Research Papers

Parameter-Dependent Lyapunov Functions in the Robust Control of Discrete Linear Repetitive Processes Using Previous Pass-Windowed Information

[+] Author and Article Information
Błażej Cichy

Institute of Control and Computation Engineering, University of Zielona Góra, ul. Podgórna 50, 65-246 Zielona Góra, Polande-mail: b.cichy@issi.uz.zgora.pl

Krzysztof Galkowski

Institute of Control and Computation Engineering, University of Zielona Góra, ul. Podgórna 50, 65-246 Zielona Góra, Polande-mail: k.galkowski@issi.uz.zgora.pl

Eric Rogers

Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UKe-mail: etar@ecs.soton.ac.uk

Manuscript received August 23, 2014; final manuscript received February 24, 2015; published online April 20, 2015. Assoc. Editor: Athanasios Pantelous.

ASME J. Risk Uncertainty Part B 1(2), 021008 (Apr 20, 2015) (12 pages) Paper No: RISK-14-1040; doi: 10.1115/1.4029971 History: Received August 23, 2014; Accepted March 04, 2015; Online April 20, 2015

The variables in multidimensional systems are functions of more than one indeterminate, and such systems cannot be controlled by standard systems theory. This paper considers a subclass of these systems that operate over a subset of the upper-right quadrant of the two-dimensional (2D) plane in the discrete domain with a specified recursive structure known as repetitive processes. Physical examples of such processes are known and also their representations can be used in the analysis of other classes of systems, such as iterative learning control. This paper gives new results on the use of the parameter-dependent Lyapunov functions for stability analysis and controls law design of a subclass of repetitive processes that arise in application areas. These results aim to eliminate or reduce the effects of model parameter uncertainty.

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Grahic Jump Location
Fig. 2

Illustrating the updating structure of the current pass profile vector in Eq. (2)

Grahic Jump Location
Fig. 1

Illustrating the updating structure of the current pass state vector in Eq. (2)

Grahic Jump Location
Fig. 4

Pass profile dynamics for uncontrolled process—Scenario 1 and vertex 1

Grahic Jump Location
Fig. 6

The controlled process inputs—Scenario 1—vertices 1, 2, and 3

Grahic Jump Location
Fig. 5

Pass profiles for controlled process—Scenario 1—vertices 1, 2, and 3

Grahic Jump Location
Fig. 3

The transfer function of the gantry robot dynamics at the x-axis

Grahic Jump Location
Fig. 7

Pass profiles of the controlled process—Scenario 2—vertices 1, 2, and 3

Grahic Jump Location
Fig. 8

The controlled process inputs—Scenario 2—vertices 1, 2, and 3

Grahic Jump Location
Fig. 9

Pass profiles and the input signal for model switching from vertex 1 to 2, then from 2 to 3, and back to 1—Scenario 3




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