Rocket Landing Control with Grid Fins and Path-following using MPC
원문 초록
In this project, we attempt to optimize a landing trajectory of a rocket. The goal is to minimize the total fuel consumption during the landing process using different techniques. Once the optimal and feasible trajectory is generated using batch approach, we attempt to follow the path using a Model Predictive Control (MPC) based algorithm, called Trajectory Optimizing Path following Estimation from Demonstration (TOPED), in order to generalize to similar initial states and models, where we introduce a novel cost function for the MPC to solve. We further show that TOPED can follow a demonstration trajectory well in practice under model mismatch and different initial states.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Differentiable Nonlinear Model Predictive Control
Evaluating the Impact of Model Accuracy for Optimizing Battery Energy Storage Systems
Re4MPC: Reactive Nonlinear MPC for Multi-model Motion Planning via Deep Reinforcement Learning
Deep Operator Neural Network Model Predictive Control
Knot So Simple: A Minimalistic Environment for Spatial Reasoning
Efficient Configuration-Constrained Tube MPC via Variables Restriction and Template Selection
토론
이 논문과 연결된 포럼 글이 아직 없습니다.