Paper Info
Title
Iterative Learning Control for a Hydraulic Cushion.
Abstract
An Iterative Learning Control algorithm is presented for the force control circuit of a hydraulic cushion, which improves the existing control scheme based on classical PI control and feedback linearization. The circuit contains a proportional valve for regulating the pressure at the cylinder chamber and, therefore, the force applied by the cushion. The Iterative Learning Control filter design is based on the rejection of the valve's dynamics, which are filtered by a fourth-order low-pass filter. The filter is divided into two second-order filters to carry out forward and backward filtering and obtain zero-phase filtering. The proposed methodology improves the performance of the existing control scheme and reduces considerably the settling time and overshoot of the pressure signal.
Year
DOI
Venue
2019
10.1007/978-3-030-20055-8_48
14TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING MODELS IN INDUSTRIAL AND ENVIRONMENTAL APPLICATIONS (SOCO 2019)
Keywords
Field
DocType
Iterative Learning Control,Feed-forward,Feedback linearization,Hydraulic press,Force control
Mathematical optimization,Settling time,Hydraulic press,Control theory,Computer science,Feedback linearization,Overshoot (signal),Filter (signal processing),Iterative learning control,Filter design,Feed forward
Conference
Volume
ISSN
Citations 
950
2194-5357
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Ignacio Trojaola100.34
Iker Elorza201.01
Eloy Irigoyen33814.23
Aron Pujana-arrese402.03
Carlos Calleja500.34