Stability Analysis of Hypersampled Model Predictive Control
원문 초록
This paper introduces a new framework for analyzing the stability of discrete-time model predictive controllers acting on continuous-time systems. The proposed framework introduces the distinction between discretization time (used to generate the optimal control problem) and sampling time (used to implement the controller). The paper not only shows that these two time constants are independent, but also motivates the benefits of selecting a sampling time that is smaller than the discretization time. The resulting approach, hereafter referred to as Hypersampled Model Predictive Control, overcomes the traditional trade-off between performance and computational complexity that arises when selecting the sampling time of traditional discrete-time model predictive controllers.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Differentiable Nonlinear Model Predictive Control
Deep Operator Neural Network Model Predictive Control
Data-driven Model Predictive Control using MATLAB
Model Tensor Planning
Reimagination with Test-time Observation Interventions: Distractor-Robust World Model Predictions for Visual Model Predictive Control
Parallel Branch Model Predictive Control on GPUs
토론
이 논문과 연결된 포럼 글이 아직 없습니다.