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Predictive iterative learning control with experimental validation

Predictive iterative learning control with experimental validation
Predictive iterative learning control with experimental validation
This paper develops an iterative learning control law that exploits recent results in the area of predictive repetitive control where a priori information about the characteristics of the reference signal is embedded in the control law using the internal model principle. The control law is based on receding horizon control and Laguerre functions can be used to parameterize the future control trajectory if required. Error convergence of the resulting controlled system is analyzed. To evaluate the performance of the design, including comparative aspects, simulation results from a chemical process control problem and supporting experimental results from application to a robot with two inputs and two outputs are given.
0967-0661
24-34
Wang, Liuping
d3cd762e-6708-4126-89e5-97926bf347c9
Freeman, Christopher T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Rogers, Eric
611b1de0-c505-472e-a03f-c5294c63bb72
Wang, Liuping
d3cd762e-6708-4126-89e5-97926bf347c9
Freeman, Christopher T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Rogers, Eric
611b1de0-c505-472e-a03f-c5294c63bb72

Wang, Liuping, Freeman, Christopher T. and Rogers, Eric (2016) Predictive iterative learning control with experimental validation. Control Engineering Practice, 53, 24-34. (doi:10.1016/j.conengprac.2016.04.001).

Record type: Article

Abstract

This paper develops an iterative learning control law that exploits recent results in the area of predictive repetitive control where a priori information about the characteristics of the reference signal is embedded in the control law using the internal model principle. The control law is based on receding horizon control and Laguerre functions can be used to parameterize the future control trajectory if required. Error convergence of the resulting controlled system is analyzed. To evaluate the performance of the design, including comparative aspects, simulation results from a chemical process control problem and supporting experimental results from application to a robot with two inputs and two outputs are given.

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More information

Accepted/In Press date: 4 April 2016
e-pub ahead of print date: 11 May 2016
Published date: August 2016
Organisations: Vision, Learning and Control

Identifiers

Local EPrints ID: 390798
URI: http://eprints.soton.ac.uk/id/eprint/390798
ISSN: 0967-0661
PURE UUID: 0bb088be-fb16-49ee-b6bf-90058240a29c
ORCID for Eric Rogers: ORCID iD orcid.org/0000-0003-0179-9398

Catalogue record

Date deposited: 04 Apr 2016 18:32
Last modified: 07 Oct 2020 06:02

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