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Prediction-based Adaptive Robust Compensation for Motion Control of Time-delayed Uncertain Linear Motors | IEEE Conference Publication | IEEE Xplore

Prediction-based Adaptive Robust Compensation for Motion Control of Time-delayed Uncertain Linear Motors


Abstract:

The simultaneous presence of parameter variations, time-varying disturbances / uncertain nonlinearities, and the delayed signal in the control loop make the motion contro...Show More

Abstract:

The simultaneous presence of parameter variations, time-varying disturbances / uncertain nonlinearities, and the delayed signal in the control loop make the motion control of an iron core linear motor system difficult. Existing model-based control methodologies can handle only a subset of the above imprecisions and hence become insufficient to accurately track the desired motion. In this paper, a prediction-based adaptive robust control (PARC) design is developed for high performance motion control of linear motors subjected to above complexities. The proposed design, suited for a class of nth - order delayed uncertain dynamical system, comprises: i) prediction-based model compensation to attenuate the effect of input delay; ii) prediction-based projection type learning mechanisms to reduce the parameter uncertainties; iii) an improved robust prediction scheme that factors in both parameter and disturbance uncertainties; iv) and prediction-based nonlinear robust feedback to attenuate the effect of model approximation errors and disturbances. Performing all these simultaneously, the designed controller can successfully track a desired motion and achieve a guaranteed robust performance. The simulation results demonstrate improved performance of the proposed PARC scheme compared to conventional model reference adaptive robust control designs.
Date of Conference: 27-29 June 2018
Date Added to IEEE Xplore: 16 August 2018
ISBN Information:
Electronic ISSN: 2378-5861
Conference Location: Milwaukee, WI, USA

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