Clean system inversion learning control law

Authors:
Yongqiang Ye;Danwei Wang
Affiliations:
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
Venue:
Automatica (Journal of IFAC)
Year:
2005

Citing 0
Cited 3

Brief paper: Iterative Learning Control for uncertain systems: Robust monotonic convergence analysis

Automatica (Journal of IFAC)
Brief paper: A decoupled inversion-based iterative control approach to multi-axis precision positioning: 3D nanopositioning example

Automatica (Journal of IFAC)
Fractional zero-phase filtering based on the Riemann-Liouville integral

Signal Processing

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Abstract

In this paper, an iterative learning control approach, clean system inversion, is proposed for multi-input multi-output (MIMO) time-invariant systems, as a remedy to the system inversion law. The analysis and design are carried out in the frequency domain. This model based scheme relies on non-causal filtering and need no high order derivatives of error signals and no numerical differentiation. Experimental results on an industrial robot system show that the scheme is effective.