Finite Control Set-Model Predictive Speed Control for Induction Motors with Optimal Duration

Ahmed, Abdelsalam A.; Koh, Byung Kwon; Kim, Jung-Su; Lee, Youngil

doi:10.1016/j.ifacol.2017.08.1056

Cited by 9 publications

(6 citation statements)

References 11 publications

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“…To maximize the developed T e , which is related with i q 1 so that i d 1 , i d 3 , and i q 3 are imposed to 0, the hysteresis controller regulates the generator current with its reference. The speed control concept in details is shown in Figure .…”

Section: Machine Side Convertermentioning

confidence: 99%

“…In this paper, the MPC is employed to track the rotor speed with its reference that is estimated from the MPPT. Using Euler approximation, Equation is rewritten as follows:

ω_{m} ((), k + 1) = ((), 1 - \frac{f T_{s}}{J}) ω_{m} ((), k) + \frac{T_{s}}{J} ((), T_{m} ((), k) - T_{e} ((), k)),

where T s is the sampling time, then the cost function will be

J_{ω} = e_{ω} {(([]|, k + 1, k))}^{T} W e_{ω} ((), [k + 1| k]),

where e ω ([ k + 1| k ] is one‐step state error prediction and W is positive weighting matrix.

e_{ω} ((), [k + 1| k]) = ω_{ref} - ω_{m} ([], k + 1)

…”

Section: Speed Control Loopmentioning

confidence: 99%

See 1 more Smart Citation

Model predictive speed control of five‐phase permanent magnet synchronous generator‐based wind generation system via wind‐speed estimation

Mousa

Youssef

Mohamed

2019

Int Trans Electr Energ Syst

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Summary Accurate wind‐speed measure along with an effective control technology is an important aspect to attain optimal wind power. This paper proposes a sensorless maximum power point tracking (MPPT) algorithm that estimates the effective wind speed without an anemometer to reduce wind‐turbine installation cost and improve the overall efficiency. This algorithm depends on the aerodynamic torque power coefficient approximation to the third‐order polynomial. This paper investigates different control schemes of a 1.5‐MW grid‐tied five‐phase permanent magnet synchronous generator (PMSG) based, a variable‐speed wind‐energy conversion system (VS‐WECS). To eradicate the limitations of the proportional‐integral (PI) controller as a speed controller, model predictive controller (MPC) is implemented as a replacement of PI controller. The MPC is employed to track the rotor speed to the optimal speed. Both the PI and the MPC are designed and deliberated to satisfy the obedient performance of the speed control loop. Moreover, a comparative study of speed control schemes is performed between the conventional PI controller and the MPC. Performance of the proposed control schemes is validated using the MATLAB/SIMULINK. Simulation results show the superiority of MPC compared with the conventional PI controller and the validity of the MPC as a vital solution for drawbacks of the PI controller.

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Section: Machine Side Convertermentioning

confidence: 99%

“…In this paper, the MPC is employed to track the rotor speed with its reference that is estimated from the MPPT. Using Euler approximation, Equation is rewritten as follows:

ω_{m} ((), k + 1) = ((), 1 - \frac{f T_{s}}{J}) ω_{m} ((), k) + \frac{T_{s}}{J} ((), T_{m} ((), k) - T_{e} ((), k)),

where T s is the sampling time, then the cost function will be

J_{ω} = e_{ω} {(([]|, k + 1, k))}^{T} W e_{ω} ((), [k + 1| k]),

where e ω ([ k + 1| k ] is one‐step state error prediction and W is positive weighting matrix.

e_{ω} ((), [k + 1| k]) = ω_{ref} - ω_{m} ([], k + 1)

…”

Section: Speed Control Loopmentioning

confidence: 99%

Model predictive speed control of five‐phase permanent magnet synchronous generator‐based wind generation system via wind‐speed estimation

Mousa

Youssef

Mohamed

2019

Int Trans Electr Energ Syst

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“…In this section, the detailed procedures for deriving the torque equation including the iron loss are presented. In the rotor FOC, the torque equation is given by (13). From (7) and writing i md in terms of i iq , we have…”

Section: Acknowledgmentmentioning

confidence: 99%

“…The results clarified that the temperature variations have a negligible effect on the reference stator current magnitude; however, it significantly varies the reference slip speed. In [13], a predictive MTPA strategy is proposed based on direct torque and flux control and without considering iron loss. The effectiveness of this strategy is limited to high torque and high speed applications.…”

Section: Introductionmentioning

confidence: 99%

Online maximum torque per ampere control for induction motor drives considering iron loss using input–output feedback linearisation

Hesar

Zarchi

Khoshhava

2019

IET Electric Power Applications

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This study presents a novel online, accurate and simple model-based maximum torque per ampere (MTPA) strategy for input-output feedback linearisation control of induction motor (IM) drives. Despite conventional MTPA control principles which are under the assumption of iron loss neglecting, the proposed strategy takes iron loss effect into account. This study highlights the iron loss influence on MTPA scheme. Firstly, the cross-coupling effects in the IM model and torque non-linearity due to the iron loss in torque-speed characteristics of the IM are discussed. The criterion for the MTPA scheme is then introduced and investigated by gradient approach so that when the gradient vectors of the torque and stator current magnitude are parallel, the MTPA strategy is satisfied. Finally, to confirm the validity of the proposed control scheme, experiments are carried out.

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“…Previously, MPC methods were limited to the slow processing applications due to the requirement of high processing capacity. Now, with the availability of low cost high capacity processors, the MPC can be applied in fast processing applications like AC motor drives applications [22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Analysis and investigation of different advanced control strategies for high-performance induction motor drives

et al. 2020

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Induction motor (IM) drives have received a strong interest from researchers and industry particularly for high-performance AC drives through vector control method. With the advancement in power electronics and digital signal processing (DSP), high capability processors allow the implementation of advanced control techniques for motor drives such as model predictive control (MPC). In this paper, design, analysis and investigation of two different MPC techniques applied to IM drives; the model predictive torque control (MPTC) and model predictive current control (MPCC) are presented. The two techniques are designed in Matlab/Simulink environment and compared in term of operation in different operating conditions. Moreover, a comparison of these techniques with field-oriented control (FOC) and direct torque control (DTC) is conducted based on simulation studies with PI speed controller for all control techniques. Based on the analysis, the MPC techniques demonstrates a better result compared with the FOC and DTC in terms of speed, torque and current responses in transient and steady-state conditions.

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Finite Control Set-Model Predictive Speed Control for Induction Motors with Optimal Duration

Cited by 9 publications

References 11 publications

Model predictive speed control of five‐phase permanent magnet synchronous generator‐based wind generation system via wind‐speed estimation

Model predictive speed control of five‐phase permanent magnet synchronous generator‐based wind generation system via wind‐speed estimation

Online maximum torque per ampere control for induction motor drives considering iron loss using input–output feedback linearisation

Analysis and investigation of different advanced control strategies for high-performance induction motor drives

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