2020
DOI: 10.1049/iet-cta.2018.5821
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Non‐linear‐disturbance‐observer‐enhanced MPC for motion control systems with multiple disturbances

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Cited by 28 publications
(15 citation statements)
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“…3) 4) To select the optimal combination of voltage vectors V Copt , a cost function g 1 ( 30) is first used to pre-select three combinations of voltage vectors, i.e., V Cs 1 ,V Cs 2 , V Cs 3 , which can provide the most powerful capability on dynamic response enhancement. 5) The optimal combination of voltage vectors V Copt out of three combinations of voltage vectors is then further determined by the second cost function g 2 (33) for speed and flux control. At this step, the optimal combination of voltage vectors V Copt is saved in the register waiting to be applied to PMSM, as well as to be used to conduct system status prediction on next control period.…”
Section: Overall Control Diagrammentioning
confidence: 99%
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“…3) 4) To select the optimal combination of voltage vectors V Copt , a cost function g 1 ( 30) is first used to pre-select three combinations of voltage vectors, i.e., V Cs 1 ,V Cs 2 , V Cs 3 , which can provide the most powerful capability on dynamic response enhancement. 5) The optimal combination of voltage vectors V Copt out of three combinations of voltage vectors is then further determined by the second cost function g 2 (33) for speed and flux control. At this step, the optimal combination of voltage vectors V Copt is saved in the register waiting to be applied to PMSM, as well as to be used to conduct system status prediction on next control period.…”
Section: Overall Control Diagrammentioning
confidence: 99%
“…Moreover, parameter variations and measurement error effects would deteriorate the control performance in a practical control system. To deal with the adverse effect of these disturbances, observers are introduced to estimate various disturbances, and an enhanced control algorithm with disturbance compensations can be developed accordingly [32], [33]. It has been proven that the employment of observers contributes to develop a robust controller [34].…”
Section: Introductionmentioning
confidence: 99%
“…It is widely known that the proportional-integral-derivative (PID) control approach is the most widely used in the industrial field, because of its simple implementation and clear physical meaning in control engineering [1]. However, in actual applications, the PMSM servo system is unavoidably faced with various uncertainties and disturbances [2,3]. The traditional feedback control method may find it difficult to provide good tracking performance and disturbance rejection performance simultaneously [4].…”
Section: Introductionmentioning
confidence: 99%
“…So developing effective control methods to achieve excellent speed control performance has gradually become a significant issue for PMSMs in the past few decades (Meng et al , 2019; Wang et al , 2019). Nowadays, a variety of advanced control strategies have been applied to PMSMs, such as sliding mode control (SMC) (Fang et al , 2020; Huang et al , 2019; Wang et al , 2017), H-infinity control (Hans and Ghosh, 2020), model predictive control (MPC) (Li et al , 2020; Wang et al , 2020; Yan et al , 2019), neural network control (NNC) (Cheng and Chen, 2020), active disturbance rejection control (ADRC) (Liu et al , 2019; Mei and Yu, 2020) and so on, which not only improve the dynamic and steady state performances of the PMSMs but also enrich the control methods of the PMSMs.…”
Section: Introductionmentioning
confidence: 99%