Summary of Rocket Landing Control with Grid Fins and Path-following Using Mpc, by Junhao Yu et al.
Rocket Landing Control with Grid Fins and Path-following using MPC
by Junhao Yu, Jiarun Wei
First submitted to arxiv on: 25 May 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This project optimizes rocket landing trajectories to minimize fuel consumption using various techniques. A batch approach generates an optimal and feasible trajectory, which is then followed by a Model Predictive Control (MPC) algorithm called Trajectory Optimizing Path following Estimation from Demonstration (TOPED). TOPED generalizes to similar initial states and models, with a novel cost function used to solve the MPC problem. The approach demonstrates good performance under model mismatch and different initial states. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary To optimize rocket landing trajectories and minimize fuel consumption, researchers developed an algorithm called Trajectory Optimizing Path following Estimation from Demonstration (TOPED). TOPED uses a Model Predictive Control (MPC) method to follow the optimal trajectory generated using a batch approach. This allows the algorithm to generalize to similar initial states and models. |
