ModellingParallel branch MPC on GPUsarXiv — Systems and Control (eess.SY) · yesterdayModellingImpact of shared autonomous vehicles in microtransit: Atlanta casearXiv — Systems and Control (eess.SY) · yesterdayModellingHybrid simulation of circular supply chains in healthcarearXiv — Systems and Control (eess.SY) · yesterdayDigital twinFDF tool simplifies building AI digital twinsarXiv API — полнотекстовый поиск "digital twin" · yesterdayForecastingMPC and genetic algorithm for flying pendulum controlarXiv — Systems and Control (eess.SY) · yesterdayForecastingHybrid control architecture for safe vehicle lateral controlarXiv — Systems and Control (eess.SY) · yesterdayForecastingAdaptive MPC for ground vehicles: review and implementationarXiv — Systems and Control (eess.SY) · yesterdayDigital twinML-assisted Bayesian Calibration of Accelerator Digital TwinarXiv API — полнотекстовый поиск "digital twin" · yesterdayDigital twinDigital Twin Testbed for Cyberattack and Defense Analysis in Hospital IT/OT EnvironmentsarXiv API — полнотекстовый поиск "digital twin" · yesterdayModellingGenerative Agent-based Simulation of Mobility Policy Preferences from SurveysarXiv — Computers and Society (cs.CY) · 2dForecastingScalable Gaussian Process with Trigonometric Features for Safe MPCarXiv — Systems and Control (eess.SY) · 2dForecastingTwo-Layer MPC for Sustainable Data Centers with Workload Flexibility and Heat RecoveryarXiv — Systems and Control (eess.SY) · 2d
A GPU-based solver for trajectory planning problems using branch model predictive control is presented. The solver is based on iterative LQR, multiple-shooting formulation, and augmented Lagrangian method for constraint handling. Numerical experiments show superiority over a CPU-based solver on large-scale problems.
Why it matters
Accelerating MPC computations on GPU enables real-time planning for large systems, which is critical for autonomous vehicles and robotics.
The integration of shared autonomous vehicles (SAVs) into microtransit systems, which address the last-mile problem, is investigated. The Atlanta case study shows that SAVs can improve sustainability, convenience, and reliability compared to conventional fixed-route transit.
Researchers applied a hybrid discrete-event and agent-based simulation to analyze the transition to circular economy in healthcare supply chains. Using laparoscopic scissors as a case study, they assessed the impact of introducing reusable products on individual supply chain members and the entire system. The work accounts for uncertainties in flows and actor behavior, which was not done before.
An approach combining model predictive control (MPC) and an online genetic algorithm is proposed to estimate the unknown pendulum length in a flying inverted pendulum control problem. Experiments on a real setup confirmed the accuracy and robustness of the method under various initial conditions and disturbances.
