Chaitanya Jugade
Position:
Department: Lab: eMail: Homepage: |
M. Tech. 2nd Year
Instrumentation and Control Embedded Systems Lab [email protected], [email protected] http://www.coepembeddedlab.com/chaitanya |
Biography
Chaitanya Jugade is a second year student of Master of Technology in Instrumentation and Control Engineering with specialization in Process Instrumentation, at College of Engineering, Pune. He received his Bachelor's degree in Instrumentation and Control Engineering from Government College of Engineering, Amravati in 2015. He also worked as a programmer analyst for two years in Cognizant Technology Solutions, Pune.
Chaitanya is working on to improve the memory footprints of Explicit MPC for real time application.
Chaitanya is working on to improve the memory footprints of Explicit MPC for real time application.
Personal
Research Interests
- Model Predictive Control
- Optimization
- Control Systems
- Embedded systems
- Universal Number system based MPC
- Novel Numerical method for optimization
- Machine learning for MPC
Master's Thesis
A Memory Efficient Embedded Model Predictive Control
Abstract:
For explicit model predictive control (EMPC), off-line pre-computed optimal feedback laws need to be stored in a look-up table for on-line evaluation. The need for memory to store the look-up table on embedded hardware limits applicability of EMPC to systems with few states, a small number of constraints, and short prediction horizons.
we are implementing a novel technique to reduce the memory footprints of EMPC solutions. The idea is based on encoding all data (i.e., the critical regions and the feedback laws) as posit numbers, which can be viewed as a memory-efficient replacement for the IEEE 754 floating-point standard. By using the posit number system, we achieve more accuracy with fewer bits, and posits can be efficiently deployed on embedded hardware like PLC, FPGA, DSP, ARM, etc. We are designing and implementing a posit-based EMPC for the control of the coupled tank system. The total memory footprints can be reduced by 75% without losing control accuracy. An additional advantage of the approach is that it can be applied on the top of existing complexity reduction techniques.
Abstract:
For explicit model predictive control (EMPC), off-line pre-computed optimal feedback laws need to be stored in a look-up table for on-line evaluation. The need for memory to store the look-up table on embedded hardware limits applicability of EMPC to systems with few states, a small number of constraints, and short prediction horizons.
we are implementing a novel technique to reduce the memory footprints of EMPC solutions. The idea is based on encoding all data (i.e., the critical regions and the feedback laws) as posit numbers, which can be viewed as a memory-efficient replacement for the IEEE 754 floating-point standard. By using the posit number system, we achieve more accuracy with fewer bits, and posits can be efficiently deployed on embedded hardware like PLC, FPGA, DSP, ARM, etc. We are designing and implementing a posit-based EMPC for the control of the coupled tank system. The total memory footprints can be reduced by 75% without losing control accuracy. An additional advantage of the approach is that it can be applied on the top of existing complexity reduction techniques.
Publications
- Chaitanya Jugade, Deepak Ingole, Dayaram N Sonawane, Michal Kvasnica, John Gustafson,A Memory Efficient FPGA Implementation of Offset-Free Explicit Model Predictive Controller, IEEE Transactions on Control Systems Technology, 2022
- Chaitanya Jugade, Deepak ingole, Dayaram Sonawane, Michal Kvasnica, John Gustafson, “A Memory Efficient Implementation of Offset Free Explicit Model Predictive Controller on FPGA Using Posits”, Submitted in IEEE Transaction on Control System Technology.
- Chaitanya Jugade, Deepak ingole, Dayaram Sonawane, Michal Kvasnica, John Gustafson, “A Framework for Embedded Model Predictive Control using Posits”, Accepted in 59th Conference on Decision and Control (CDC 2020), IEEE, Jeju Island, Republic of Korea, 2020.
- Chaitanya Jugade, Deepak ingole, Dayaram Sonawane, Michal Kvasnica, John Gustafson, "A Memory Efficient Explicit Model Predicitve Control using Posits", Published on IEEE, 6th Indian Control Conference (ICC 2019), IEEE, IIT Hyderabad, India, 2019.