short-paper

Open access

Very Low Power High-Frequency Floating Point FPGA PID Controller

Authors:

Radhit Dedania,

Sang-Woo JunAuthors Info & Claims

HEART '22: Proceedings of the 12th International Symposium on Highly-Efficient Accelerators and Reconfigurable Technologies

Pages 102 - 107

https://doi.org/10.1145/3535044.3535060

Published: 09 June 2022 Publication History

All formats PDF

Abstract

In this work, we present the design and implementation of a floating-point Proportional-Integral-Derivative (PID) controller accelerator which achieves a high rate of 637 K samples per second at 20 mW of power consumption, implemented on a Lattice UP5K FPGA. Our system delivers over 70 × the performance compared to a microprocessor with comparable size and power constraints, and 5 × the power efficiency compared to a larger and more capable ARM Cortex-M4F with hardware floating-point operators. We achieve such high performance using a systolic array design using simplified hardware floating-point operators implemented using embedded DSP blocks on a low-power FPGA. We support simple handling of complex reference such as sinusoidal signals by storing the reference as a time series in on-chip block RAM. The level of high performance, low power, and small size we achieve is necessary for our target application of micro, or insect-scale robotics.

References

[1]

Imran Arif Abdul Jamil and M. Moghavvemi. 2021. Optimization of PID Controller Tuning method using Evolutionary Algorithms. In 2021 Innovations in Power and Advanced Computing Technologies (i-PACT). 1–7. https://doi.org/10.1109/i-PACT52855.2021.9696875

[2]

Varun Aggarwal, Meng Mao, and U-M O’reilly. 2006. A self-tuning analog proportional-integral-derivative (pid) controller. In First NASA/ESA Conference on Adaptive Hardware and Systems (AHS’06). IEEE, 12–19.

Digital Library

[3]

Mohammad Pourmahmood Aghababa. 2016. Optimal design of fractional-order PID controller for five bar linkage robot using a new particle swarm optimization algorithm. Soft Computing 20, 10 (2016), 4055–4067.

Digital Library

[4]

Marc Andrysco, David Kohlbrenner, Keaton Mowery, Ranjit Jhala, Sorin Lerner, and Hovav Shacham. 2015. On subnormal floating point and abnormal timing. In 2015 IEEE Symposium on Security and Privacy. IEEE, 623–639.

Digital Library

[5]

Kiam Heong Ang, G. Chong, and Yun Li. 2005. PID control system analysis, design, and technology. IEEE Transactions on Control Systems Technology 13, 4(2005), 559–576. https://doi.org/10.1109/TCST.2005.847331

[6]

Daniele Bagni and Duncan Mackay. 2013. Floating-point PID controller design with Vivado HLS and system generator for DSP. Xilinx Application Note XAPP1163(2013).

[7]

B Borovic, Ai-qun Liu, Dan Popa, H. Cai, and F Lewis. 2005. Open-loop versus closed-loop control of MEMS devices: Choices and issues. J. Micromech. Microeng 15 (10 2005), 1917–1924. https://doi.org/10.1088/0960-1317/15/10/018

[8]

Y.F. Chan, M. Moallem, and W. Wang. 2004. Efficient implementation of PID control algorithm using FPGA technology. In 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601), Vol. 5. 4885–4890 Vol.5. https://doi.org/10.1109/CDC.2004.1429572

[9]

CK Chandni, VV Sajith Variyar, and K Guruvayurappan. 2017. Vision based closed loop pid controller design and implementation for autonomous car. In 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 1928–1933.

[10]

John Comstock Doyle, Bruce A. Francis, and Allen R. Tannenbaum. 1991. Feedback Control Theory. Prentice Hall Professional Technical Reference.

[11]

Mouser Electronics. Accessed 2022-04-04. Lattice ICE40UP5K-UWG30ITR1K. https://www.mouser.com/ProductDetail/Lattice/ICE40UP5K-UWG30ITR1K.

[12]

Sawyer B Fuller. 2019. Four wings: An insect-sized aerial robot with steering ability and payload capacity for autonomy. IEEE Robotics and Automation Letters 4, 2 (2019), 570–577.

