Optimal torque control of a synchronous machine (SM)
Problem to solve
- Developing a controller that enables synchronous machines (SMs) to accurately and energy-efficiently follow the torque command
Figure 1. Concept of optimal torque control of SMs
- Resolving the rank deficiency in real-time state and parameter estimation
Specific research topics
- Developing a generalized model predictive torque control (GMPTC) scheme for optimal operation of different SMs
- Developing a real-time state and parameter estimator that can reliably operate across a wide range of operating conditions
- Developing a reinforcement learning (RL)-based automatic gain tuner for the GMPTC scheme and estimator
- Validating the effectiveness of the combined GMPTC scheme, estimator, and automatic gain tuner for various SMs
Experimental setup
Figure 2. Experimental setup
Control and AI techniques used in research
- Model predictive control (MPC) techniques
- State and parameter estimation techniques
- Reinforcement learning (RL) algorithms
- Numerical optimization algorithms
Expected results
- The combination of the developed technologies demonstrates promising potential as a universal torque controller for SMs.
Relevant references
- K. Choi and K.-B. Park*, “Model Predictive Torque Control of Synchronous Machines Without a Current or Stator Flux Reference Generator,” in 2023 IEEE 32st International Symposium on Industrial Electronics (ISIE).
- K. Choi, Y. Kim, S.-K. Kim*, and K.-S. Kim*, “Computationally efficient model predictive torque control of permanent magnet synchronous machines using numerical techniques,” IEEE Transactions on Control Systems Technology, vol. 30, no. 4, pp. 1774-1781, 2022.
- K. Choi, Y. Kim, K.-S. Kim*, and S.-K. Kim*, “Real-time optimal torque control of interior permanent magnet synchronous motors based on a numerical optimization technique,” IEEE Transactions on Control Systems Technology, vol 29, no. 4, pp. 1815-1822, 2021.
Relevant research projects or grants
- GIST-삼성전자 지능형모터트랙 (삼성전자, 2023 - 2027)
- 자율주행 기능지원을 위한 소프트웨어 오픈 API를 가지는 전기차용 샤시플랫폼 개발 (한국자동차연구원, 2022 - 2024)
