Publication

Correlation-Based Tuning of Linear Multivariable Decoupling Controllers

Dominique Bonvin, Alireza Karimi, Ljubisa Miskovic
2005
Conference Papers

Abstract

The recently-proposed method for iterative correlation-based controller tuning is considered in this paper for the tuning of multivariable Linear Time-Invariant (LTI) controllers. The parameters of the controller are updated directly using the data acquired in closed-loop operation. This approach allows one to tune some elements of the controller transfer function matrix to satisfy the desired closed-loop performance, while the other elements are tuned to mutually decouple the closed-loop outputs. The controller parameters are calculated by minimization of the cross-correlation function involving instrumental variables. A very simple choice of the instruments is proposed. The approach is applied to a simulation model of a gas turbine engine, and excellent results are obtained in terms of decoupling and performance.

Official source

https://infoscience.epfl.ch/entities/publication/27506d7f-daa3-41b6-b58b-fbc5a9effe62

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.

Dominique Bonvin, Alireza Karimi, Ljubisa Miskovic
2005
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/27506d7f-daa3-41b6-b58b-fbc5a9effe62

About this result

Related concepts (14)

Control theory

Control theory is a field of control engineering and applied mathematics that deals with the control of dynamical systems in engineered processes and machines. The objective is to develop a model or algorithm governing the application of system inputs to drive the system to a desired state, while minimizing any delay, overshoot, or steady-state error and ensuring a level of control stability; often with the aim to achieve a degree of optimality. To do this, a controller with the requisite corrective behavior is required.

Closed-loop controller

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.

Open-loop controller

In control theory, an open-loop controller, also called a non-feedback controller, is a control loop part of a control system in which the control action is independent of the "process output", which is the process variable that is being controlled. It does not use feedback to determine if its output has achieved the desired goal of the input command or process setpoint. There are many open-loop controls, such as on/off switching of valves, machinery, lights, motors or heaters, where the control result is known to be approximately sufficient under normal conditions without the need for feedback.

Related publications (29)

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Alireza Karimi, Mert Eyuboglu, Nathan Russell Powell

This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

2024

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Colin Neil Jones, Wenjie Xu, Bratislav Svetozarevic

We study the problem of performance optimization of closed -loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed -loop performance by automatically tuning controller gains or re ...

Elsevier Sci Ltd2024

Koopman-based Data-driven Robust Control of Nonlinear Systems Using Integral Quadratic Constraints

Alireza Karimi, Mert Eyuboglu

This paper introduces a novel method for data-driven robust control of nonlinear systems based on the Koopman operator, utilizing Integral Quadratic Constraints (IQCs). The Koopman operator theory facilitates the linear representation of nonlinear system d ...

2024