Observer based adaptive discrete hierarchical sliding mode control for industrial overhead crane with input...

Area of Science:

• Control Systems Engineering
• Robotics
• Mechatronics

Background:

• Industrial overhead cranes suffer from control performance degradation due to input saturation and inaccurate state estimation.
• Anti-sway control is crucial for efficient and safe operation of overhead cranes.
• Existing methods struggle to robustly handle state estimation inaccuracies and input saturation simultaneously.

Purpose of the Study:

• To develop an advanced control strategy for overhead crane anti-sway control that addresses input saturation and enhances state estimation accuracy.
• To improve the robustness and performance of overhead crane systems in industrial environments.
• To provide a stable and effective solution for suppressing payload sway.

Main Methods:

• A cascaded observer (ALKF) integrating a Luenberger observer and an adaptive Kalman filter with adaptive weighting was designed for enhanced state estimation.
• An adaptive discrete hierarchical sliding-mode controller (AHSMC) with an input saturation compensation mechanism was developed.
• The controller dynamically adjusts sliding-mode reaching law parameters to counteract input saturation effects.

Main Results:

• The proposed ALKF observer significantly improved the robustness and accuracy of state estimation.
• The AHSMC effectively suppressed the adverse effects of input saturation on control performance.
• Comparative experiments on a 0.5-ton industrial overhead crane demonstrated superior swing suppression capabilities.

Conclusions:

• The integrated ALKF observer and AHSMC provide a robust and effective solution for overhead crane anti-sway control.
• The proposed method enhances system stability and performance, particularly under input saturation conditions.
• Experimental validation confirms the practical applicability and superior performance of the developed control scheme.