The Improved Division-Less MT-Type Velocity Estimation Algorithm for Low-Cost FPGAs

Aleš Hace

doi:10.3390/electronics8030361

Abstract

Advanced motion control applications require smooth and highly accurate high-bandwidth velocity feedback, which is usually provided by an incremental encoder. Furthermore, high sampling rates are also demanded in order to achieve cutting-edge system performance. Such control system performance with high accuracy can be achieved easily by FPGA-based controllers. On the other hand, the well-known MT method for velocity estimation has been well proven in practice. However, its complexity, which is related to the inherent arithmetic division involved in the calculus part of the method, prevents its holistic implementation as a single-chip solution on small-size low-cost FPGAs that are suitable for practical optimized control systems. In order to overcome this obstacle, we proposed a division-less MT-type algorithm that consumes only minimal FPGA resources, which makes it proper for modern cost-optimized FPGAs. In this paper, we present new results. The recursive discrete algorithm has been further optimized, in order to improve the accuracy of the velocity estimation. The novel algorithm has also been implemented on the experimental FPGA board, and validated by practical experiments. The enhanced algorithm design resulted in improved practical performance.

Highlights

Nowadays, digital programmable circuits such as FPGAs are used widely for many industrial applications [1]
FPGAs can ensure highly accurate and short sampling periods, which are required for advanced motion control applications
The velocity estimation obtained by the FPGA was matched with the results obtained offline on the post-processing computer utilizing the floating-point arithmetic in the double-precision mode

Summary

Introduction

Digital programmable circuits such as FPGAs are used widely for many industrial applications [1]. FPGA devices have reached a high maturity level in terms of performance, power consumption, and cost, which makes them suitable for different application fields [2] that involve sensor systems [3,4], control systems [5,6], haptic interfaces [7,8], robotics [9,10,11], and other advanced electronic devices for signal processing and communications, e.g., [12,13,14,15]. A short processing time of control algorithms is possible; the feature-rich FPGAs have overwhelming resources that are required for performing complex computation algorithms [17,18]

Methods

Results

Discussion

Conclusion