Optimal input design for multibody systems by using an extended adjoint approach.

Area of Science:

• Multibody dynamics
• System identification
• Optimization methods

Background:

• Parameter identification is crucial for accurate multibody system modeling.
• Optimizing input signals can significantly improve parameter identifiability.
• Existing methods may lack systematic or automated approaches for complex systems.

Purpose of the Study:

• To develop an automated method for optimizing multibody system inputs.
• To enhance parameter identifiability through maximized information content in measurements.
• To provide a systematic approach applicable to various multibody systems.

Main Methods:

• Utilizing the Fisher information matrix to quantify information content.
• Employing the adjoint system of sensitivity differential equations for optimization.
• Combining these techniques for a systematic and automated optimization process.

Main Results:

• The proposed method systematically optimizes inputs for improved parameter identifiability.
• The approach leverages Fisher information and adjoint systems effectively.
• It allows for the incorporation of additional optimization goals, such as state constraints.

Conclusions:

• The presented method offers an automated and systematic way to optimize multibody system inputs for parameter identification.
• Maximizing Fisher information content is key to enhancing identifiability.
• The approach is versatile and can be extended to include other constraints.