Predictive Control of Power Converters and Electrical Drives

8.1 Introduction

Over recent decades, control of electrical drives has been widely studied. Linear methods like PI controllers using PWM and non linear methods such as hysteresis control have been fully documented in the literature and dominate high-performance industrial applications [1, 2]. The most widely used linear strategy in high performance electrical drives is field-oriented control (FOC) [3–6], in which a decoupled torque and flux control is performed by considering an appropriate coordinate frame. A non linear hysteresis-based strategy such as direct torque control (DTC) [7] appears to be a solution for high performance applications.

At the end of the 1970s, model predictive control (MPC) was developed in the petrochemical industry [8–10]. The term MPC does not imply a specific control strategy, but covers an ample variety of control techniques that make explicit use of a mathematical model of the process and minimization of an objective function [11] to obtain the optimal control signals. The slow dynamics of chemical processes allow long sample periods, providing enough time to solve the online optimization problem.

Due to the rapid development of microprocessors, the idea of having only a centralized controller, without a cascade control structure, was considered to improve the dynamic behavior. Furthermore, the increasing number of drive applications, in which fast dynamic response, low parameter sensitivity, and algorithm simplicity are required, has motivated the ...