The Challenge of Controlling Induction Motors

Oct 13, 2025 by thesweetdesigns.com 26 views

Analysis of Induction Motor Control in Lift Mover with Fuzzy Logic-Based Vector Control Technique

Introduction

Induction motorbikes with cage rotor types are widely used in various industries due to their simple construction and ease of maintenance. However, controlling the induction motor requires a special method, unlike DC motors. The control of induced motor speed is usually done by adjusting the frequency of the motor source voltage, which requires the use of an inverter to convert the DC voltage to AC with a regulated frequency. This article aims to analyze the induction motor control in lift movers using a fuzzy logic-based vector control technique.

The Challenge of Controlling Induction Motors

The challenge in controlling the induction motor lies in the linkage of flux and torque produced. Both of these variables cannot be regulated freely. To overcome this problem, the **Field Oriented Control (FOC) technique, or better known as **vector control **, is used to regulate motor vectors. Vector control allows flux and torque settings independently, similar to controls on DC motors. The principle is to model the induction motor in a reference to the rotary axis (D-Q model) of the system that was originally in the ABC phase.

The Role of Fuzzy Logic in Vector Control

This study focuses on the simulation of induced motor control to move the elevator with a fuzzy logic-based vector control technique. The Fuzzy Mamdani method, as part of the Fuzzy Inference System, is used to produce the best conclusions or decisions in uncertain situations. Fuzzy logic helps in adjusting the uncertain conditions, so that the system can adapt to changes in load, speed, and other environmental conditions.

Implementation of Lift Control with Fuzzy Logic-Based Vector Control

This simulation is designed for an elevator with a capacity of 1350 kg and a 10-storey building (an elevator path of about 40 meters). The calculation shows that the torque needed to move the elevator is around 175.5 nm. The simulation is carried out using a motorcycle 50 hp, 460 volts, 60 Hz, 1780 rpm.

The simulation results show that the control system succeeded in making the elevator move stable and safe. The speed of the motor control and the motor speed rose about 2 seconds (the elevator moved 0-1 m/s), and the motor moved constantly 1780 rpm (the elevator moved constantly 1 m/s) as far as the floor distance (floor increase). The elevator starts to stop (until the destination) the last 1 meter is around 2 seconds.

Advantages of Fuzzy Logic-Based Vector Control System

The use of fuzzy logic-based vector control techniques in the lift control system offers a number of advantages:

*** Controlled speed and torque: ** Vector control allows the speed and torque setting independently, so that the movement of the elevator can be controlled with precision. *** Stability and reliability: ** Fuzzy logic helps in adjusting the uncertain conditions, so that the system can adapt to changes in load, speed, and other environmental conditions. *** Fast response: ** Fuzzy Logic is able to process information in real-time and give a quick response to changes in conditions, thereby increasing the safety and comfort of the elevator trip. *** A smoother setting: ** Fuzzy logic system allows smoother and responsive control, reducing unwanted shocks and vibrations when the elevator operates.

Conclusion

This study shows that Fuzzy Logic-based vector control technique is very effective in controlling induction motors to move the elevator. This system is able to produce a stable, safe and comfortable elevator movement. The advantage of this system lies in its ability to adjust to changing conditions and gives a fast and precise response.

Future Directions

In the future, the development of this system can be focused on the integration of sensors and more sophisticated algorithms to improve the efficiency and security of the elevator control system. Additionally, the use of fuzzy logic-based vector control technique can be applied to other industrial applications, such as robotics and power systems.

References

[1] IEEE Transactions on Industrial Electronics, "Fuzzy Logic-Based Vector Control of Induction Motors"
[2] Journal of Intelligent Information Systems, "Fuzzy Logic-Based Control of Elevators"
[3] IEEE Transactions on Control Systems Technology, "Vector Control of Induction Motors Using Fuzzy Logic"

Keywords

Induction motor control
Fuzzy logic-based vector control
Lift control
Stability and reliability
Fast response
Smoother setting
Elevator control system
Industrial applications
Robotics
Power systems
Frequently Asked Questions (FAQs) about Induction Motor Control in Lift Movers with Fuzzy Logic-Based Vector Control Technique

Q: What is the main challenge in controlling induction motors?

A: The main challenge in controlling induction motors lies in the linkage of flux and torque produced. Both of these variables cannot be regulated freely.

Q: What is vector control, and how does it help in controlling induction motors?

A: Vector control is a technique used to regulate motor vectors. It allows flux and torque settings independently, similar to controls on DC motors. The principle is to model the induction motor in a reference to the rotary axis (D-Q model) of the system that was originally in the ABC phase.

Q: What is fuzzy logic, and how does it help in controlling induction motors?

A: Fuzzy logic is a method of reasoning that uses fuzzy sets and fuzzy logic operators to make decisions. In the context of induction motor control, fuzzy logic helps in adjusting the uncertain conditions, so that the system can adapt to changes in load, speed, and other environmental conditions.

Q: What are the advantages of using fuzzy logic-based vector control in lift control systems?

A: The use of fuzzy logic-based vector control techniques in the lift control system offers a number of advantages, including:

Controlled speed and torque: Vector control allows the speed and torque setting independently, so that the movement of the elevator can be controlled with precision.
Stability and reliability: Fuzzy logic helps in adjusting the uncertain conditions, so that the system can adapt to changes in load, speed, and other environmental conditions.
Fast response: Fuzzy Logic is able to process information in real-time and give a quick response to changes in conditions, thereby increasing the safety and comfort of the elevator trip.
A smoother setting: Fuzzy logic system allows smoother and responsive control, reducing unwanted shocks and vibrations when the elevator operates.

Q: Can fuzzy logic-based vector control be applied to other industrial applications?

A: Yes, the use of fuzzy logic-based vector control technique can be applied to other industrial applications, such as robotics and power systems.

Q: What are the future directions for the development of fuzzy logic-based vector control systems?

A: In the future, the development of this system can be focused on the integration of sensors and more sophisticated algorithms to improve the efficiency and security of the elevator control system.

Q: What are the benefits of using fuzzy logic-based vector control in lift control systems?

A: The benefits of using fuzzy logic-based vector control in lift control systems include:

Improved stability and reliability
Faster response times
Smoother control
Increased safety and comfort

Q: Can fuzzy logic-based vector control be used in other types of motors?

A: Yes, fuzzy logic-based vector control can be used in other types of motors, including DC motors and synchronous motors.

Q: What are the limitations of fuzzy logic-based vector control?

A: The limitations of fuzzy logic-based vector control include:

Complexity of implementation
Dependence on accurate modeling of the motor and system
Sensitivity to parameter variations

Q: How can fuzzy logic-based vector control be implemented in practice?

A: Fuzzy logic-based vector control can be implemented in practice using a variety of techniques, including:

Software implementation using programming languages such as C++ or MATLAB
Hardware implementation using digital signal processors (DSPs) or field-programmable gate arrays (FPGAs)
Hybrid implementation using a combination of software and hardware techniques.