Model-based predictive direct speed control applied to a Permanent Magnet Synchronous Motor with trapezoidal back-EMF

Abstract

This paper presents an investigative work about the application of State Space Model-Based Predictive Control in a three-phase Permanent Magnet Synchronous Motor with trapezoidal back-electromotive force, for speed control. Such motor is utilized in the white goods appliances industry and also in automotive and medical applications, among others, especially due to its high effiency and long life cycle. The predictive control methods present a differential in the driving performance for industrial applications, mainly by enabling the imposition of constraints. In this work, a linear prediction model identified with a Least Mean Squares algorithm is used with the State-Space predictive control approach. Such predictive method is interesting for industrial applications for being easy to tune and, in addition to the imposition of constraints, allowing ponderation between tracking performance and spent energy. The utilization of constraints is discussed for the predictive algorithm in this work. There are satisfactory simulated and experimental results that show advantages in using the mentioned control method to drive the Permanent Magnet Synchronous Motor.

Procedures to Design Multi-Model-Based Predictive Controller Applied to BLDC Drive

“…Therefore, this work proposes the use of a multi-model approach to deal with the BLDC motor drive nonlinear relation between control action and speed. This paper can be considered a continuation from the works proposed by Bartsch et al (2015) and Negri et al (2014) previously published by the authors. Here only a single linear model to describe the motor behavior, which could be improved with the multi-model treatment, is considered.…”

Predictive Control Approach For Permanent Magnet Synchronous Motor Drive

“…The identified model describes speed behavior (output) as a function of duty cycle (input) [13]. As mechanical dynamics are represented by a first order equation, a first order model was chosen for identification.…”

“…Such control techniques first appeared in petrochemical industry patents, in the decade of 1970. Since that epoch, many predictive control approaches were developed, as generalized predictive control (GPC) [14], dynamic matrix control (DMC) [14] and state space modelbased predictive control (SSMPC) [13]- [16] among others, being utilized in a variety of applications [14].…”

“…In industrial electronics, two research lines using SSMPC are highlighted: the continuous control set (CCS) [13], [17] and the finite control set (FCS) approaches [18], [19]. The first considers control action is a real number.…”

“…An identified model is used due to complexity of inverter-motor drive system model. The procedure used to perform this identification is detailed in [13]. However, there are some additional contributions in this paper.…”