Adaptive control in dynamical systems using reservoir computing

Summary

The paper proposes a data-driven technique for adaptive control in dynamical systems using reservoir computing. The method uses a reservoir computer to predict system parameters from time series data, and then uses a control signal to drive the system to a target state.

Highlights

• The proposed method uses reservoir computing to predict system parameters from time series data.
• The method is model-free and does not require prior knowledge of the system dynamics.
• The control signal is based on the predicted parameter values and is used to drive the system to a target state.
• The method is demonstrated on numerical simulations of the Rössler system and the logistic map.
• The method is also demonstrated on an experimental implementation of the Rössler system using an electronic circuit.
• The results show that the method can effectively control the system to a target state.
• The method has potential applications in a wide range of fields, including physics, engineering, and biology.

Key Insights

• The proposed method uses a reservoir computer to predict system parameters from time series data, allowing for real-time control of the system.
• The method is model-free and does not require prior knowledge of the system dynamics, making it applicable to a wide range of systems.
• The control signal is based on the predicted parameter values, allowing for precise control of the system.
• The method is demonstrated on both numerical simulations and experimental implementations, showing its effectiveness in different contexts.
• The method has potential applications in fields such as physics, engineering, and biology, where control of complex systems is crucial.
• The use of reservoir computing allows for efficient and accurate prediction of system parameters, enabling real-time control.
• The proposed method provides a new approach to adaptive control, allowing for precise control of complex systems without requiring prior knowledge of the system dynamics.

Mindmap

Citation

Mandal, S., Chauhan, S., Verma, U. K., Shrimali, M. D., & Aihara, K. (2024). Adaptive control in dynamical systems using reservoir computing (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2412.17501