惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
美团技术团队
Last Week in AI
Last Week in AI
WordPress大学
WordPress大学
博客园 - 三生石上(FineUI控件)
博客园 - 聂微东
雷峰网
雷峰网
阮一峰的网络日志
阮一峰的网络日志
博客园 - 叶小钗
IT之家
IT之家
Google DeepMind News
Google DeepMind News
D
Docker
J
Java Code Geeks
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
Apple Machine Learning Research
Apple Machine Learning Research
博客园 - 【当耐特】
V
V2EX
Hugging Face - Blog
Hugging Face - Blog
博客园 - Franky
月光博客
月光博客
宝玉的分享
宝玉的分享
酷 壳 – CoolShell
酷 壳 – CoolShell
aimingoo的专栏
aimingoo的专栏
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More

cs updates on arXiv.org

Beyond Binary Edits Robust Multimodal Knowledge Editing with Adversarial Subspace Alignment Agentic Proving for Program Verification MemAudit: Post-hoc Auditing of Poisoned Agent Memory via Causal Attribution and Structural Anomaly Detection OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents One Policy, Infinite NPCs: Persona-Traceable Shared RL Policies for Scalable Game Agents How Human-Like Are Large Language Models? A Register-Aware Linguistic Evaluation Framework Benchmarking Google Embeddings 2 against Open-Source Models for Multilingual Dense Retrieval and RAG Systems Structure-Guided Entity Resolution: Fine-Tuning LLMs for Robust Name Matching in Complex Linguistic Contexts Solving the Aircraft Disassembly Scheduling Problem Co-ReAct: Rubrics as Step-Level Collaborators for ReAct Agents CP or DP? Why Not Both: A Case Study in the Partial Shop Scheduling Problem Asking For An Old Friend: Diagnosing and Mitigating Temporal Failure Modes in LLM-based Statutory Question Answering EDGE-OPD: Internalizing Privileged Context with Evidence Guided On-Policy Distillation ARES: Automated Rubric Synthesis for Scalable LLM Reinforcement Learning SSDAU: Structured Semantic Data Augmentation for Joint Entity and Relation Extraction Naturalistic measure of social norms alignment Articulatory strategy as a source of variation in acoustic vowel dynamics When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems EquiSumm : A Gender Bias-Aware Framework for Inclusive Tweet Summarization Metacognition as Reward: Reinforcing LLM Reasoning via Knowledge and Regulation Signals From Correctness to Preference: A Framework for Personalized Agentic Reinforcement Learning Cultural Adaptation in Large Language Models for Political Discourse Emotion Recognition in Sign Language Conversation ClimateChat-300K: A Multi-Modal Facebook Dataset for Understanding Diverse Perspectives in Climate Communication AraHopeCorpus: Annotation Guidelines and Dataset for Hope Speech in Arabic Social Media Crisis Discourse Human-in-the-Loop Multi-Agent Ventilator Decision Support with Contextual Bandit Preference Learning Convergence Without Understanding: When Language Models Agree on Representations but Disagree on Reasoning DART: Semantic Recoverability for Structured Tool Agents Ontological Knowledge Blocks: Executable Compliance and Profile-Based Validation for Trustworthy AI Systems Parallel Context Compaction for Long-Horizon LLM Agent Serving
Minimum settling-time PI control of pure delay processes ...
[Submitted on 13 Jun 2026] · 2026-06-16 · via cs updates on arXiv.org

View PDF HTML (experimental)

Abstract:We solve, exactly, the problem of minimum settling-time PI control of a pure delay process K e^{-Ls} under the hard time-domain constraint of zero overshoot, y(t) <= 1 for all t. The closed loop is a neutral delay system whose step response is piecewise polynomial on the delay segments, with geometrically decaying jump discontinuities at the segment boundaries t = kL. The constrained optimum is characterized by an equioscillation-type contact structure whose active contacts sit at echo boundaries: kink maxima grazing the setpoint, jumps landing on the settling-band edge, and boundary troughs anchored to it. The number of contact equations equals the number of gains, so the optimum is exactly computable for every band delta. In a closed-form regime, delta in [(3-2 sqrt2)/4, (3-2 sqrt2)/2] approx [4.29%, 8.58%], the optimal gains are independent of delta: K Kp = 1 - sqrt2/2, K Ki L = sqrt2/2, and the optimal settling time is Ts*(delta) = (4 - sqrt2 - 2 sqrt(delta)) L. Outside this window the optimum solves an explicit two-equation polynomial system per regime, and Ts*(delta) is a staircase with exact flats at integer multiples of L from jump-landing pinning. As delta -> 0 the optimal gains converge to K Kp = e^{-2}, K Ki L = 4 e^{-2}, the generic multiplicity-induced-dominancy (GMID) point of the neutral quasipolynomial. The GMID response satisfies the hard constraint and uniquely maximizes the decay rate; yet at every finite delta the delta-adapted optimum strictly beats the fixed GMID tuning, by about 40% at delta = 2%. The MID point is thus the limit of the optimal gains without ever being the optimal tuning. A numerical extension to first-order-plus-time-delay plants quantifies the speed/robustness trade across Ms in [1.39, 1.76].

Submission history

From: Senol Gulgonul [view email]
[v1] Sat, 13 Jun 2026 18:05:41 UTC (436 KB)