Robust Predictive Control of Electro-mechanical Servo System

Panchal, Bhavnesh; Kolhe, Jaywant P.; Parlikar, V. V.; Talole, S. E.

doi:10.3182/20140313-3-in-3024.00022

Cited by 2 publications

(1 citation statement)

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“…To address these issues, an Extended State Observer (ESO) is designed to estimate the output derivatives as well as the effect of uncertainties and dis turbances. The estimates are then employed in the predictive control law for the robustification of the same leading to robust predictive control design [15], [16]. Numerical simulations results as applied to trajectory tracking control problem of Quanser's flexible joint system are presented to demonstrate efficacy of the design.…”

Section: Introductionmentioning

confidence: 98%

Experimental validation of robust predictive controller

Pancha

Kolhe²,

Talole

2015

2015 International Conference on Industrial Instrumentation and Control (ICIC)

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In this work, design and experimental validation of an Extended State Observer (ESO) based robust predictive controller for flexible joint system is presented. An output tracking predictive controller is designed for control of flexible joint system. However, the controller requires accurate mathe matical model as well as output derivatives to be available for its implementation. In this work, the issues are addressed by estimating the plant uncertainty and output derivatives by using an ESO. The ESO estimates the output derivatives and modeling uncertainty simultaneously and the estimates are used in the predictive controller designed for nominal system. Closed loop stability of the overall system is established. Numerical simulation results of the proposed approach as applied to the flexible joint system are presented and it is shown that the ESO based predictive controller offers improved performance. Finally, the efficacy of the proposed design is validated through experiments carried on Quanser's flexible joint module. The results show that the ESO based design offers superior performance in presence of significant plant uncertainty.

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Section: Introductionmentioning

confidence: 98%