Model-Free Precompensator Tuning Based on the Correlation Approach

Mark Edward John Butcher, Alireza Karimi, Roland Longchamp
2008
Journal paper

Abstract

High performance output tracking can be achieved by precompensator or feedforward controllers based on the inverse of either the closed-loop system or the plant model, respectively. However, it has been shown that these inverse controllers can adversely affect the tracking performance in the presence of model uncertainty. In this paper, a model-free approach based on only one set of acquired data from a simple closed-loop experiment is used to tune the controller parameters. The approach is based on the decorrelation of the tracking error and the desired output and is asymptotically not sensitive to noise and disturbances. From a system identification point of view the stable inverse of the closed-loop system is identified by an extended instrumental variable algorithm in the framework of errors-in-variables identification methods. By a frequency-domain analysis of the criterion, it is shown that the weighted two-norm of the difference between the controller and the inverse of the closed-loop transfer function can be minimized. The method is successfully applied to a high precision position control system.

Official source

https://infoscience.epfl.ch/record/111862?ln=en

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related concepts

Related publications

Related publications (11)

, ,

High performance output tracking can be achieved by precompensator or feedforward controllers based on the inverse of the closed-loop system or the plant model. However, it has been shown that these inverse controllers can affect adversely the tracking performance in the presence of model uncertainty. In this paper, a model-free approach based on only one set of acquired data from a simple closed-loop experiment is used to tune the controller parameters. The approach is based on the decorrelation of the tracking error and the desired output and is not asymptotically sensitive to noise and disturbances. By a frequency-domain analysis of the criterion, it is shown that the weighted two-norm of the difference between the controller and the inverse of the plant model (or the closed-loop transfer function) can be minimized. The method is successfully applied to a high precision position control system.

2005

H infinity Gain-scheduled Controller Design for Rejection of Time-varying Narrow-band Disturbances Applied to a Benchmark Problem

Zlatko Emedi, Alireza Karimi

A new method for H-infinity gain-scheduled controller design by convex optimization is proposed that uses only frequency-domain data. The method is based on loop shaping in the Nyquist diagram with constraints on the weighted infinity-norm of closed-loop transfer functions. This method is applied to a benchmark for adaptive rejection of multiple narrow-band disturbances. First, it is shown that a robust controller can be designed for the rejection of a sinusoidal disturbance with known frequency. The disturbance model is fixed in the controller, based on the internal model principle, and the other controller parameters are computed by convex optimization to meet the constraints on the infinity-norm of sensitivity functions. It is shown next that a gain scheduled-controller can be computed for a finite set of disturbance frequencies by convex optimization. An adaptation algorithm is used to estimate the disturbance frequency which adjusts the parameters of the internal model in the controller. The simulation and experimental results show the good performance of the proposed control system.

Lavoisier2013

H-Infinity Gain-Scheduled Controller Design for Rejection of Time-Varying Disturbances with Application to an Active Suspension System

Zlatko Emedi, Alireza Karimi

A new method for H-infinity gain-scheduled controller design by convex optimization is proposed that uses only frequency-domain data. The method is based on loop shaping in the Nyquist diagram with constraints on the weighted infinity norm of closed-loop transfer functions. This method is applied to an active suspension system for adaptive rejection of multiple narrow-band disturbances. First, it is shown that a robust controller can be designed for the rejection of a sinusoidal disturbance with known frequency. The disturbance model is fixed in the controller, based on the internal model principle, and the other controller parameters are computed by convex optimization to meet the constraints on the infinity-norm of sensitivity functions. It is shown next that a gain scheduled controller can be computed for a finite set of disturbance frequencies by convex optimization. An adaptation algorithm is used to estimate the disturbance frequency which adjusts the parameters of the internal model in the controller. The simulation and experimental results show the good performance of the proposed control system.

2013