System dynamics monitoring using PIC micro-controller-based PLSE

Area of Science:

• Non-linear time series analysis
• Embedded systems engineering
• Dynamical systems theory

Background:

• Permutation Largest Slope Entropy (PLSE) effectively distinguishes regular and non-regular dynamics.
• Existing PLSE algorithms provide local characterizations, missing micro-phenomena like intermittency.
• Real-time monitoring of complex system dynamics requires efficient algorithms suitable for embedded platforms.

Purpose of the Study:

• To implement an optimized Permutation Largest Slope Entropy (PLSE) algorithm on a PIC microcontroller for real-time monitoring of system dynamics.
• To adapt the PLSE algorithm for resource-constrained embedded systems using XC8 compiler and MPLAB X IDE.
• To validate the developed tool's effectiveness in capturing system behavior, including micro-phenomena.

Main Methods:

• Optimization of the PLSE algorithm for low-power PIC microcontrollers (PIC16F18446).
• Implementation using XC8 compiler and MPLAB X IDE on the Explorer 8 development board.
• Validation using an electrical circuit exhibiting periodic and chaotic dynamics (Duffing oscillator).

Main Results:

• Successful implementation of an optimized PLSE algorithm on a PIC microcontroller.
• Demonstrated capability for real-time monitoring of dynamical system behavior.
• Effective characterization of system dynamics, including micro-phenomena, validated against phase portraits and prior studies.

Conclusions:

• The developed PIC microcontroller-based PLSE tool enables efficient real-time monitoring of dynamical systems.
• The optimized algorithm successfully addresses limitations of traditional PLSE by capturing micro-phenomena.
• This work provides a practical solution for analyzing complex system dynamics in embedded applications.