A GA-based parameters tuning method for an ADRC controller of ISP for aerial remote sensing applications

Area of Science:

• Control Systems Engineering
• Robotics
• Aerospace Engineering

Background:

• Aerial imaging systems require high stabilization accuracy despite environmental disturbances.
• Existing control methods may lack robustness against multi-source disturbances.
• Parameter tuning for advanced controllers like ADRC can be challenging.

Purpose of the Study:

• To develop and validate a genetic algorithm (GA)-based parameter tuning method for active disturbance rejection control (ADRC).
• To improve the stabilization accuracy and robustness of a three-axis inertially stabilized platform (ISP) for aerial imaging.
• To demonstrate the superiority of the GA-tuned ADRC over empirical tuning methods.

Main Methods:

• Proposed an active disturbance rejection control (ADRC) scheme for a three-axis inertially stabilized platform (ISP).
• Developed a genetic algorithm (GA) to optimize the parameters of the ADRC controller.
• Validated the proposed method through simulations and experimental tests.

Main Results:

• The GA-based ADRC demonstrated significant disturbance rejection capabilities.
• Stabilization accuracy was markedly improved using the proposed method.
• Compared to empirical tuning, the root-mean-square (RMS) stabilization error under a movable base was reduced by up to 50.09%.

Conclusions:

• The GA-based parameter tuning method effectively enhances ADRC performance for aerial ISPs.
• This approach offers superior disturbance rejection and improved stabilization accuracy.
• The method provides a robust solution for stabilizing imaging platforms in challenging environments.