Optimal control strategy of state feedback control for surface-mounted PMSM drives based on auto-tuning of seeker optimization algorithm

This paper focus on a state feedback controller (SFC)-based optimal control scheme for surface-mounted permanent-magnet synchronous motor (SPMSM) with auto-tuning of controller built on seeker optimization algorithm (SOA). First, based on the nonlinear state-space model of SPMSM, voltage feedforward...

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Bibliographic Details
Published inInternational journal of applied electromagnetics and mechanics Vol. 66; no. 4; pp. 705 - 725
Main Authors Cao, Junhao, Sun, Xiaodong, Tian, Xiang
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.08.2021
Sage Publications Ltd
Subjects
Algorithms
Compensation
Control systems
Decoupling
Disturbance observers
Equations of state
Feedback control
Optimal control
Optimization
Optimization algorithms
Permanent magnets
Rotor speed
State feedback
State space models
Synchronous motors
Torque
Tuning
feedforward compensation
state feedback control
disturbance observer
seeker optimization algorithm (SOA)
Surface-mounted permanent magnet synchronous motor (SPMSM)
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Summary:This paper focus on a state feedback controller (SFC)-based optimal control scheme for surface-mounted permanent-magnet synchronous motor (SPMSM) with auto-tuning of controller built on seeker optimization algorithm (SOA). First, based on the nonlinear state-space model of SPMSM, voltage feedforward compensation is used to design a linear SFC. Then in order to guarantee the steady performance in speed and current, integral models considering the errors of rotor speed and current response in d-axis are added in the state space model of SPMSM. Furthermore, by statically decoupling the load torque in the state equation, feedforward compensation is implemented on the load torque to improve the dynamic performance of the controller. The load torque is estimated by using disturbance observer with reasonable parameter selection. Then, with the consideration of the search capacity of seeker optimization algorithm (SOA), it is adopted to acquire matrix coefficient of the presented controller. Furthermore, in order to suppress the speed overshoot, a penalty term is introduced to the fitness index. The performance of the proposed method has been validated experimentally and compared with the conventional method under different conditions.
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ISSN:1383-5416
1875-8800
DOI:10.3233/JAE-201630