EnergySix-legged robot developed in Penza for pipeline inspectionCNews · 3dModellingEnhanced Imitation Learning of Model Predictive Control through Importance WeightingarXiv — Systems and Control (eess.SY) · 4dModellingLimited knowledge exchange across biological subfields in agent-based modellingarXiv — Physics and Society (physics.soc-ph) · 4dDigital twinReasoner-checked ontology crosswalks for a national digital twinarXiv API — полнотекстовый поиск "digital twin" · 5dDigital twinDigital twin speeds up reinforcement learning for lab robotsarXiv API — полнотекстовый поиск "digital twin" · 5dDigital twinDataset for deciding between evidence gathering and action in control-system incidentsarXiv — Computational Engineering, Finance, and Science (cs.CE) · 5dDigital twinSparse stochastic twins can outperform exact digital twinsarXiv — Computational Engineering, Finance, and Science (cs.CE) · 5dModellingPluralism of rival models in network models of sciencearXiv — Multiagent Systems (cs.MA) · 5dForecastingEstimation and MPC for balancing a wheel-legged robot under unknown disturbancesarXiv — Systems and Control (eess.SY) · 5dDigital twinConsolidating dispersed DSO data into a digital twin of the distribution gridarXiv API — полнотекстовый поиск "digital twin" · 6dDigital twinIntegrating ML and uncertainty quantification for real-time decisions in digital twinsarXiv API — полнотекстовый поиск "digital twin" · 6dDigital twinBiases in end-to-end digital twins built from chained modelsarXiv API — полнотекстовый поиск "digital twin" · 5d
A nonlinear adaptive predictive control method (NPCAC) is proposed that identifies a pseudo-linear model online from input-output data without prior training. It combines recursive least squares with information forgetting and iterative MPC, tested with polynomial, Fourier, and spline basis functions. The approach handles systems with high uncertainty.
Why it matters
This is relevant for real-time control of complex nonlinear processes requiring rapid adaptation.
Original headline
Nonlinear Predictive Cost Adaptive Control of Pseudo-Linear Input-Output Models Using Polynomial, Fourier, and Cubic Spline Observables
arXiv:2611.06622v1 Announce Type: new Abstract: The approximation of model predictive control (MPC) algorithms with neural network models has received significant attention in the power electronics research community, as a valuable tool to enable the real-time implementation of computationally…
A bibliometric analysis of 22,936 agent-based modelling articles from Web of Science, classified by an LLM into biological subfields. Based on citations and author overlap, 83%, 81% and 69% of references in ecology, epidemiology and oncology stay within their own subfield.
The authors propose a theoretical and experimental model comparing communities of agents that hold rival theories side by side with communities that fold everything they hear into a single model. The work builds on Feyerabend's idea of theoretical pluralism, where coexistence of incompatible theories helps science work.
