Unconstrained and Constrained Predictive Control for the Multivariable Process with Non-minimum Phase

Abstract

A B S T R A C TNon-minimum phase Multi-input Multi-Ouput (MIMO) systems are known to be difficult to control. Model Predictive Control (MPC) algorithms are powerful control design methods widely applied to industrial processes. The handling of various input constraints in the MPC problem of ARIMAX nonminimum phase MIMO systems is considered. This approach is applied for control of industrial quadruple tanks. However, there is no easy way to solve the problem of constraints. The methods based on the quadratic programming (QP) technique are used to solve the constrained optimization problem. A comparative study of unconstrained and constrained control system behavior is given. Some illustrative simulation results for a considered system are presented and discussed. Encouraging results are obtained that motivate for further investigations.

Constrained model predictive control for the quadruple-tank process

“…In the previous paper given in [15], a comparative study of unconstrained and constrained control system behavior is developed and the method based on the Quadratic Programming (QP) technique are used to solve the constrained optimization problem. The aim of this work is to design and study the predictive controller for controlling the level of tanks in a quadruple tank process depending on type of constrained problems.…”

Influencia de las Restricciones en la Síntesis de un Controlador Predictivo

“…1 factores. Se pueden colocar restricciones tales como: rango de acción limitado, incremento de acción limitado, salida restringida, entre otros (Zidane, 2019).…”

“…La aplicación de la programación cuadrática para resolver el problema de optimización del MPC bajo restricciones cuando se utilizan índices de coste de tipo cuadrático es ampliamente utilizada (Zidane, 2019), y permite resolver varias formulaciones de problemas de control predictivo con restricciones.…”