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Sensorless Speed Control for SPMSM via Nonlinear Observer and Modified Super-Twisting ADRC |
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Mingyuan Hu, Kwanho You(Sungkyunkwan University, Korea) |
| In this paper, a modified super-twisting active disturbance rejection control (MSTADRC) and a nonlinear observer (NOB) are used to implement a sensorless speed control for surface mounted permanent magnet synchronous motor (SPMSM), which has a complex internal structure and is characterized by nonlinear and variable parameters. A new reaching law is designed in super-twisting sliding mode control (STSMC). We proposed the MSTADRC via STSMC and active disturbance rejection control (ADRC). NOB has been selected for estimation of position or angle value. Finally, the validity and effectiveness of this approach are illustrated by simulation. |
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PMSM MTPA-control with Reinforcement Learning and CO2 burden |
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Raik Orbay, Yijie Ren, Joachim Härsjö, Lukasz Sobieraj(Volvo Car Corporation, Sweden), Martin Fabian, Torbjörn Thiringer(Chalmers University of Technology, Sweden) |
| Maximum Torque per Ampere (MTPA) approach allows rapid & precise electric motor control, while assuring the efficiency. To incorporate the MTPA approach, look-up tables (LuT) are populated based on physical principles. Especially for embedded systems like encountered in vehicles, parsing data from densely populated tensors like the LuT is rather resource intensive. In this work, supervised learning will be used to devise a regression based surrogate model for LuT by Neural Networks. In an effort to reduce the training data
needs, a Reinforcement Learning (SARSA) based MTPA control will additionally be developped. Finally, a CO2e emission
budget for chosen approaches will be reported. |
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Fuzzy dynamic sliding mode control for permanent magnet synchronous generator model |
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Ramasamy Kavikumar, Seung-Hoon Lee, Ramalingam Sakthivel, Ohmin Kwon(Chungbuk National University, Korea) |
| This paper investigates the fuzzy control problem for fuzzy permanent magnet synchronous motor (PMSM) model via dynamic sliding-mode method. The key advantage of the developed approach is that a very restrictive assumptions in most existing sliding mode control approaches for fuzzy systems have been removed. This paper employs the dynamic sliding mode scheme to control nonlinear PMSM. Thus, sufficient conditions are proposed to make the sliding surface reachable with the existence of the system perturbations to make the augmented system stable. Finally, the applicability of designed dynamic sliding methodology is demonstrated by a controller design for the nonlinear PMSM model. |
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Double ESOs based Active Disturbance Rejection Control for Permanent Magnet Synchronous Motors |
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Gwanyeon Kim, Wonhee KIM(Chung-Ang University, Korea) |
| The double extended state observers that enhance the estimation performance is proposed to improve the permanent magnet synchronous motor position control performance. Although conventional single ESO estimates not only the states but the disturbance, the estimation errors inevitably remain. To reduce the remained estimation errors, the additional ESO is employed to estimate the remained errors from a single ESO. Then, the additional estimated states are integrated with the estimated values from the single ESO to obtain a more accurate estimate value. The experiment is conducted to verify the performance of the proposed method compared with the conventional ESO and cascade ESO. |
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H∞ LPV Observer Design for Position-sensorless Control of Switched Reluctance Motors: An LMI Approach |
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Seungju Moon, DongYoon Han, Huibeom Youn, Gyuwon Kim(Kumoh National Institute of Technology, Korea), Bogoon Kim(NUC Electronics, Korea), Jaepil Ban(Kumoh National Institute of Technology, Korea) |
| Switched reluctance motors (SRMs) are valued for their cost-effectiveness, simple structure, and high power density in industries. To cut costs further, operating SRMs without position sensors is vital. This study introduces a technique using H∞ linear parameter varying (LPV) observer for sensorless SRM control. A 6/4 SRM is approximated as an LPV system with errors. An H∞ LPV observer is then proposed to precisely estimate rotor position despite model uncertainties and disturbances. The observer is designed using linear matrix inequalities (LMIs). Simulation results confirm the observer's effectiveness in sensorless SRM control. |
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Autotuning Gain based Backstepping Control Using Online Policy Iteration for PMSM |
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KwanKyun Byeon, Sesun You, Jiwon Seo, Wonhee KIM(Chung-Ang University, Korea) |
| Permanent magnet synchronous motors (PMSMs) are widely used to carry out the periodic motion of machines.
In manufacturing processes, it is important to achieve satisfactory control performance of the PMSMs for manufacturing efficiency and application safety.
This paper proposes an autotuning gain based backstepping control using online policy iteration for PMSMs..
The backstepping controller is designed for position tracking in the PMSMs.
The control gains are updated by the online policy iteration method in real time.
In the proposed method, stability is guaranteed during gain autotuning.
Furthermore, the gain-tuning time required to obtain the desired control performance is reduced. |
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