Model-Based Predictive Control for Non-Integer Order Systems via LMI Optimization

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Main Authors: Dr. Ramesh Nair, Dr. Astrid Jensen
Format: Recurso digital
Published: Zenodo 2020
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author Dr. Ramesh Nair
Dr. Astrid Jensen
author_facet Dr. Ramesh Nair
Dr. Astrid Jensen
contents <p>—In this paper, the problem of robust model predictive control (MPC) for discrete-time linear systems in linear fractional transformation form with structured uncertainty and norm-bounded disturbance is investigated. The problem of minimization of the cost function for MPC design is converted to minimization of the worst case of the cost function. Then, this problem is reduced to minimization of an upper bound of the cost function subject to a terminal inequality satisfying the l2-norm of the closed loop system. The characteristic of the linear fractional transformation system is taken into account, and by using some mathematical tools, the robust predictive controller design problem is turned into a linear matrix inequality minimization problem. Afterwards, a formulation which includes an integrator to improve the performance of the proposed robust model predictive controller in steady state condition is studied. The validity of the approaches is illustrated through a robust control benchmark problem</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_19319123
institution Zenodo
language
publishDate 2020
publisher Zenodo
record_format zenodo
spellingShingle Model-Based Predictive Control for Non-Integer Order Systems via LMI Optimization
Dr. Ramesh Nair
Dr. Astrid Jensen
Linear fractional transformation
linear matrix inequality
robust model predictive control
state feedback control.
<p>—In this paper, the problem of robust model predictive control (MPC) for discrete-time linear systems in linear fractional transformation form with structured uncertainty and norm-bounded disturbance is investigated. The problem of minimization of the cost function for MPC design is converted to minimization of the worst case of the cost function. Then, this problem is reduced to minimization of an upper bound of the cost function subject to a terminal inequality satisfying the l2-norm of the closed loop system. The characteristic of the linear fractional transformation system is taken into account, and by using some mathematical tools, the robust predictive controller design problem is turned into a linear matrix inequality minimization problem. Afterwards, a formulation which includes an integrator to improve the performance of the proposed robust model predictive controller in steady state condition is studied. The validity of the approaches is illustrated through a robust control benchmark problem</p>
title Model-Based Predictive Control for Non-Integer Order Systems via LMI Optimization
topic Linear fractional transformation
linear matrix inequality
robust model predictive control
state feedback control.
url https://doi.org/10.5281/zenodo.19319123