Results 51 to 60 of about 826,819 (165)

Enhanced Model Predictive Control Using State Variable Feedback for Steady-State Error Cancellation

Sensors
The rapid dynamic responses of predictive control algorithms are widely acknowledged. However, achieving accurate steady-state reference tracking hinges not just on a precise mathematical model of the system but also on its parameters.
Marcos Andreu, Jaime Rohten, José Espinoza, José Silva, Esteban Pulido, Lesyani Leon   +5 more
doaj   +1 more source

Estimation and control using sampling-based Bayesian reinforcement learning

IET Cyber-Physical Systems, 2019
Real-world autonomous systems operate under uncertainty about both their pose and dynamics. Autonomous control systems must simultaneously perform estimation and control tasks to maintain robustness to changing dynamics or modelling errors.
Patrick Slade, Zachary N. Sunberg, Zachary N. Sunberg, Mykel J. Kochenderfer   +3 more
doaj   +1 more source

Extreme learning-based non-linear model predictive controller for an autonomous underwater vehicle: simulation and experimental results

IET Cyber-systems and Robotics, 2019
In this study, an extreme learning-based non-linear model predictive controller (NMPC) is proposed for path following planning of an autonomous underwater vehicle (AUV) using horizontal way-points. The proposed controller comprises a kinematic controller
Biranchi Narayan Rath, Bidyadhar Subudhi
doaj   +1 more source

Voltage space vector‘s computation for current control in three phase converters

Revista Facultad de Ingeniería Universidad de Antioquia, 2012
This work presents two current loop techniques, for three phase voltage source converters (VSC) used as controlled rectifiers (CR) operating at unity power factor.
Alberto Berzoy, Julio Viola, José Restrepo   +2 more
doaj   +1 more source

Conformal Loss-Controlling Prediction

IEEE Transactions on Neural Networks and Learning Systems
Conformal prediction is a learning framework controlling prediction coverage of prediction sets, which can be built on any learning algorithm for point prediction. This work proposes a learning framework named conformal loss-controlling prediction, which extends conformal prediction to the situation where the value of a loss function needs to be ...
Di Wang, Ping Wang, Zhong Ji, Xiaojun Yang, Hongyue Li   +4 more
openaire   +3 more sources

Enhanced Vehicle Dynamics and Safety through Tire–Road Friction Estimation for Predictive ELSD Control under Various Conditions of General Racing Tracks

Applied Sciences
This study focuses on the tire–road friction estimation for the predictive control strategy of electronically limited slip differential (ELSD) to improve the handling and acceleration performance of front-wheel drive cars, which typically suffer from ...
Seunghoon Woo, Seunguk Jeon, Eunhyek Joa, Donghoon Shin   +3 more
doaj   +1 more source

Virtual position predictive control with system delay observer to improve PMLSM position tracking accuracy

IET Electric Power Applications
To improve the position tracking accuracy of permanent magnet linear synchronous motors (PMLSM), this paper introduces a virtual position predictive control (VPPC) with a system delay observer (SDO). Un‐like conventional position predictive control (CPPC)
Rongkun Wang, Congwei Su, Quankai Du, Qibin Xiong, Yujia Zhuang, Xinyi Zhang, Xinhua Guo   +6 more
doaj   +1 more source

Predictive control method with conduction mode detection to suppress input current distortion of three‐level power factor correction

IET Electric Power Applications
A novel predictive control method with conduction mode detection is proposed to suppress input current distortion of three‐level power factor correction (PFC) converters.
Xifeng Xie, Zeliang Shu, Rongxin Chen, Jianghong Yin, Chunxiang Ling   +4 more
doaj   +1 more source

Robust predictive control strategy for grid‐connected inverters with ultra‐local model based on linear matrix inequality

IET Power Electronics
To address the issue of poor robustness in the model predictive control of grid‐connected inverters due to disturbances in load model parameters, this article developed an ultra‐local model robust predictive controller based on Linear Matrix Inequality ...
Chunxi Liu, Fangrui Hong, Zhile Liu, Li Zhou, Xuanxu Jin, Zhiwei Lin   +5 more
doaj   +1 more source

Prediction Horizon-varying Model Predictive Control (MPC)for Autonomous Vehicle Control

Electronics
Abstract The prediction horizon is a key parameter in model predictive control (MPC), related to the effectiveness and stability of model predictive control. In vehicle control, the selection of prediction horizon is influenced by factors such as speed, path curvature, and target point density.
Zhenbin Chen, Jiaqin Lai, Peixin Li, Omar I. Awad, Yubing Zhu   +4 more
openaire   +1 more source