Extended State Observer Based Speed Control Scheme for PMSM Drives

Sonawane, Rakesh; Apte, Aishwarya

doi:10.1109/icacct.2018.8529646

Cited by 11 publications

(5 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where d is the desired value from the model, and y is the output value. For this application, the output of the neural model y can be defined using (18). According to the issues considered above, the adjustments of the gains in the analyzed controller are described with the following equations [56]:…”

Section: Scenario 1-partial Adaptation Of the Parameters Used In The ...mentioning

confidence: 99%

See 1 more Smart Citation

Speed Control Based on State Vector Applied for Electrical Drive with Elastic Connection

et al. 2022

View full text Add to dashboard Cite

The paper is focused on issues related to the control of electrical drives with oscillations of state variables. The main problem deals with the construction of the mechanical part, which contains elastic elements used as a coupling between the motor machine and the load. In such cases, strict tracking of the reference trajectory is difficult, so damping of the disturbances is necessary. For this purpose, the full state vector of the object is applied as the feedback signal for the speed controller. This method is efficient and relatively easy to implement (including the hardware part). However, the control accuracy is dependent on the quality of the parameters identification and the invariance of the object. Thus, two adaptive structures are proposed for the two-mass system. Moreover, selected coefficients were optimized using metaheuristic algorithms (symbiotic organism search and flower pollination algorithm). After presentation of the preliminaries and mathematical background, tests were conducted, and the numerical simulations are shown. Finally, the experimental verification for the 0.5 kW DC machines was performed. The results confirm the theoretical concept and the initial assumptions: the state controller leads to the precise control of the drive with a long shaft; recalculation of the parameters can improve the work of the drive under changes of time constants; modern design tools are appropriate for this application.

show abstract

Section: Scenario 1-partial Adaptation Of the Parameters Used In The ...mentioning

confidence: 99%

“…Although mathematical models of the variables can be used, their dependence on parameter uncertainties poses a significant problem [17]. In order to obtain a robust tool for the state variables calculation, state observers [18], the Luenberger observers [19], and the Kalman filters [20] are usually implemented.…”

Section: Introductionmentioning

confidence: 99%

Speed Control Based on State Vector Applied for Electrical Drive with Elastic Connection

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Namely, only the order of the system should be known. This outstanding feature makes ESO-based control methods more and more popular in recent years (Khankalantary and Sheikholeslam, 2020; Nie et al, 2019; Pawar et al, 2021; Sonawane and Apte, 2018; Song et al, 2022). In the study by Zhang et al (2020), an improved model free predictive current controller is proposed based on the ESO for a permanent magnet synchronous machine (PMSM) drives that does not require motor parameters and needs less tuning work and lower computational time.…”

Section: Introductionmentioning

confidence: 99%

Perturbation observer design based on extremum seeking control: An analytical insight

Taleshian

Noei

Sadati

et al. 2023

Transactions of the Institute of Measurement and Control

View full text Add to dashboard Cite

In this paper, an optimal extended state observer (ESO) is designed for nonlinear integral chain system. For the first time, in this paper, proportional–integral (PI) extremum seeking control (ESC; PIESC) approach is applied to design a perturbation observer by minimizing the estimation error. The PI type structure of the ESC provides fast transient response for the closed-loop system to attain optimum equilibrium point. A mathematical proof is presented to show that the average error dynamic asymptotically converges to zero while the estimation error is minimized. The simulation results verify that the estimation error achieved by the proposed PIESC-based ESO (PIESC-ESO) is found significantly less than that achieved by the classic ESO and PSO-based ESO. Moreover, if slow changes occur within the system or external to it, the PIESC-ESO is still able to modify the observer gains such that the estimation error is minimized again. Therefore, this may help PIESC-ESO to be used in practical applications.

show abstract

“…However, the buffeting problem affecting estimation accuracy could not be overcome. Sonawane and Apte [13] estimated rotor speed by using the state observer method, which was characterized by good stability and strong robustness. However, the algorithm was complex and requires an amount of computation.…”

Section: Introductionmentioning

confidence: 99%

Speed Sensorless Control of Hybrid Excitation Axial Field Flux-Switching Permanent-Magnet Machine Based on Model Reference Adaptive System

et al. 2020

View full text Add to dashboard Cite

A novel 6/13-pole hybrid excitation axial field flux-switching permanent magnet machine (HEAFFSPMM) exhibits strong fault tolerance capability, high efficiency, and large torque density. However, merely few research on speed sensorless control in HEAFFSPMM exists. The speed sensorless control methods based on model reference adaptive system (MRAS) are studied and compared for the machine to improve the stability and reliability of the system and consequently improve the application of machine in control system. Based on the field-oriented control strategy, the MRAS observer of speed is designed and built by applying stator currents, stator flux linkages, and simplified stator currents. The three speed sensorless control algorithms of MRAS are compared and analyzed by using MATLAB/Simulink simulation and dSPACE1104 experimental platform. Results show that the speed sensorless control algorithm based on simplified stator currents has good control performance and high control accuracy. INDEX TERMS Hybrid excitation, axial field flux-switching permanent magnet machine, simplified stator current, model reference adaptive system, and speed sensorless control. NOMENCLATURE u d , u q Stator voltage in d-q axis. u f Excitation voltage. i d , i q Stator current in d-q axis. i f Excitation current. L d , L q Stator inductance in d-q axis. L f Excitation inductance. R s Stator resistance. R f Excitation resistance. T e Electromagnetic torque. T eMAX Maximum value of torque. T eMIN Minimum value of torque. δ Torque ripple. ψ m Flux linkage produced by permanent magnets. ψ d , ψ q d, q-axis component of the stator flux. ω e Electric angular velocity. The associate editor coordinating the review of this manuscript and approving it for publication was Xiaodong Sun .

show abstract

Extended State Observer Based Speed Control Scheme for PMSM Drives

Cited by 11 publications

References 9 publications

Speed Control Based on State Vector Applied for Electrical Drive with Elastic Connection

Speed Control Based on State Vector Applied for Electrical Drive with Elastic Connection

Perturbation observer design based on extremum seeking control: An analytical insight

Speed Sensorless Control of Hybrid Excitation Axial Field Flux-Switching Permanent-Magnet Machine Based on Model Reference Adaptive System

Contact Info

Product

Resources

About