusion models remains under-explored. In…

Machine Learning · Computer Science 2024-12-09 Zixiang Chen , Huizhuo Yuan , Yongqian Li , Yiwen Kou , Junkai Zhang , Quanquan Gu

We propose a hierarchical control framework for the synthesis of correct-by-construction controllers for nonlinear control-affine systems with respect to reach-avoid-stay specifications. We first create a low-dimensional continuous…

Systems and Control · Electrical Eng. & Systems 2021-04-19 Pierre-Jean Meyer , He Yin , Astrid H. Brodtkorb , Murat Arcak , Asgeir J. Sørensen

Consistent distillation methods have evolved into effective techniques that significantly accelerate the sampling process of diffusion models. Although existing methods have achieved remarkable results, the selection of target timesteps…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Qi Wang , Shuliang Zhu , Jinjia Zhou

Step distillation has become a leading technique for accelerating diffusion models, among which Distribution Matching Distillation (DMD) and Consistency Distillation are two representative paradigms. While consistency methods enforce…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Tao Liu , Hao Yan , Mengting Chen , Taihang Hu , Zhengrong Yue , Zihao Pan , Jinsong Lan , Xiaoyong Zhu , Ming-Ming Cheng , Bo Zheng , Yaxing Wang

Discrete (DTCs) and continuous time crystals (CTCs) are novel dynamical many-body states, that are characterized by robust self-sustained oscillations, emerging via spontaneous breaking of discrete or continuous time translation symmetry.…

This paper reinterprets the Synthetic Control (SC) framework through the lens of weighting philosophy, arguing that the contrast between traditional SC and Difference-in-Differences (DID) reflects two distinct modeling mindsets: sparse…

Methodology · Statistics 2025-10-31 Le Wang , Xin Xing , Youhui Ye

Control contraction metrics (CCMs) are a new approach to nonlinear control design based on contraction theory. The resulting design problems are expressed as pointwise linear matrix inequalities and are and well-suited to solution via…

Optimization and Control · Mathematics 2014-06-06 Ian R. Manchester , Jean-Jacques E. Slotine