Nonlinear control of a permanent magnet synchronous motor with disturbance torque estimation

Solsona, J.; Valla, M.I.; Muravchik, Carlos H.

doi:10.1109/60.866994

Cited by 154 publications

(59 citation statements)

References 10 publications

(15 reference statements)

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“…In most of the previous speed control methods, z 1 (t), z 2 (t), and z 3 (t), and their time derivatives are commonly ignored and the nominal values of the system parameters (k 1 , k 2 ,..., k 6 ) are used to construct the feedforward control term regardless of these system uncertainties [4], [5], [8], [9], and [13]. However, when the system parameters change during the operation of the drive system, the system parameters used in these controllers are mismatched with their actual values.…”

Section: A Error Dynamic Modelmentioning

confidence: 99%

“…Consequently, the system parameter variations can strongly affect the control performance of these conventional schemes. Moreover, most of the previous methods require an assumption that the time derivative of the load torque is equal to zero [4]- [6], [8]- [11], and [13]. Therefore, these two problems limit the accuracy of the speed regulator.…”

Section: A Error Dynamic Modelmentioning

confidence: 99%

“…First, the feedback control term is designed to make the system dynamics stable. Many researchers are interested in applying the feedback control term into well-known design techniques such as the sliding mode controller [4], [5], feedback linearization controller (FLC) [6], [7], fuzzy logic controller [8], [9], state-dependent Riccati equation controller [10], [11], linear matrix inequality (LMI) controller [12], [13], etc. Meanwhile, the feedforward control term is the main and common term of these controllers, which is employed to compensate for the nonlinear coupling factors using nominal parameters.…”

Section: Introductionmentioning

confidence: 99%

“…This can have a strong influence on the control performance of these conventional schemes. Another limitation is that, these control methods [4]- [6], [8]- [11], and [13] also need an assumption that the time derivative of the load torque is equal to zero. This may lead to a slow transient behavior of the load torque observer.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Sliding Mode Control of SPMSM Drivers: An Online Gain Tuning Approach with Unknown System Parameters

Jung¹,

Leu²,

Dang³

et al. 2014

Journal of Power Electronics

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This paper proposes an online gain tuning algorithm for a robust sliding mode speed controller of surface-mounted permanent magnet synchronous motor (SPMSM) drives. The proposed controller is constructed by a fuzzy neural network control (FNNC) term and a sliding mode control (SMC) term. Based on a fuzzy neural network, the first term is designed to approximate the nonlinear factors while the second term is used to stabilize the system dynamics by employing an online tuning rule. Therefore, unlike conventional speed controllers, the proposed control scheme does not require any knowledge of the system parameters. As a result, it is very robust to system parameter variations. The stability evaluation of the proposed control system is fully described based on the Lyapunov theory and related lemmas. For comparison purposes, a conventional sliding mode control (SMC) scheme is also tested under the same conditions as the proposed control method. It can be seen from the experimental results that the proposed SMC scheme exhibits better control performance (i.e., faster and more robust dynamic behavior, and a smaller steady-state error) than the conventional SMC method.

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Section: A Error Dynamic Modelmentioning

confidence: 99%

Section: A Error Dynamic Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sliding Mode Control of SPMSM Drivers: An Online Gain Tuning Approach with Unknown System Parameters

Jung¹,

Leu²,

Dang³

et al. 2014

Journal of Power Electronics

View full text Add to dashboard Cite

show abstract

“…To guarantee a fast transient response and an excellent trajectory tracking capability, various nonlinear control methods such as [4]- [13] have been reported. These methods include robust control [4], disturbance observer based control [5]- [7], adaptive control [8]- [9], nonlinear feedback linearization [10]- [11], and neural network control [12], [13]. However, most of the previous control algorithms have been established on the assumption that knowledge of the PMSM parameters is available.…”

Section: Introductionmentioning

confidence: 99%

Implementation of a Robust Fuzzy Adaptive Speed Tracking Control System for Permanent Magnet Synchronous Motors

Jung¹,

Choi²,

Lee

2012

Journal of Power Electronics

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This paper presents a fuzzy adaptive speed controller that guarantees a fast dynamic behavior and a precise trajectory tracking capability for surfaced-mounted permanent magnet synchronous motors (SPMSMs). The proposed fuzzy adaptive control strategy is simple and easy to implement. In addition, the proposed speed controller is very robust to system parameter and load torque variations because it does not require any accurate parameter values. The global stability of the proposed control system is analytically verified. To evaluate the proposed fuzzy adaptive speed controller, both simulation and experimental results are shown under motor parameter and load torque variations on a prototype SPMSM drive system.

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Sensorless vector control of permanent magnetic synchronous motor with parameter error compensation

Pak

Kang

2021

Int Trans Electr Energ Syst

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The position sensorless vector control of permanent magnetic synchronous motor is the method that implements the vector control by estimating the rotor position from the motor model in the basis of the voltage and the current signal of the motor without measuring the motor position directly. The sensorless vector control is divided into two methods: estimating the rotor position based on the stationary reference frame and rotational reference frame. This article presents the research results of more improved estimation performance by combining these two methods. First, we estimate the rotor position by using the open-loop estimation algorithm based on the stationary reference frame, evaluate the estimation error based on the model from the rotational reference frame and compensate the estimate in a feedback way with differences from the current measurements. At the same time, we also take the parameter errors included in the model into account. This article performed the experiment for the parameter identification and for the sensorless vector control, and demonstrated its effectiveness.

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Nonlinear control of a permanent magnet synchronous motor with disturbance torque estimation

Cited by 154 publications

References 10 publications

Sliding Mode Control of SPMSM Drivers: An Online Gain Tuning Approach with Unknown System Parameters

Sliding Mode Control of SPMSM Drivers: An Online Gain Tuning Approach with Unknown System Parameters

Implementation of a Robust Fuzzy Adaptive Speed Tracking Control System for Permanent Magnet Synchronous Motors

Sensorless vector control of permanent magnetic synchronous motor with parameter error compensation

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