Permanent Magnet Synchronous Machines and Drives: Flux Weakening Advanced Control Techniques

This paper discusses the implementation of evolutionary optimization algorithms to improve the performance of Permanent Magnet Synchronous Machines (PMSMs). It also covers the control design in the flux weakening region and proposes a modern control method of model predictive control to enhance the dynamic performance of interior PMSMs. The study investigates the dynamic performance of both surface-mounted and interior permanent magnet types of PMSMs through case studies and illustrative examples using MATLAB.

Format: Hardback
Length: 248 pages
Publication date: 31 July 2023
Publisher: Taylor & Francis Ltd

Permanent Magnet Synchronous Machines (PMSMs) are a type of electric motor that uses permanent magnets to generate torque. They are widely used in industrial applications such as robotics, automation, and renewable energy systems. Evolutionary optimization algorithms are powerful tools that can be used to improve the performance of PMSMs. In this paper, we will discuss the implementation of evolutionary optimization algorithms in PMSM control design.

The first section of the paper will provide a comprehensive overview of PMSM control design. We will discuss the basic principles of PMSM operation, as well as the challenges that arise in designing efficient control systems for these machines. We will also introduce the concept of flux weakening, which is a common technique used in PMSM control to improve their dynamic performance.

The second section of the paper will focus on the implementation of evolutionary optimization algorithms in PMSM control design. We will discuss the different types of evolutionary optimization algorithms that can be used, such as genetic algorithms, particle swarm optimization, and evolutionary programming. We will also discuss the advantages and disadvantages of each algorithm, as well as the specific requirements for their implementation in PMSM control.

The third section of the paper will present a modern control method of model predictive control (MPC) is proposed to improve the dynamic performance of interior PMSM. MPC is a control method that uses a mathematical model of the system to predict its future behavior and then adjusts the control inputs accordingly. We will discuss the principles of MPC, as well as the specific requirements for its implementation in PMSM control.

The fourth section of the paper will study the dynamic performance of two kinds of PMSMs, that of surface mounted and interior permanent magnet types. We will use MATLAB to simulate the behavior of these machines and compare the results of different control methods. We will also discuss the advantages and disadvantages of each control method and provide illustrative examples with MATLAB.

In conclusion, this paper provides a comprehensive overview of the implementation of evolutionary optimization algorithms in PMSM control design. We have discussed the basic principles of PMSM operation, the challenges of designing efficient control systems, and the advantages and disadvantages of different control methods. We have also presented a modern control method of MPC that is proposed to improve the dynamic performance of interior PMSM. Finally, we have studied the dynamic performance of two kinds of PMSMs and provided illustrative examples with MATLAB.

Dimension: 234 x 156 (mm)
ISBN-13: 9781032330655