Optimal Digital Implementation of Fractional-Order Models in a Microcontroller.

Area of Science:

• Electrical Engineering
• Control Systems
• Mechatronics

Background:

• Fractional-order (FO) models offer enhanced accuracy for dynamic systems like brushless DC (BLDC) micromotors.
• Implementing FO operators in real-time applications faces computational and memory constraints.

Purpose of the Study:

• To analyze and implement both integer-order (IO) and FO models of BLDC micromotors on a microcontroller (MCU).
• To evaluate and compare different approximation methods for the fractional-order operator.

Main Methods:

• Analysis of classic IO and FO BLDC micromotor models.
• Discretization and implementation of models on an ARM Cortex-M7 microcontroller.
• Application of Oustaloup Recursive filter and Grünwald-Letnikov definition with Short Memory Principle for FO approximation.
• Verification through experimental results and performance index calculations (IAE, ISE).

Main Results:

• Demonstrated efficient implementation of FO models on an MCU.
• Quantified the accuracy of different FO approximation methods using IAE and ISE.
• Validated model performance against experimental data.

Conclusions:

• Approximation methods enable practical implementation of FO BLDC micromotor models.
• The proposed techniques are adaptable to various microcontroller platforms.
• This work facilitates the use of advanced FO control strategies in resource-constrained systems.