Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Input‐output nominalization of linear systems with slow‐varying uncertainties

Input‐output nominalization of linear systems with slow‐varying uncertainties Purpose – The purpose of this paper is to present a method to compensate slow varying disturbances and plant parameter drifts using a simple yet robust algorithm called input‐output nominalization. Design/methodology/approach – In case of known uncertainties, an analytical expression of pre‐computed feed‐forward compensation command is derived. In presence of unknown disturbances and parameter drifts, the control algorithm uses a proportional‐integrative estimator‐based nominalizer. It creates a nominalizing signal, reflecting the deviation of the system from its nominal form using plant input and output. The signal is subtracted from the nominal controller output to cancel the uncertainty and disturbances effects. Findings – As a result, the uncertain plant and the nominalizer quickly converge to the nominal plant. Therefore, a simple controller tuned according to the nominal plant can be used despite the disturbances and parameter drifts and a nominal response is always obtained. Simulation and experimental results are given to describe the control algorithm performance and inherent limitations. Research limitations/implications – The proposed method is suitable for linear systems with low frequency uncertainties and disturbances only. Practical implications – The technique allows compensating errors in plant parameter identifications as well as parameter drifts during plant operations. Constant and slow varying disturbances are also rejected, allowing obtaining a prescribed nominal response. Originality/value – The proposed approach is different from the common robust control methods to the uncertain linear systems control. Instead of designing a robust controller, efforts are concentrated on the plant input‐output nominalization in a fashion similar to input‐output linearization. The method allows compensating slow varying disturbances and plant parameter drifts using a simple algorithm leading to a simple controller tuned according to the nominal plant parameters. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering Emerald Publishing

Input‐output nominalization of linear systems with slow‐varying uncertainties

Download PDF
18 pages

Loading next page...
 
/lp/emerald-publishing/input-output-nominalization-of-linear-systems-with-slow-varying-YkowK5ysXh
Publisher
Emerald Publishing
Copyright
Copyright © 2010 Emerald Group Publishing Limited. All rights reserved.
ISSN
0332-1649
DOI
10.1108/03321641011007975
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to present a method to compensate slow varying disturbances and plant parameter drifts using a simple yet robust algorithm called input‐output nominalization. Design/methodology/approach – In case of known uncertainties, an analytical expression of pre‐computed feed‐forward compensation command is derived. In presence of unknown disturbances and parameter drifts, the control algorithm uses a proportional‐integrative estimator‐based nominalizer. It creates a nominalizing signal, reflecting the deviation of the system from its nominal form using plant input and output. The signal is subtracted from the nominal controller output to cancel the uncertainty and disturbances effects. Findings – As a result, the uncertain plant and the nominalizer quickly converge to the nominal plant. Therefore, a simple controller tuned according to the nominal plant can be used despite the disturbances and parameter drifts and a nominal response is always obtained. Simulation and experimental results are given to describe the control algorithm performance and inherent limitations. Research limitations/implications – The proposed method is suitable for linear systems with low frequency uncertainties and disturbances only. Practical implications – The technique allows compensating errors in plant parameter identifications as well as parameter drifts during plant operations. Constant and slow varying disturbances are also rejected, allowing obtaining a prescribed nominal response. Originality/value – The proposed approach is different from the common robust control methods to the uncertain linear systems control. Instead of designing a robust controller, efforts are concentrated on the plant input‐output nominalization in a fashion similar to input‐output linearization. The method allows compensating slow varying disturbances and plant parameter drifts using a simple algorithm leading to a simple controller tuned according to the nominal plant parameters.

Journal

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering – Emerald Publishing

Published: Jan 1, 2010

Keywords: Algorithmic languages; Control systems; Systems theory; Electric motors

References

  • Simple adaptive control of uncertain systems
    Bar‐Kana, I.; Kaufman, H.
  • Feedback Control of Dynamic Systems
    Franklin, G.F.; Powell, J.F.; Emami‐Naeini, A.
  • Adaptive sliding mode control with PID tuning for uncertain systems
    Kuo, T.C.; Huang, Y.J.; Chen, C.Y.; Chang, C.H.
  • HIL‐based virtual disturbance and parameter variations of controlled electric drive
    Kuperman, A.
  • Virtual torque and inertia loading of controlled electric drive
    Kuperman, A.; Rabinovici, R.
  • Feedforward compensation of load and parameter variations of electric drive
    Kuperman, A.; Horen, Y.; Suissa, U.; Tapuchi, S.
  • Control of Electric Drives
    Leonhard, W.
  • Observers for multivariable systems
    Luenberger, D.G.
  • Generalized approach of the disturbance torque control
    Rabinovici, R.; Andreescu, G.D.
  • Applied Nonlinear Control
    Slotine, J.J.E.; Li, W.
  • MCK240 v1.0
    Technosoft DSP Motion Solutions
  • Stochastic optimal control and estimation methods adapted to the noise characteristics of the sensorimotor system
    Todorov, E.
  • Sliding mode prediction tracking control design for uncertain systems
    Xiao, L.; Su, H.; Chu, J.
  • Adaptive control for a class of linear systems with matching uncertainties and its application to ship steering
    Yuan, S.; Guo, C.