[13]

Benjamin Goldberg, Raphael Zufferey, Neel Doshi, Elizabeth Farrell Helbling, Griffin Whittredge, Mirko Kovac, and Robert J Wood. 2018. Power and control autonomy for high-speed locomotion with an insect-scale legged robot. IEEE Robotics and Automation Letters 3, 2 (2018), 987–993.

[14]

P Gopi, Gopi krishna rao P V, M V Subramanyam, and K Satyaprasad. 2013. Model based Tuning of PID Controller. JOurnal of control and instrumentation 4 (01 2013), 16.

[15]

Juan J. Gude and Evaristo Kahoraho. 2012. Kappa-tau type PI tuning rules for specified robust levels: The frequency response method. In Proceedings of 2012 IEEE 17th International Conference on Emerging Technologies Factory Automation (ETFA 2012). 1–8. https://doi.org/10.1109/ETFA.2012.6489612

[16]

Vikram Iyer, Ali Najafi, Johannes James, Sawyer Fuller, and Shyamnath Gollakota. 2020. Wireless steerable vision for live insects and insect-scale robots. Science robotics 5, 44 (2020), eabb0839.

[17]

Noah T Jafferis, E Farrell Helbling, Michael Karpelson, and Robert J Wood. 2019. Untethered flight of an insect-sized flapping-wing microscale aerial vehicle. Nature 570, 7762 (2019), 491–495.

[18]

Elisha Joseph and O OlaiyaO.2018. Cohen-Coon PID Tuning Method: A Better Option to Ziegler Nichols-Pid Tuning Method. Computer Engineering and Intelligent Systems 9 (2018), 33–37.

[19]

C.B. Kadu and C.Y. Patil. 2016. Design and Implementation of Stable PID Controller for Interacting Level Control System. Procedia Computer Science 79 (2016), 737–746. https://doi.org/10.1016/j.procs.2016.03.097 Proceedings of International Conference on Communication, Computing and Virtualization (ICCCV) 2016.

[20]

Jeong-Seob Kim, Hyo-Won Jeon, and Seul Jung. 2007. Hardware implementation of nonlinear PID controller with FPGA based on floating point operation for 6-DOF manipulator robot arm. In 2007 International Conference on Control, Automation and Systems. 1066–1071. https://doi.org/10.1109/ICCAS.2007.4407057

[21]

Joao Lima, Ricardo Menotti, Joao M. P. Cardoso, and Eduardo Marques. 2006. A Methodology to Design FPGA-based PID Controllers. In 2006 IEEE International Conference on Systems, Man and Cybernetics, Vol. 3. 2577–2583. https://doi.org/10.1109/ICSMC.2006.385252

[22]

Kangdi Lu, Wuneng Zhou, Guoqiang Zeng, and Wei Du. 2018. Design of PID controller based on a self-adaptive state-space predictive functional control using extremal optimization method. Journal of the Franklin Institute 355, 5 (2018), 2197–2220. https://doi.org/10.1016/j.jfranklin.2017.12.034

[23]

David R Lutz and Chris N Hinds. 2005. Novel rounding techniques on the NEON floating-point pipeline. In Proc. 39th Asilomar Conf. Signals, Syst. Comput. 1342–1346.

[24]

R. Namba, T. Yamamoto, and M. Kaneda. 1997. Robust PID controller and its application. In 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation, Vol. 4. 3636–3641 vol.4. https://doi.org/10.1109/ICSMC.1997.633233

[25]

Atheer L Salih, Mahmoud Moghavvemi, Haider AF Mohamed, and Khalaf Sallom Gaeid. 2010. Flight PID controller design for a UAV quadrotor. Scientific research and essays 5, 23 (2010), 3660–3667.

[26]

David Shah, Eddie Hung, Clifford Wolf, Serge Bazanski, Dan Gisselquist, and Miodrag Milanovic. 2019. Yosys+ nextpnr: an open source framework from verilog to bitstream for commercial fpgas. In 2019 IEEE 27th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM). IEEE, 1–4.

