Results 31 to 40 of about 303,155 (330)

Angle Tracking Robust Learning Control for Pneumatic Artificial Muscle Systems

IEEE Access, 2021
Pneumatic artificial muscle systems have been widely used in the applications of biomimetic robots and medical auxiliary devices. The existence of high nonlinearities, uncertainties and time-varying characteristics in pneumatic artificial muscle systems ...
Dong Guo, Wei Wang, Yuntao Zhang, Qiuzhen Yan, Jianping Cai   +4 more
doaj   +1 more source

Adaptive development and maintenance of user-centric software systems [PDF]

, 2004
A software system cannot be developed without considering the various facets of its environment. Stakeholders – including the users that play a central role – have their needs, expectations, and perceptions of a system.
Alspaugh, Beynon-Davies, Borgholm, Breitman, Bødker, Claus Pahl, Crnkovic, Dix, Egyed, Grønbæk, Kazman, Kotonya, Kösters, Lee, Lung, Medvidovic, Moisiadis, Nuseibeh, Pahl, Russo, Shaw, Smeaton, Smeaton, Sommerville, Sutcliffe   +24 more
core   +1 more source

Extremum Seeking-based Iterative Learning Linear MPC

, 2014
In this work we study the problem of adaptive MPC for linear time-invariant uncertain models. We assume linear models with parametric uncertainties, and propose an iterative multi-variable extremum seeking (MES)-based learning MPC algorithm to learn on ...
Benosman, Mouhacine, Di Cairano, Stefano, Weiss, Avishai   +2 more
core   +1 more source

Iterative nonlinear model predictive control of a PH reactor. A comparative analysis [PDF]

, 2005
IFAC WORLD CONGRESS (16) (16.2005.PRAGA, REPÚBLICA CHECA)This paper describes the control of a batch pH reactor by a nonlinear predictive controller that improves performance by using data of past batches.
Bordons Alba, Carlos, Ramos Cueli, José
core   +1 more source

Fuzzy System-Based Position Tracking Iterative Learning Control for Tank Gun Control Systems With Error Constraints

IEEE Access, 2022
In order to get accurate position tracking and effective system constraint together for tank gun control systems, a fuzzy system-based barrier adaptive iterative learning control scheme is proposed.
Zheng Hong, Qiuzhen Yan, Xiushan Wu, Jianping Cai   +3 more
doaj   +1 more source

A Novel Iterative Second-Order Neural-Network Learning Control Approach for Robotic Manipulators

IEEE Access, 2023
Iterative Learning Control (ILC) is known as a high-accuracy control strategy for repetitive control missions of mechatronic systems. However, applying such learning controllers for robotic manipulators to result in excellent control performances is now ...
Dang Xuan Ba, Nguyen Trung Thien, Joonbum Bae   +2 more
doaj   +1 more source

Distributed power control over interference channels using ACK/NACK feedback [PDF]

, 2014
In this work, we consider a network composed of several single-antenna transmitter-receiver pairs in which each pair aims at selfishly minimizing the power required to achieve a given signal-to-interference-plus-noise ratio. This is obtained modeling the
Andreotti, Riccardo, Debbah, Merouane, Marchetti, Leonardo, Sanguinetti, Luca   +3 more
core   +3 more sources

Iterative Learning with Adaptive Sliding Mode Control for Trajectory Tracking of Fast Tool Servo Systems

Applied Sciences
To address the tracking control problem of the periodic motion fast tool servo system (FTS), we propose a control method that combines adaptive sliding mode control with closed-loop iterative learning control.
Xiuying Xu, Pengbo Liu, Shuaishuai Lu, Fei Wang, Jingfang Yang, Guangchun Xiao   +5 more
doaj   +1 more source

Iterative Learning Tracking Control of a Hybrid-Driven Based Three-Cable Parallel Manipulator

Advances in Mechanical Engineering, 2014
The aim of this work was to present iterative learning tracking control of a hybrid-driven based three-cable parallel manipulator (HDCPM). The HDCPM has the advantages of both cable parallel manipulator and hybrid-driven planar five-bar mechanism. Design
Bin Zi, Jianbin Cao, Sen Qian
doaj   +1 more source

Model-Data Driven Learning Adaptive Robust Control of Precision Mechatronic Motion Systems With Comparative Experiments

IEEE Access, 2018
In order to meet the rigorous motion accuracy requirement and efficiently utilize the repetitive-task characteristics in modern precision industry, this paper concentrates on the comprehensive research of model-based data-driven learning adaptive robust ...
Chuxiong Hu, Zhipeng Hu, Yu Zhu, Ze Wang, Suqin He   +4 more
doaj   +1 more source