Robotic systems automate repetitive tasks, take on complex and laborious tasks, and work in environments that are dangerous or harmful to humans. More integrated, high-performance microcontrollers (MCUs) enable higher power efficiency, smoother and safer motion, and higher accuracy for increased productivity and automation. For example, higher accuracy (sometimes at 0.).within 1mm) is important for handling applications such as laser welding, precision coatings, or inkjet or 3D printing.
The number of axes of the robotic arm and the type of control architecture required (centralized or distributed) determine which MCU or motor control integrated circuit (IC) is suitable for the system. Modern factories use a combination of robots with different axes and degrees of freedom of movement (moving and rotating in the x, y, or z planes) to meet the needs of different stages of manufacturing; As a result, different control architectures are used throughout the factory floor.
When choosing an MCU, choosing one with extra performance headroom enables future scalability and support for additional features. Planning ahead for scalability and add-ons can also save cost, time, and complexity during the design process.
This article examines both centralized and distributed (or decentralized) motor control architectures, as well as design considerations for integrated real-time MCUs that implement them.
Centralized architecture
In a centralized system, one MCU is used to control multiple axes. This approach effectively addresses heat dissipation in higher power motor drives (typically over 2kW to 3kW) that require large heat sinks and cooling fans. In this architecture, position data is typically taken externally via a resolver board or aggregator connected to the encoder.
Typically, in this architecture, multiple power stages are located on the same PCB or are in close proximity, so a single MCU can control multiple axes. This approach simplifies real-time control and synchronization between multiple axes, as long communication lines are not required between multiple motor control MCUs.
Motor control MCU MPUs in centralized architectures require high-performance real-time processing cores (such as R5F cores or DSPs), real-time communication interfaces (such as EtherCAT), ample PMW channels, and peripherals for voltage and current sensing. MCUs such as the AM243X enable scalable multi-axis systems that provide real-time control peripherals for up to six axes and enable real-time communication in a single chip.
In the past, FPGAs or ASIC devices were primarily used for centralized motor control in automation systems. However, modern MCUs based on ARM Cortex, such as the AM243X, have gained popularity in recent years. These MCUs are highly integrated and cost-effective, helping designers meet the performance requirements of their systems while enabling design scalability and flexibility.
While centralized control architectures can meet the performance and efficiency design requirements of high-power automation systems such as heavy-payload industrial robots, these systems require the use of additional cables, mechanical motors that connect cabinets and joints, and position sensors and aggregators. Not only are these wires costly, but they are also prone to wear and tear and require maintenance.
Figure 1: Block diagram of a decentralized motor control architecture for a multi-axis system.
Decentralized or distributed architecture
Recently, decentralized or distributed architectures (Figure 2) have become increasingly popular in systems with lower power requirements and have become the standard approach for cobot manipulators.
The decentralized architecture integrates multiple single-axis motor drives into each joint of the robot and connects and synchronizes them via real-time communication interfaces such as EtherCAT. Typically each drive controls one axis and handles certain safety functions locally. As a result, each MCU requires real-time control and communication capabilities, single-axis motor control peripherals, three to six PWM channels, on-chip successive approximation register analog-to-digital converters, or δ-modulator inputs.
In these applications, the position sensor is often located close to the MCU, so these MCUs require a digital or analog interface to read the data from the position sensor. While this architecture requires more MCUs, it can significantly reduce system-level costs due to the need for less cabling between the power bus and the communication interface. Modern real-time MCUs, such as the F28P65X, integrate not only all the necessary peripherals, but also security peripherals, providing a single- or dual-chip solution for integrated axes in a decentralized architecture with high performance in a small form factor.
Figure 2: Block diagram of a decentralized motor control architecture for a single-axis system.
Conclusion
While electric motors may not be the hottest choice in robotics right now (especially when compared to AI-enabled systems), they are the "muscles" that keep factories running and a vital part of modern manufacturing, so choosing the right control device requires a lot of consideration. As these devices become more integrated, additional features such as edge computing and wireless connectivity may be incorporated into the motor control design.
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