[27]

R. Su and N. Kermiche. 1988. A learning scheme for open-loop and closed-loop control. In Proceedings IEEE International Symposium on Intelligent Control 1988. 523–528. https://doi.org/10.1109/ISIC.1988.65486

[28]

M V Subramanyam, K Satyaprasad, and Gopi krishna rao P V. 2014. Study on PID Controller Design and Performance Based on Tuning Techniques. 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies, ICCICCT 2014. https://doi.org/10.1109/ICCICCT.2014.6993183

[29]

Abdesselem Trimeche, Anis Sakly, Abdelatif Mtibaa, and Mohamed Benrejeb. 2011. PID Controller Using FPGA Technology. In Advances in PID Control, Valery D. Yurkevich (Ed.). IntechOpen, Rijeka, Chapter 14. https://doi.org/10.5772/18295

[30]

Jagannath Wadgaonkar, Kalyani Bhole, and Prateek Singh. 2015. Floating point FPGA architecture of PID controller. In 2015 International Conference on Industrial Instrumentation and Control (ICIC). 1259–1263. https://doi.org/10.1109/IIC.2015.7150941

[31]

Yankai Xu, Kai Shuang, Shan Jiang, and Xiaoliang Wu. 2009. FPGA implementation of a best-precision fixed-point digital pid controller. In 2009 International Conference on Measuring Technology and Mechatronics Automation, Vol. 3. IEEE, 384–387.

Digital Library

[32]

J. G. Ziegler and Nathaniel B. Nichols. 1942. Optimum Settings for Automatic Controllers. Journal of Dynamic Systems Measurement and Control-transactions of The Asme 115(1942), 220–222.

[33]

Eric William Zurita-Bustamante, Jesús Linares-Flores, Enrique Guzmán-Ramírez, and Hebertt Sira-Ramírez. 2012. FPGA Implementation of PID Controller for the Stabilization of a DC-DC “Buck” Converter. Chicago: INTECH Publishing.

Cited By

Kulisz JJokiel F(2024)A Hardware Implementation of the PID Algorithm Using Floating-Point ArithmeticElectronics10.3390/electronics1308159813:8(1598)Online publication date: 22-Apr-2024
https://doi.org/10.3390/electronics13081598
Khalifa DMartel M(2023)On the Functional Properties of Automatically Generated Fixed-Point Controllers2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)10.1109/CoDIT58514.2023.10284265(786-791)Online publication date: 3-Jul-2023
https://doi.org/10.1109/CoDIT58514.2023.10284265

Recommendations

Floating-point FPGA: architecture and modeling

This paper presents an architecture for a reconfigurable device that is specifically optimized for floating-point applications. Fine-grained units are used for implementing control logic and bit-oriented operations, while parameterized and ...
FPGA optimizations for a pipelined floating-point exponential unit
ARC'11: Proceedings of the 7th international conference on Reconfigurable computing: architectures, tools and applications

The large number of available DSP slices on new-generation FPGAs allows for efficient mapping and acceleration of floating-point intensive codes. Numerous scientific codes heavily rely on executing the exponential function. To this end, we present the ...
Low-precision Floating-point Arithmetic for High-performance FPGA-based CNN Acceleration
Low-precision data representation is important to reduce storage size and memory access for convolutional neural networks (CNNs). Yet, existing methods have two major limitations: (1) requiring re-training to maintain accuracy for deep CNNs and (2) ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

HEART '22: Proceedings of the 12th International Symposium on Highly-Efficient Accelerators and Reconfigurable Technologies

June 2022

114 pages

ISBN:9781450396608

DOI:10.1145/3535044

Copyright © 2022 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 June 2022

Check for updates

Author Tags

Qualifiers

Short-paper
Research
Refereed limited

Conference

HEART2022

HEART2022: International Symposium on Highly-Efficient Accelerators and Reconfigurable Technologies

June 9 - 10, 2022

Tsukuba, Japan

Acceptance Rates

HEART '22 Paper Acceptance Rate 10 of 21 submissions, 48%;

Overall Acceptance Rate 22 of 50 submissions, 44%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
695
Total Downloads

Downloads (Last 12 months)313
Downloads (Last 6 weeks)52

Reflects downloads up to 10 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Kulisz JJokiel F(2024)A Hardware Implementation of the PID Algorithm Using Floating-Point ArithmeticElectronics10.3390/electronics1308159813:8(1598)Online publication date: 22-Apr-2024
https://doi.org/10.3390/electronics13081598
Khalifa DMartel M(2023)On the Functional Properties of Automatically Generated Fixed-Point Controllers2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)10.1109/CoDIT58514.2023.10284265(786-791)Online publication date: 3-Jul-2023
https://doi.org/10.1109/CoDIT58514.2023.10284265

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents