Multi-axis motor control design [Comparison of DSP solution and FPGA motor control solution]

It is important that modern drive systems integrate control loop accuracy, scalability, network communication, peripheral control, data and design security, functional safety and reliability. In addition, the motor must be accurately and synchronously controlled without compromising performance and certainty, especially in multi-axis control systems.

The electrical energy consumed by the motor accounts for a very high proportion of global electricity consumption. To a large extent, the energy consumption of the motor depends on the motor and transmission efficiency. In order to reduce consumption, improve transmission efficiency and improve performance, energy efficiency standards have been implemented by regulatory agencies around the world. Therefore, the deployment of motor drives is increasingly using high precision, high performance motor control algorithms. It is important that modern drive systems integrate control loop accuracy, scalability, network communication, peripheral control, data and design security, functional safety and reliability. In addition, the motor must be accurately and synchronously controlled without compromising performance and certainty, especially in multi-axis control systems. To meet these control and integration requirements, embedded designers design drives that not only can run complex motor control algorithms, but also support multiple peripheral communications in an increasingly connected environment.

Comparison of Microcontroller/Digital Signal Processor Solutions with FPGA Motor Control Solutions

Motor control application design Traditionally uses a microcontroller (MCU) or digital signal processor (DSP) to run motor control algorithms. However, as people increasingly deploy high-performance industrial control systems with higher levels of integration, scalability, and existing IP reusability, FPGAs are a priority, especially in combination with ARM Cortex M3 microcontrollers and FPGA logic resources. The program provides an ideal division of labor for many key tasks. There are several reasons why they are increasingly being adopted.

First, due to the architecture and access to the instruction memory, the microcontroller is well suited for slower serial tasks, but FPGAs are an ideal choice for time-critical parallel processing. For example, in multi-axis control, multiple motors that are speed independent are controlled by implementing a deterministic control loop. Typically, multi-axis motor control systems also integrate peripheral control, sensor interface, protection logic/security and network communication. Tasks related to these functions each have different execution times and priorities.

The microcontroller or DSP drive controller uses a masking and interrupt service routine to assign an execution priority level for each task. Some unshielded tasks may be executed before the control loop, resulting in an indeterminate actual execution time of the control loop. In contrast, FPGA control loops and system-on-a-chip (SoC) FPGAs are implemented in parallel with other processes, and in multi-axis control loops, they can also be run sequentially using Time Division Multiplexing (TDM) schemes.

SoC FPGAs with ARM Cortex-M3 microcontrollers perform this application even more efficiently: this FPGA is ideal for control loops that are executed in a strictly deterministic timing mode, while the lower speed interface can be combined with ARM M3 micro Controller connection (Figure 1).

Figure 1: Highly Integrated Motor Control Solution for Flash-Based SmartFusion2 SoC FPGA Implementation

Table 1: Microcontroller/Digital Signal Processor Solutions vs FPGA Motor Control Solutions

In addition, FPGA solutions improve scalability and performance. As mentioned above, in FPGA-based control, tasks with lower priority have no effect on the execution of the control loop. Therefore, increasing the number of motors does not affect the execution time of the control loop. Depending on the requirements, you can expand the IP portfolio running on the FPGA, from driving two brushless DC (BLDC) step motor channels to a six-axis solution, or increasing motor performance to over 70,000 RPM.

In addition, FPGA-based multi-axis control can support higher pulse width modulation (PWM) switching frequencies up to hundreds of KHz. In addition to features such as integrated PWM generation, FPGA-based motor controllers include embedded processing, control peripherals (such as USB, PCIe, I2C, and CAN) dedicated blocks, multi-user defined I/O, and ready-to-use reference designs. Type IP library. It is important to remember that the motor control algorithm is not the only required function. Typically, a complete motor control design requires one or more communication interfaces and control I/O. These interfaces are not designed for high performance, so they are ideal for implementation with microcontrollers such as the M3. The communication interface can be a CAN bus, SPI, UART or other control bus. SoC FPGAs provide a bridge between the customer's peripherals and the rest of the design, and when other peripherals are needed, a microcontroller-based SoC FPGA can be used. Modular IP components also simplify customization and expansion, supporting different combinations of multi-axis motors or high rotational speed solutions while meeting evolving regional technical standards. The more compact the IP block (ie, the entire combination of less than 10,000 logic elements), the more net space is available to support integration requirements.

