Nonlinear robust adaptive precision motion control of motor servo systems with unknown actuator backlash compensation

Area of Science:

• Robotics and Control Systems
• Mechanical Engineering
• Mechatronics

Background:

• Motor servo systems often face challenges with modeling uncertainties and actuator backlash, hindering precise motion control.
• Existing control strategies may struggle with unknown parameters and disturbance bounds, limiting practical application.

Purpose of the Study:

• To develop a robust and adaptive control strategy for high-precision motion control in motor servo systems.
• To address challenges posed by modeling uncertainties and unknown actuator backlash in real-time.
• To enhance the engineering practicability of controllers by enabling automatic estimation of disturbance bounds.

Main Methods:

• A synthesized adaptive law combined with a continuous nonlinear robust term is employed.
• An adaptive technique is utilized to update unknown actuator backlash parameters in real-time.
• A backlash inverse function is incorporated to eliminate the backlash effect.
• The controller automatically estimates the disturbance upper bound through an adaptive law.

Main Results:

• The proposed controller demonstrates effective handling of parameter uncertainties and system disturbances.
• Real-time adaptation of actuator backlash parameters and elimination of backlash effects were achieved.
• The controller successfully estimated unknown disturbance bounds, improving practical applicability.
• Theoretical analysis confirmed perfect asymptotic stability, even with unmodeled dynamics.

Conclusions:

• The presented adaptive control method offers superior performance and robustness for motor servo systems.
• The approach effectively compensates for modeling uncertainties and unknown actuator backlash.
• The controller's ability to self-estimate disturbance bounds enhances its engineering value and applicability.