MIMO ultra-local model-based adaptive enhanced model-free control using extremum-seeking for coupled mechatronic...

Area of Science:

• Mechatronics and Control Systems Engineering
• Robotics and Automation

Background:

• Mechatronic systems (e.g., robotic arms) are vital but difficult to model due to coupling and uncertainty.
• Traditional model-based control is often impractical for these complex systems.

Purpose of the Study:

• To develop an adaptive, enhanced model-free control for multi-input multi-output (MIMO) mechatronic systems.
• To achieve robust trajectory tracking in the presence of system uncertainties and disturbances.

Main Methods:

• A novel MIMO ultra-local model with a non-diagonal gain matrix (α) was developed to approximate system dynamics.
• An extremum-seeking (ES) technique was employed to optimize the gain matrix α.
• Time-delay estimation (TDE) and Proportional-Derivative (PD) control with accuracy compensation ensured closed-loop stability.

Main Results:

• The proposed model-free control framework effectively handles MIMO mechatronic systems.
• Extremum-seeking optimization of the non-diagonal gain matrix significantly enhanced control performance.
• Simulations on robotic manipulators demonstrated the method's effectiveness and superiority.

Conclusions:

• The developed MIMO ultra-local model and ES-based adaptive control offer a robust solution for trajectory tracking in complex mechatronic systems.
• The approach provides a stable and high-performing control strategy validated through rigorous simulations.