Publication

Fixed-order SISO controller design for H∞ loop shaping method using frequency responses

2015
Conference Papers

Abstract

Robust control is used for a system with uncertainties and disturbances. Above all, the H∞ loop shaping method is known as the method achieving good control performance. However, this method takes much time to build the mathematical model of an actual plant and its uncertainty. In this paper, we propose the fixed-order controller design method which only uses frequency response data of the plant. Moreover, the controller is designed by the convex optimization. Thereby, the identification cost is expected to be less than the previous method without an increase in the calculation cost. The effectiveness of the proposed method is verified through the experiment for the belt-driven two-mass system, and comparison with the previous method in the last of this paper.

Official source

https://infoscience.epfl.ch/entities/publication/5908f17b-22ce-4ffd-853a-dc6fd64294ad

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.

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

2015
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/5908f17b-22ce-4ffd-853a-dc6fd64294ad

About this result

Related concepts (32)

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.

Euler method

In mathematics and computational science, the Euler method (also called the forward Euler method) is a first-order numerical procedure for solving ordinary differential equations (ODEs) with a given initial value. It is the most basic explicit method for numerical integration of ordinary differential equations and is the simplest Runge–Kutta method. The Euler method is named after Leonhard Euler, who first proposed it in his book Institutionum calculi integralis (published 1768–1870).

Model predictive control

Model predictive control (MPC) is an advanced method of process control that is used to control a process while satisfying a set of constraints. It has been in use in the process industries in chemical plants and oil refineries since the 1980s. In recent years it has also been used in power system balancing models and in power electronics. Model predictive controllers rely on dynamic models of the process, most often linear empirical models obtained by system identification.

Related publications (23)

Fixed-order SISO controller design for H∞ loop shaping method using frequency responses

Chat with Graph Search

CuClarabel: GPU Acceleration for a Conic Optimization Solver

Neural Process Model Predictive Control

Gradient-Normalized Smoothness for Optimization with Approximate Hessians