Abstract: The promise of model-predictive control (MPC) in robotics has led to extensive development of efficient numerical optimal control solvers in line with differential dynamic programming ...
Quadratically constrained quadratic programming (QCQP) problems appear in a wide range of engineering fields, including computer science, communication engineering, and finance. A key difficulty in ...
We consider the optimal scheduling of hydropower plants in a hydrothermal interconnected system. This problem, of outmost importance for large-scale power systems with a high proportion of hydraulic ...
Convolutional Neural Networks (CNNs) are pivotal in computer vision and Big Data analytics but demand significant computational resources when trained on large-scale datasets. Conventional training ...
This repository implements dynamic programming (DP) heuristics for solving the Quadratic Knapsack Problem (QKP). The QKP is a variant of the classical knapsack problem where the profit matrix includes ...
Community driven content discussing all aspects of software development from DevOps to design patterns. The Mojo programming language is new. In fact, it’s still under development. At the end of 2023, ...
Introduction: Path planning algorithms are challenging to implement with mobile robots in orchards due to kinematic constraints and unstructured environments with narrow and irregularly distributed ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Abstract: This article addresses the consensus tracking control of multiagent systems (MASs) via a quadratic programming (QP) optimization framework, where the control Lyapunov function (CLF) ...
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