Publication

Correlation-Based Tuning of a Restricted-Complexity Controller for an Active Suspension System

Dominique Bonvin, Ljubisa Miskovic
2003
Conference Papers

Abstract

A correlation-based controller tuning method is proposed for the \Design and optimization of restricted-complexity controllers" benchmark problem. The approach originally proposed for model following is applied to solve the disturbance rejection problem. The idea is to tune the controller parameters such that the closed-loop output be uncorrelated with the measured disturbance. Since perfect decorrelation between the closed-loop output and the disturbance is not attainable with a restricted-complexity controller, the cross-correlation of these two signals is minimized. This is done iteratively using stochastic approximation. A frequency analysis of the tuning criterion allows dealing with control speci cations expressed in terms of constraints on the sensitivity functions. Application to the active suspension system of the Automatic Laboratory of Grenoble (LAG) provides a 2nd-order controller that meets the control speci cations to a large extent.

Official source

https://infoscience.epfl.ch/entities/publication/eddbe2b5-82de-49cc-b1d4-5c085242abac

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Dominique Bonvin, Ljubisa Miskovic
2003
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/eddbe2b5-82de-49cc-b1d4-5c085242abac

About this result

Related concepts (32)

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A closed-loop controller or feedback controller is a control loop which incorporates feedback, in contrast to an open-loop controller or non-feedback controller. A closed-loop controller uses feedback to control states or outputs of a dynamical system. Its name comes from the information path in the system: process inputs (e.g., voltage applied to an electric motor) have an effect on the process outputs (e.g., speed or torque of the motor), which is measured with sensors and processed by the controller; the result (the control signal) is "fed back" as input to the process, closing the loop.

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