Sensorless load torque estimation and passivity based control of buck converter fed DC motor

Area of Science:

• Electrical Engineering
• Control Systems
• Robotics

Background:

• DC motors are crucial actuators in various applications.
• Sensorless control eliminates the need for speed sensors, reducing cost and complexity.
• Controlling DC motor speed under uncertain load conditions is challenging.

Purpose of the Study:

• To propose a novel passivity-based control strategy for sensorless DC motor operation.
• To stabilize the speed of a Buck converter-fed DC motor under diverse load conditions.
• To develop and compare a sensorless online algebraic approach for load torque estimation.

Main Methods:

• Implementation of exact tracking error dynamics passive output feedback control.
• Utilizing a Buck converter to feed the DC motor.
• Employing a sensorless online algebraic approach for load torque estimation.
• Comparison with a sensorless reduced-order observer approach.
• Performing sensitivity analysis to optimize control variables.

Main Results:

• The proposed passivity-based control effectively stabilizes DC motor speed under constant, fan, propeller, and unknown load torques.
• The sensorless online algebraic approach demonstrates superior performance in load torque estimation compared to the reduced-order observer.
• Sensitivity analysis identified optimal control variables for enhanced performance.
• Simulation and experimental results validate the proposed approach's superiority.

Conclusions:

• The developed passivity-based control offers a robust and effective solution for sensorless DC motor speed stabilization.
• The online algebraic load torque estimation method provides accurate and reliable performance under various load conditions.
• This research contributes a superior sensorless control strategy for DC motor applications, validated by comprehensive testing.