The proposed additive continuous-time system identification method has a wide range of potential applications across various fields. Beyond the identification of flexible beams and mechanical systems, this method can be effectively utilized in:
Robotics: In robotic systems, where multiple dynamic modes (e.g., rigid and flexible) interact, the additive model can help in accurately identifying the dynamics of robotic arms or mobile robots, leading to improved control strategies.
Aerospace Engineering: The identification of aircraft dynamics, particularly in the presence of flexible components such as wings or control surfaces, can benefit from the additive approach, allowing for better modeling of the system's response to control inputs.
Automotive Systems: In vehicle dynamics, the method can be applied to model the interactions between different subsystems, such as suspension and chassis dynamics, which are crucial for enhancing ride comfort and handling.
Biomedical Engineering: The identification of biological systems, such as the dynamics of prosthetic limbs or the response of biological tissues to stimuli, can leverage the additive model to capture the complex interactions between different biological processes.
Environmental Systems: In ecological modeling, the method can be used to identify the dynamics of ecosystems where multiple species or environmental factors interact, providing insights into population dynamics and resource management.
Energy Systems: The identification of renewable energy systems, such as wind turbines or solar panels, can benefit from the additive approach to model the interactions between different energy generation modes and their responses to varying environmental conditions.
These applications highlight the versatility of the proposed method in addressing complex system dynamics across diverse engineering and scientific domains.