math.OC papers | Gist.Science

Aero-Promptness: Drag-Aware Aerodynamic Manipulability for Propeller-driven Vehicles

This paper introduces Drag-Aware Aerodynamic Manipulability (DAAM), a geometric framework for control allocation in redundant multirotors that utilizes a Riemannian metric to explicitly account for motor torque limits and aerodynamic drag, thereby generating a state-dependent manipulability volume that serves as a natural barrier function to optimize redundancy resolution while characterizing the resulting smooth manifolds and global jump discontinuities.

Antonio FranchiTue, 10 Ma🔢 math

Robust Cooperative Output Regulation of Discrete-Time Heterogeneous Multi-Agent Systems

This paper addresses the robust cooperative output regulation of discrete-time uncertain heterogeneous multi-agent systems by establishing global and local sufficient conditions for the existence and design of structured control gains, utilizing structured Lyapunov inequalities to derive linear matrix inequalities (LMIs) that enable both centralized and distributed controller synthesis.

Kursad Metehan Gul, Selahattin Burak SarsilmazTue, 10 Ma🔢 math

Evaluating consumption effects of intelligent control algorithms for district heated buildings

This paper proposes a transparent, model-based approach to isolate and decompose the energy consumption effects of intelligent district heating control algorithms from other building changes, addressing the limitations of existing evaluation methods using a decade of real-world data.

Antti Solonen, Arttu Häkkinen, Sallamaari Rapo, Antti Mäkinen, Sampo Kaukonen, Felipe UribeTue, 10 Ma🔢 math

IQC-Based Output-Feedback Control of LPV Systems with Time-Varying Input Delays

This paper proposes a convex, delay-dependent $\mathcal{H}_\infty$ output-feedback control synthesis method for LPV systems with time-varying input delays by integrating parameter-dependent Lyapunov functions with dynamic IQC multipliers and an exact-memory controller structure, thereby overcoming the non-convexity of memoryless designs to achieve reduced conservatism and improved performance.

Fen WuTue, 10 Ma🔢 math

Learning-Based Robust Control: Unifying Exploration and Distributional Robustness for Reliable Robotics via Free Energy

This paper proposes a distributionally robust free energy principle that unifies exploration and uncertainty-aware learning to enable reliable, zero-shot robotic manipulation in real-world environments without task-specific fine-tuning.

Hozefa Jesawada, Giovanni Russo, Abdalla Swikir, Fares Abu-DakkaTue, 10 Ma🔢 math

Distributionally Robust Geometric Joint Chance-Constrained Optimization: Neurodynamic Approaches

This paper introduces a two-time scale neurodynamic duplex approach utilizing projection equations to solve distributionally robust geometric joint chance-constrained optimization problems with unknown distributions, demonstrating convergence to the global optimum through neural networks in applications such as shape optimization and telecommunications.

Ange Valli (L2S), Siham Tassouli (OPTIM), Abdel Lisser (L2S)Tue, 10 Ma🔢 math

Faster Parametric Submodular Function Minimization by Exploiting Duality

This paper presents the first weakly polynomial-time algorithms for the parametric submodular line search problem by exploiting a dual formulation and cutting-plane methods to reduce the number of calls to the exact submodular function minimization oracle.

Swati Gupta, Alec ZhuTue, 10 Ma🔢 math

Rethinking Strict Dissipativity for Economic MPC

This paper introduces the novel concept of two-storage strict dissipativity to bridge the gap between storage functions and value functions in economic model predictive control, proving it as a necessary and sufficient condition for asymptotic stability while offering easier verification and new terminal cost designs.

Mario ZanonTue, 10 Ma🔢 math

First-Order Geometry, Spectral Compression, and Structural Compatibility under Bounded Computation

This paper proposes an operator-theoretic framework that encodes structural constraints via self-adjoint operators to unify gradient projection, spectral compression, and multi-objective feasibility under a single geometric structure, revealing how constraints distort ascent geometry and concentrate effective dynamics along dominant spectral modes.

Changkai LiTue, 10 Ma🔢 math

Intrinsic Sequentiality in P: Causal Limits of Parallel Computation

This paper demonstrates that a specific polynomial-time decision problem, defined by causal token traversal constraints, inherently requires linear time to execute and cannot be accelerated by parallel computation, thereby revealing a fundamental gap between logical parallelism and causal executability that places the problem outside the classical $\mathbf{NC}$ complexity class.