Reliability and security are two other important aspects of an FPGA solution. Avionics is especially important when designing systems for applications such as satellite solar panels, steering and control systems, medical scanners, nuclear power plant machinery and actuators, and engine control applications. Many semiconductor components, including MCU/DSP, are susceptible to single-event upset (SEU). The best choice for reliability and security is based on Flash rather than SRAM. All configuration information chips are located in non-volatile memory and they never expose the bit stream at startup. FPGAs are also more reliable than microcontrollers when implementing motor control and networking functions where deterministic timing is important. The timing difference of the microcontroller is a few milliseconds, while the timing difference of the FPGA is only a few nanoseconds or less.

FPGAs also meet the security challenge requirements of deterministic multi-axis motor control solutions. In today's industry, designs may be cloned, or their data may be threatened with tampering or theft. Another threat faced by OEMs is that they deal with all suppliers or contract manufacturers that require design and IP or may over-manufacture. Most MCUs/DSPs may not provide the level of advanced security features inherent in FPGAs that provide hardware security, design security, and data security in a layered approach (three key elements of a comprehensive security strategy). Some flash-based FPGAs can also act as trusted root devices with critical storage capabilities to protect the hyper-connected industrial IoT from malicious attacks. FPGAs use features such as physical anti-cloning (PUF) to address security requirements. In public/private key schemes, public key infrastructure (PKI) is used, and private keys are used to implement M2M authentication. Other features include cryptographic accelerators, random number generators, hardware firewalls to protect the CPU/DSP core, and differential power analysis (DPA) measures that work together to allow the entire system to layer security as needed to protect hardware and data.

The key advantages of FPGA-based motor control implementations compared to microcontroller- or DSP-based implementations are determinism, scalability and performance, reliability, and durability and safety.

● Deterministic - In an MCU or DSP implementation, tasks are run sequentially, with different execution times and interrupt priorities. The execution time of the ISR is not necessarily limited and may result in uncertainty. In contrast, FPGAs run tasks in parallel, the execution time of each task is deterministic, and always produces deterministic output.

● Scalability and performance - MCU/DSP performance is not optimized for multi-axis motor control with higher switching frequency. High speed motors require higher switching frequencies (eg 500 kHz) and ' = 2 μs ' FOC loop execution. The MCU hardware architecture (PWM, ADC, and GPIO) has limitations in controlling multiple motors. With FPGA implementation, the advanced field oriented control (FOC) execution time is 1 μs. TDM for FOC can be used to control multiple motors. Any I/O pin can be configured for the PWM and ADC interfaces. The FPGA integrates multiple Industrial Ethernet protocols, HMIs, and other interfaces not supported by typical MCU/DSP.

● Reliability and durability – MCUs and DSPs are susceptible to soft failure (SEU) and have a short life. FPGAs are not affected by SEU and are resistant to radiation in a variety of applications, and product life is typically over 20 years.

• Security – MCU/DSP-based implementations are at risk of tampering, cloning, and manufacturing, while FPGA-based implementations are tamper-proof, secure boot, secure communications, and strong security inheritance.

Figure 2: SmartFusion2 Dual-Axis Motor Control Starter Kit (SF2-MC-STARTER-KIT)

It is very challenging for motor developers to meet today's energy efficiency regulations and new technology requirements while ensuring that the design is scalable to support different multi-axis motors or high rotational rate solution combinations. Flash-based SoC FPGAs address these challenges, combining processing power with hardware and software programmability and the ability to integrate new features and functionality while promoting multiple layers of security. They provide advanced features such as multi-axis control, deterministic response, parallel processing, functional integration and flexibility, enabling designers to reduce the total cost of ownership (TCO) of their systems.

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