How MCUs Improve System Performance in Robotic Motor Control Designs

Robotic systems automate repetitive tasks, undertake complex and laborious operations, and work in environments that are dangerous or harmful to humans. Higher integration and higher performance microcontrollers (MCUs) enable higher power efficiency, smoother and safer motion, and higher precision, thereby increasing productivity and automation. For example, higher accuracy (sometimes within 0.1mm) is important for applications that handle laser welding, precision coating, or inkjet or 3D printing.

The number of axes in the robot and the type of control architecture required (centralized or distributed) determine the right MCU or motor control integrated circuit (IC) for the system. Modern factories use a combination of robots with different numbers of axes and degrees of freedom of motion (movement and rotation in the x, y, or z plane) to meet the needs of different manufacturing stages; therefore, different control architectures are used throughout the factory floor.

When selecting an MCU, choosing one with extra performance headroom can enable scalability and support for additional features in the future. Planning for scalability and additional features in advance during the design process can also save cost, time, and complexity.

This article will explore 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 solves the thermal issues 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 acquired externally through a resolver board or aggregator connected to the encoder.

Typically, in this architecture, multiple power stages are located on the same PCB or in close proximity so that one MCU can control multiple axes . This approach simplifies real-time control and synchronization between multiple axes because long communication lines are not required between multiple motor control MCUs.

The motor control MCU/MPU in a centralized architecture needs to have a high-performance real-time processing core (such as the R5F core or DSP), a real-time communication interface (such as EtherCAT), sufficient PMW channels, and peripherals for voltage and current sensing. MCUs such as the AM243x can build scalable multi-axis systems, providing real-time control peripherals for up to six axes and implementing real-time communication in a single chip.

In the past, FPGA or ASIC devices were mainly used for centralized motor control in automation systems. However, modern MCUs based on Arm Cortex, such as the AM243x, have become increasingly popular in recent years. These MCUs are highly integrated and cost-effective, helping designers meet the performance requirements of their systems while achieving scalability and flexibility in their designs.

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 to connect the cabinet and the mechanical motors of the joints, as well as the position sensors and aggregators. These wires are not only costly, but also prone to wear and tear, requiring maintenance.

Figure 1: Block diagram of a decentralized motor control architecture for multi-axis systems

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 collaborative robotic manipulators.

A decentralized architecture integrates multiple single-axis motor drives into each joint of the robot and connects and synchronizes them via a real-time communication interface such as EtherCAT. Each drive typically controls one axis and handles certain safety functions locally. Therefore, each MCU requires real-time control and communication capabilities, single-axis motor control peripherals, three to six PWM channels, and on-chip successive approximation register analog-to-digital converters or delta-sigma modulator inputs.

In these applications, the position sensor is usually close to the MCU, so these MCUs need a digital or analog interface to read the data from the position sensor. Although this architecture requires more MCUs, it can significantly reduce system-level costs due to less wiring requirements between the power bus and the communication interface. Modern real-time MCUs (such as the F28P65x) integrate not only all necessary peripherals, but also safety peripherals, thus providing a single-chip or dual-chip solution for integrated axes in a decentralized architecture and achieving high performance in a small form factor.

Figure 2: Block diagram of a decentralized motor control architecture for a single-axis system

Conclusion

While motors may not be the hottest choice in robotics today (especially when compared to AI-enabled systems), they are the muscle that keeps 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 motor control designs.