---
name: motor-control-90d4143cff0e
description: Motor control algorithms and driver implementation
category: Application-Specific
allowed-tools:
  - Bash
  - Read
  - Write
  - Edit
  - Glob
  - Grep
graph:
  domains: [domain:embedded-systems]
  specializations: [specialization:embedded-systems]
  skillAreas: [skill-area:rtos-programming, skill-area:firmware-development]
  roles: [role:embedded-engineer]
---

# Motor Control Skill

## Overview

This skill provides motor control algorithm implementation and driver development expertise for embedded systems controlling DC, BLDC, stepper, and AC induction motors.

## Capabilities

### PWM Generation
- Center-aligned PWM configuration
- Dead-time insertion
- Complementary output setup
- PWM frequency selection
- Duty cycle modulation
- SVPWM (Space Vector PWM)

### Control Algorithms
- FOC (Field-Oriented Control)
- Scalar V/f control
- Six-step commutation
- Sinusoidal commutation
- DTC (Direct Torque Control)
- Model predictive control

### Position/Speed Feedback
- Encoder interface (quadrature)
- Hall sensor configuration
- Resolver interface
- Sensorless algorithms
- Back-EMF zero-crossing
- Observer-based estimation

### Current Sensing
- Shunt resistor configuration
- Current amplifier setup
- ADC synchronization with PWM
- Oversampling strategies
- DC offset compensation
- Phase reconstruction

### Control Loops
- Current loop (torque control)
- Speed loop (velocity control)
- Position loop (servo control)
- Anti-windup strategies
- Feed-forward compensation
- Gain tuning methods

### Motor Identification
- Parameter measurement
- Auto-tuning procedures
- Resistance/inductance measurement
- Back-EMF constant
- Inertia estimation

### Protection Features
- Overcurrent protection
- Overvoltage protection
- Overtemperature monitoring
- Stall detection
- Safe torque off (STO)

## Target Processes

- `device-driver-development.js` - Motor driver implementation
- `real-time-architecture-design.js` - Real-time control design
- `isr-design.js` - Control loop ISR design

## Dependencies

- Motor control libraries (ST MC SDK, TI MotorWare)
- DSP libraries for fixed-point math
- Encoder/Hall sensor hardware

## Usage Context

This skill is invoked when tasks require:
- Motor driver development
- FOC algorithm implementation
- Position/speed control
- Motor parameter tuning
- Protection circuit design

## Motor Types Supported

| Type | Control Method | Feedback |
|------|---------------|----------|
| Brushed DC | PWM duty cycle | Encoder optional |
| BLDC | Six-step, FOC | Hall, encoder, sensorless |
| PMSM | FOC | Encoder, resolver, sensorless |
| Stepper | Step/direction, microstepping | Open-loop, encoder |
| AC Induction | V/f, FOC | Encoder, sensorless |

## FOC Implementation Example

```c
typedef struct {
    float i_alpha, i_beta;    // Clarke transform output
    float i_d, i_q;           // Park transform output
    float v_d, v_q;           // Voltage commands
    float v_alpha, v_beta;    // Inverse Park output
    float theta;              // Rotor angle
    float speed;              // Rotor speed
} foc_state_t;

void foc_current_loop(foc_state_t* state, float i_a, float i_b, float i_c) {
    // Clarke transform
    clarke_transform(i_a, i_b, i_c, &state->i_alpha, &state->i_beta);

    // Park transform
    park_transform(state->i_alpha, state->i_beta, state->theta,
                   &state->i_d, &state->i_q);

    // PI controllers
    state->v_d = pi_controller(&pid_d, state->i_d_ref - state->i_d);
    state->v_q = pi_controller(&pid_q, state->i_q_ref - state->i_q);

    // Inverse Park
    inv_park_transform(state->v_d, state->v_q, state->theta,
                       &state->v_alpha, &state->v_beta);

    // SVPWM
    svpwm_generate(state->v_alpha, state->v_beta, pwm_duties);
}
```

## Configuration

```yaml
motor_control:
  motor_type: bldc | pmsm | stepper | induction
  control_method: foc | six_step | vf | step_dir
  pwm_frequency: 20000  # Hz
  current_loop_rate: 20000  # Hz
  speed_loop_rate: 1000  # Hz
  feedback: encoder | hall | sensorless
```


---
Source attribution: a5c-ai
Original project: https://github.com/a5c-ai/babysitter/blob/feb68abe397acc14f32b34984975c48fedba2b33/library/specializations/embedded-systems/skills/motor-control/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

# MIT License

Copyright (c) 2025 A5C AI

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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The above copyright notice and this permission notice shall be included in all
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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# Mega AI Hub resource metadata

Creator / publisher: a5c-ai
Original project: https://github.com/a5c-ai/babysitter/blob/feb68abe397acc14f32b34984975c48fedba2b33/library/specializations/embedded-systems/skills/motor-control/SKILL.md
Attribution basis: Source repository record

Fields of work: Development & Engineering, Product Management
Roles: Backend Developer, Embedded / IoT Developer, Product Manager
Specialties: Backend
Tools: Bash
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 7df0f76d0acf63afd750951c2226f37d048cb0003db6ec667841cdf754fa00c6