Hybrid Optimization Process Applied to Tuning of Dynamic Matrix Control: Study Case with DC Motor

Cleber Asmar Ganzaroli,Luiz Alberto Do Couto,Rafael Nunes Hidalgo Monteiro Dias,Douglas Freire De Carvalho,Wesley Pacheco Calixto

doi:10.22149/teee.v2i2.98

Abstract

This paper presents study about Dynamic Matrix Control (DMC) controller applied to speed control of DC motor. DMC controller parameters (prediction horizon, control horizon and damping rate of reference) are obtained through optimization methods employing heuristic, deterministic and hybrid strategies. The use of advanced control technique combined with using of optimization methods aims to achieve highly efficient control, reducing the transient state period and variations in steady state. These methods were applied on a simulation model in order to verify which one provides better control results. Index Terms—Predictive Control, Deterministic Optimization, Heuristic Optimization, Hybrid Optimization, DC motor.

Highlights

DIRECT current (DC) motors are used in various situations ranging from residential applications to purposes of industrial scale
The proposed optimized controllers were simulated for the same DC motor speed control in order to compare which optimization method obtain the most efficient controller, searching for reduction of the transient period and variations in continuous operation
To analyze the efficiency of the control developed was used as main criterion the Integral of Absolute Error of speed, presenting the existing error between the speed developed by DC motor and reference speed

Summary

Introduction

DIRECT current (DC) motors are used in various situations ranging from residential applications to purposes of industrial scale. Utilization of DC motors implies, often, in its speed control. Aiming to do a high quality speed control of DC machines several number of techniques has been developed [1]. Control systems techniques are employed seeking to promote proper implementation of processes, generally, controlling manipulated system variables to obtain desired values for output system variables [2]. Control systems techniques are often applied to control speed of DC machines aiming to promote proper implementation of processes. Model based Predictive Control (MPC) refers to determinate class of control algorithms that seek to obtain optimal control signal minimizing certain objective function, explicitly using process model. MPC have been developed seeking to solve problems of process control in industrial environment, in oil industry, being initially proposed by Richalet at 1978, proposing the Model Predictive Heuristic Control (MPHC) and by Cutler & Remaker at 1980, proposing the Dynamic Matrix Control

Methods

Results

Conclusion