Active disturbance rejection control for optoelectronic stabilized platform based on adaptive fuzzy sliding mode...

Area of Science:

• Control Systems Engineering
• Robotics and Automation
• Optoelectronics

Background:

• Optoelectronic platforms require precise target tracking capabilities.
• Traditional control methods often struggle with external disturbances and system uncertainties.
• LuGre friction models are crucial for accurate servo system representation.

Purpose of the Study:

• To develop an advanced control strategy for enhancing the target tracking performance of optoelectronic platforms.
• To combine Active Disturbance Rejection Control (ADRC) with Adaptive Fuzzy Sliding Mode Control (AFSMC) for superior control.
• To validate the proposed method's effectiveness in suppressing disturbances and improving tracking accuracy.

Main Methods:

• Establishing a servo system model incorporating LuGre friction.
• Implementing an AFSMC controller for estimating unknown system dynamics and reducing chattering.
• Designing an ADRC controller tuned via Back-Propagation neural networks.
• Utilizing Lyapunov's theorem and Barbara's lemma for stability analysis.

Main Results:

• The combined ADRC and AFSMC controller significantly improved the optoelectronic platform's target tracking capability.
• The Back-Propagation neural network-tuned ADRC demonstrated higher tracking accuracy compared to empirical tuning.
• Simulations confirmed the controller's effectiveness in suppressing external disturbances.
• The proposed method enhanced the controller's disturbance isolation properties.

Conclusions:

• The integration of ADRC and AFSMC offers a robust solution for enhancing optoelectronic platform control.
• The developed control strategy effectively addresses system uncertainties and external disturbances.
• This approach provides a foundation for more precise and reliable optoelectronic system operations.