A Computationally Lightweight Multi-Rate Estimation and Passivity-Based Control Architecture for Sensorless BLDC Fan Drives

This repository contains the preprint manuscript, theoretical proofs, and simulation datasets for the development of a computationally efficient, multi-rate estimation and control architecture designed for small-scale, sensorless Brushless DC (BLDC) motor drives. Conventional sensorless control architectures face strict computational bottlenecks when deployed on standard embedded microcontrollers, particularly when attempting to simultaneously address zero-speed observability, thermal parameter drift, and non-linear aerodynamic load variations. This submission presents a physics-informed framework that resolves these challenges through a structurally decomposed electro-thermo-mechanical approach, intended for standalone embedded applications. Key Technical Contributions: Proxy-State Formulation: A novel state representation that promotes back-EMF components to state variables, strictly preserving observability at exactly $0$ RPM without requiring mechanical state reconfiguration. Interacting Multiple Model (IMM) Fusion: Seamless probabilistic handover between a standstill Unscented Kalman Filter (UKF) utilizing Active Saturation Pulse (ASP) excitation with heavy-tailed Student's-$t$ innovations, and a running Extended Kalman Filter (EKF). Deterministic Thermal Augmentation: Replaces conventional random-walk stator resistance tracking with a first-principles thermodynamic energy balance, preventing long-horizon estimation drift during continuous-duty operation. Passivity-Based Adaptive Control: An Input-to-State Stable (ISS) adaptive PI control law incorporating a passivity-preserving anti-windup mechanism to handle voltage saturation. Multi-Rate Computational Efficiency: By decomposing the estimator into a $10$ kHz fast electrical loop and a $100$ Hz reduced-rate recursive least-squares (RLS) mechanical adaptation layer, the architecture restricts the computational burden to approximately $2902$ FLOPs per cycle, consuming only $35.5\%$ of the CPU duty cycle on a standard $170$ MHz STM32G4-class microcontroller.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-24
DOI
https://doi.org/10.5281/zenodo.20835395
Primary Topic
Sensorless Control of Electric Motors
Type
article
Field-Weighted Citation Impact
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article

A Computationally Lightweight Multi-Rate Estimation and Passivity-Based Control Architecture for Sensorless BLDC Fan Drives

Sheldon S. Williamson, Shubhobrata Rudra
Zenodo (CERN European Organization for Nuclear Research)
Sensorless Control of Electric Motors
article

A Computationally Lightweight Multi-Rate Estimation and Passivity-Based Control Architecture for Sensorless BLDC Fan Drives

Sheldon S. Williamson, Shubhobrata Rudra
article en

Abstract

This repository contains the preprint manuscript, theoretical proofs, and simulation datasets for the development of a computationally efficient, multi-rate estimation and control architecture designed for small-scale, sensorless Brushless DC (BLDC) motor drives. Conventional sensorless control architectures face strict computational bottlenecks when deployed on standard embedded microcontrollers, particularly when attempting to simultaneously address zero-speed observability, thermal parameter drift, and non-linear aerodynamic load variations. This submission presents a physics-informed framework that resolves these challenges through a structurally decomposed electro-thermo-mechanical approach, intended for standalone embedded applications. Key Technical Contributions: Proxy-State Formulation: A novel state representation that promotes back-EMF components to state variables, strictly preserving observability at exactly $0$ RPM without requiring mechanical state reconfiguration. Interacting Multiple Model (IMM) Fusion: Seamless probabilistic handover between a standstill Unscented Kalman Filter (UKF) utilizing Active Saturation Pulse (ASP) excitation with heavy-tailed Student's-$t$ innovations, and a running Extended Kalman Filter (EKF). Deterministic Thermal Augmentation: Replaces conventional random-walk stator resistance tracking with a first-principles thermodynamic energy balance, preventing long-horizon estimation drift during continuous-duty operation. Passivity-Based Adaptive Control: An Input-to-State Stable (ISS) adaptive PI control law incorporating a passivity-preserving anti-windup mechanism to handle voltage saturation. Multi-Rate Computational Efficiency: By decomposing the estimator into a $10$ kHz fast electrical loop and a $100$ Hz reduced-rate recursive least-squares (RLS) mechanical adaptation layer, the architecture restricts the computational burden to approximately $2902$ FLOPs per cycle, consuming only $35.5\%$ of the CPU duty cycle on a standard $170$ MHz STM32G4-class microcontroller.

Zenodo (CERN European Organization for Nuclear Research)
National Institute of Technology Rourkela (IN), Ontario Tech University (CA)
Affordable and clean energy
Openalex Percentile: Top 11%
Sensorless Control of Electric Motors
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