Machine Learning Based Adaptive Prediction Horizon in Finite Control Set Model Predictive Control

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Adaptive Horizon Model Predictive Control

Adaptive Horizon Model Predictive Control (AHMPC) is a scheme for varying as needed the horizon length of Model Predictive Control (MPC). Its goal is to achieve stabilization with horizons as small as possible so that MPC can be used on faster or more complicated dynamic processes. Beside the standard requirements of MPC including a terminal cost that is a control Lyapunov function, AHMPC requi...

متن کامل

Finite Control Set Model Predictive Control in Power Converters

This study presents a detailed description of a cost function-based predictive control strategy called Finite Control Set Model Predictive Control (FCS-MPC) and its applications to the control of power electronics converters. The basic concepts, operating principles and general properties of this control technique have been explained. The analysis is performed on two different power converter t...

متن کامل

Estimates on the Prediction Horizon Length in Model Predictive Control∗

We are concerned with model predictive control without stabilizing terminal constraints or costs. Here, our goal is to determine a prediction horizon length for which stability or a desired degree of suboptimality is guaranteed. To be more precise, we extend the methodology introduced in [7] in order to improve the resulting performance bounds. Furthermore, we carry out a comparison with other ...

متن کامل

Finite horizon robust model predictive control with terminal cost constraints

In this paper, we develop a finite horizon model predictive control algorithm which is robust to modelling uncertainties. A moving average system matrix is constructed to capture modelling uncertainties and facilitate the future output prediction. The paper is mainly focused on the step tracking problem. Using linear matrix inequality techniques, the design is converted into a semi-definite opt...

متن کامل

Finite Horizon Robust Model Predictive Control Using Linear Matrix Inequalities

In this paper, we develop a finite horizon model predictive control algorithm which is robust to model uncertainties. A moving average system matrix is constructed to capture model uncertainties and facilitate future output predictions. The paper is focused on step tracking control. Using linear matrix inequality techniques, the design is converted into a semi-definite optimization problem. Clo...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IEEE Access

سال: 2018

ISSN: 2169-3536

DOI: 10.1109/access.2018.2839519