Jing-Yuan WeiTue, 10 Ma🔢 math

Loopless Proximal Riemannian Gradient EXTRA for Distributed Optimization on Compact Manifolds

This paper proposes the Proximal Riemannian Gradient EXTRA (PR-EXTRA) algorithm, a loopless distributed optimization method for composite problems on compact manifolds that achieves an $\mathcal{O}(1/K)$ sublinear convergence rate using only single-round communication per iteration.

Yongyang Xiong, Chen Ouyang, Keyou You, Yang Shi, Ligang WuTue, 10 Ma🔢 math

Capacity of Non-Separable Networks with Restricted Adversaries

This paper investigates the capacity of single-source multicasting in networks with restricted adversaries, demonstrating that classical bounds are insufficient and requiring joint code design, while providing exact capacity results, improved lower bounds, and new generalizations for specific network families.

Christopher Hojny, Altan B. Kılıç, Sascha Kurz, Alberto RavagnaniTue, 10 Ma🔢 math

Optimal Embedding of Wiring Diagrams in Constrained Three-Dimensional Spaces

This paper proposes a mixed-integer linear programming framework that discretizes the three-dimensional wiring diagram problem into structured network graphs to optimize cable or pipeline routing while satisfying complex industrial constraints such as obstacle avoidance, safety distances, and constructibility.

Víctor Blanco, Gabriel González, Justo PuertoTue, 10 Ma🔢 math

Stability of Two-Stage Stochastic Programs Under Problem-Dependent Costs

This paper establishes a direct primal-based stability framework for two-stage stochastic programs with problem-dependent costs, proving Lipschitz continuity of the optimal value function under a regret domination property and demonstrating its applicability to both continuous and mixed-integer second-stage problems.

Nils Peyrousset, Benoît TranTue, 10 Ma🔢 math

Finite-Horizon Optimal Consumption and Investment with Time-Varying Job-Switching Costs

This paper characterizes an agent's optimal consumption, investment, and time-varying job-switching strategies over a finite horizon by reducing the dual problem to a parabolic double obstacle problem with time-dependent obstacles, for which existence, uniqueness, and free boundary smoothness are rigorously established using PDE theory.

Gugyum Ha, Junkee Jeon, Jihoon OkTue, 10 Ma🔢 math

A Distributed Method for Cooperative Transaction Cost Mitigation

This paper proposes a distributed convex optimization protocol that enables portfolio managers to iteratively adjust their independent trades based on shared cost estimates, thereby significantly reducing market impact and transaction costs without requiring the disclosure of private trading strategies or direct communication between managers.

Nikhil Devanathan, Logan Bell, Dylan Rueter, Stephen BoydTue, 10 Ma🔢 math

Column Generation for the Micro-Transit Zoning Problem

This paper generalizes the Micro-Transit Zoning Problem to incorporate a global budget and proposes an efficient Column Generation framework with pricing heuristics that outperforms existing enumeration-based approaches in solution quality and scalability across major U.S. cities.

Hins Hu, Rishav Sen, Jose Paolo Talusan, Abhishek Dubey, Aron Laszka, Samitha SamaranayakeTue, 10 Ma🔢 math

Continuous-Time Heterogeneous Agent Models with Recursive Utility and Preference for Late Resolution

This paper establishes the existence and uniqueness of a constraint viscosity solution to the Hamilton-Jacobi-Bellman equation and investigates the solution properties of continuous-time heterogeneous agent models formulated as mean field games with recursive utility and a preference for late resolution of uncertainty.

Yves Achdou, Qing TangTue, 10 Ma🔢 math

Weak Scalability of time parallel Schwarz methods for parabolic optimal control problems

This paper investigates the weak scalability of time parallel Schwarz methods for parabolic optimal control problems by developing novel theoretical tools to analyze convergence and spectral properties, thereby confirming the method's suitability for large-scale simulations on high-performance computing architectures.

Liu-Di Lu, Tommaso VanzanTue, 10 Ma🔢 math

Stabilization of monotone control systems with input constraints

This paper presents a stabilizing output-feedback controller for monotone control systems that respects input constraints, proving that if a system is stabilizable with unconstrained controls and the equilibrium control lies within the constraint set's interior, a saturated controller also achieves stabilization.

Till Preuster, Hannes Gernandt, Manuel SchallerTue, 10 Ma🔢 math

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