December 7, 2021
Valiollah Ghaffari

Valiollah Ghaffari

Degree: Associate professor
Address: Persian Gulf University
Education: Ph.D in Electrical Engineering
Phone: 07733442269
Faculty: Faculty of Intelligent Systems and Data Science

Research

Title A Model Predictive Approach to Dynamic Control Law Design in Discrete-Time Uncertain Systems
Type Article
Keywords
Journal CIRCUITS SYSTEMS AND SIGNAL PROCESSING
DOI
Researchers Valiollah Ghaffari (First researcher)

Abstract

A model predictive control ( MPC ) scheme is mainly developed in discrete-time uncertain systems. The control law contains a dynamic property in the proposed MPC. Hence, the MPC with a dynamic control policy is simply known as model predictive dynamic control ( MPDC ). To this end, a suitable matrix transformation is suggested to convert the MPDC problem into another optimization issue. Then, a systematic procedure based on linear matrix inequality ( LMI ) is addressed to the MDPC design. Hence, the MPDC synthesis is translated into an LMI minimization problem, which handles both constraints on the control inputs and plant outputs. The optimization problem can be numerically solved at each sample-time through the well known LMI solver. Then, the parameters of the dynamic controller would be automatically updated at each sample-time. The method is applied in a discrete-time example to verify the effectiveness of the presented approach versus similar results.