Backend
Direct Vector Field Guidance for Path Following
arXiv cs.SY0 views
arXiv:2610.13576v1 Announce Type: new Abstract: This paper presents a path-following guidance framework for a turn-rate-constrained unmanned aerial vehicle (UAVs). The proposed guidance strategy uses commanded course angle as a tanh-hyperbolic shaping function of the lateral deviation from the desired path. Stability characteristics illustrating asymptotic convergence to the desired path are established using Lyapunov analysis. Analytical expressions for the turn-rate and corresponding maximum turn-rate bound are derived, enabling direct gain selection for a turn-rate-limited vehicle. Numerical simulations are performed for straight-line following scenarios under both ideal and non-ideal initial heading conditions. Furthermore, a comparative study against representative arctan-, arcsine-, and arccos-based vector-field guidance laws is conducted using analytically feasible gains selected from their respective turn-rate bounds. Comparative numerical results demonstrate the proposed formulation achieves reliable boundary convergence while maintaining smooth steering behavior and a compact analytical gain-design framework.
Source:https://arxiv.org/abs/2610.13576PreviousHierarchical Graph Neural Network for Probabilistic Power Flow with Grid Topology ContingenciesNextLearning-Based Power Flow Estimation with Sparse PMU Deployment in Power Systems
Related posts
Turn Today’s Messy Notes Into Tomorrow’s Checklist With AI
0dev.to AI
A 763B MoE at "2 Bits": Where the Bytes Really Go in the GSQ-RCO GGUFs, and Why 100% Recovery Sits Inside the Noise
0dev.to AI
How I ship fixes to open-source projects maintainers actually merge (with AI in the loop)
0dev.to AI
Prompt Injection Through Documents: How to Harden an LLM Extraction Pipeline
0dev.to AI
Keeping noindex, the sitemap and the image sitemap in agreement for programmatic pages
0dev.to AI
3 Things in AI You Should Know: Character.AI Files for Bankruptcy
0dev.to AI