Maintaining deterministic real-time performance is critical for applications ranging from industrial robotics to medical devices. Embedded real-time control systems provide the computational horsepower and specialized technologies to ensure reliable, high-speed operation.
Embedded real-time control technologies are crucial enablers for the smart, autonomous, and high-performance products in demand today and into the future. By leveraging deep expertise in areas like embedded real-time architectures, sensor integration, control theory, and model-based design, companies can their next real-time product vision a reality.
We explore some of the key technologies and architectures along with example use cases below. Continue Reading
What are Embedded Systems?
In its simplest form, an embedded system is a computing system, built of a processor, memory, and input/output devices, with a dedicated function inside of a larger device or system.
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Key embedded real-time control technologies and architectures along with example use cases include:
Microcontroller/Microprocessor Based Control - For many real-time applications, utilizing dedicated microcontroller units (MCUs) or microprocessor chips provides an optimized embedded computing solution. Chip vendors like NXP, Microchip, TI, and others offer families of real-time MCUs and heterogeneous processors with architecture features tailored for control.
- Example: An automated Hospital Logistics system using autonomous robotic carts to transport materials. The cart's motor control, sensor interfacing, navigation and fleet management is coordinated by distributed ARM microprocessors with hard real-time performance.
FPGA-Based Control - Field Programmable Gate Arrays (FPGAs) are integrated circuits that can be configured with custom digital logic flows and parallelized signal processing. This architectural flexibility makes FPGAs very powerful for ultra-high-speed real-time control that exceeds the capabilities of microprocessors.
- Example: Vision-guided semiconductor manufacturing robots use FPGA-based control for semiconductor manufacturing robots to process high-definition video at multi-gigapixel per second rates to enable real-time defect detection and precision part alignment.
Real-Time Operating Systems - While some applications can use bare-metal firmware running directly on hardware, deploying a commercial real-time operating system (RTOS) like FreeRTOS, embOS or Zephyr provides scheduling, task management, and low-level driver support to build sophisticated real-time applications.
- Example: A surgical robot with multiple sensor interfaces (vision, haptics, kinematics) and multiple control loops for instrument positioning and master/slave workflow control runs an RTOS to manage and synchronize independent tasks with deterministic timing.
Motor Control: AC, DC, Brushed/Brushless - Precisely controlling rotation of motors is fundamental to automation systems. Embedded motor controllers use specialized processors and control algorithms tailored to different motor types to achieve high-performance operation and efficiency.
- Example: An HVAC optimization system integrates embedded brushless DC motor drives with IoT connectivity to provide real-time adaptive control of air handling unit motors, fans, pumps based on occupancy sensing and energy pricing data.
Sensor Integration - From analog interfaces to digital/serial protocols to wireless sensor connectivity (Bluetooth, Zigbee, etc.), embedded systems must reliably interface with diverse sensor types as inputs to real-time control loops.
- Example: A pan/tilt platform designed for autonomous drone tracking integrates inertial sensors, GPS, and high-speed machine vision cameras via MIPI interfaces to maintain stable tracking in real-time.
Hardware-in-the-Loop Simulation - Prior to deploying embedded control on physical hardware, engineers can use real-time simulation testbeds with hardware-in-the-loop (HIL) to validate control algorithms, tune parameters, and test failure mode responses.
- Example: An automotive company uses a HIL simulator combining physical engine control units connected to real-time plant models to perform verification of new engine control software across operating envelopes in a virtual environment.
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