Recurrent Neural Network-Based Robust Adaptive Model Predictive Speed Control for PMSM With Parameter Mismatch

Nguyen, Ty Trung; Tran, Hoang Ngoc; Nguyen, Ton Hoang; Jeon, Jae Wook

doi:10.1109/tie.2022.3198255

Cited by 27 publications

(13 citation statements)

References 36 publications

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“…5(a). The e 0 and e 1 are small at the end of region I, but the large gain (c 0 , c 1 ), and the large value of ė0 in the term (c 0 + c 1 ) ė0 , which is contained in (18), will continue to produce a large control signal x ref 2 in region II, as shown in Fig. 6(d).…”

Section: Adaptive Backstepping Sliding Mode Controlmentioning

confidence: 97%

“…As mentioned previously, the proposed BSMC contains convergence gains c 0 and c 1 for calculating the virtual control inputs x ref 2 as (18). Based on experiments, c 0 was selected to equal c 1 to obtain a reliable control performance.…”

Section: Adaptive Backstepping Sliding Mode Controlmentioning

confidence: 99%

“…Because of the large changes in the step profile, excessively large errors (e 0 and e 1 ) occur. These errors will be multiplied with large constant gains (c 0 and c 1 ), leading to a large control signal x ref 2 as described in (18). Due to limitations in the physical system, the current is always constrained within specific range values.…”

Section: Adaptive Backstepping Sliding Mode Controlmentioning

confidence: 99%

“…A method is therefore needed to address the drawbacks of conventional linear controllers and maintain high dynamic performance of the motor drive. Several nonlinear techniques have been developed to improve the control performance of motor systems, including backstepping control [5]- [7], adaptive control [8], [9], fuzzy-logic control [10], [11], sliding mode control (SMC) [12]- [17], and model predictive control [18]- [20].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

An Adaptive Backstepping Sliding-Mode Control for Improving Position Tracking of a Permanent-Magnet Synchronous Motor With a Nonlinear Disturbance Observer

Nguyen

et al. 2023

IEEE Access

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To provide reliable position control for a permanent-magnet synchronous motor (PMSM) under conditions of lumped disturbances such as external load torque fluctuation and system parameter variation, an adaptive backstepping sliding-mode control (ABSMC) with a nonlinear disturbance observer (NDO) is proposed. An ABSMC is a non-cascade technique that employs a position-current single-loop control structure rather than a conventional cascade control structure for vector control of the PMSM. This method uses Lyapunov theory to design a control law to ensure the motor position reaches a desired value in a finite period of time and consequently achieves a rapid transient response. The proposed ABSMC incorporates an adaptive convergence gain to avoid a large overshoot under point-to-point position command. The NDO with a nonlinear observer gain is proposed to estimate unknown disturbances and provide feed-forward compensation for the ABSMC, improving robustness and reducing steady-state position error. The proposed methods are applied to an industrial motor drive to confirm their validity in real-world operating environments.INDEX TERMS Permanent magnet synchronous motor, position tracking, adaptive backstepping sliding mode control, nonlinear disturbance observer, disturbance.

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Section: Adaptive Backstepping Sliding Mode Controlmentioning

confidence: 97%

Section: Adaptive Backstepping Sliding Mode Controlmentioning

confidence: 99%

Section: Adaptive Backstepping Sliding Mode Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Adaptive Backstepping Sliding-Mode Control for Improving Position Tracking of a Permanent-Magnet Synchronous Motor With a Nonlinear Disturbance Observer

Nguyen

et al. 2023

IEEE Access

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“…In this case, many advanced theories are used to research the performance improvement of PMSM control system. Some well known methods such as robust control, 5 adaptive control, 6 sliding mode control (SMC), [7][8][9] and intelligent control, [10][11][12][13] etc. Among these methods, SMC has been widely studied and applied in PMSM control system because of its strong robustness and easy realization.…”

Section: Introductionmentioning

confidence: 99%

A novel sliding mode control with MRAS inertia identification for permanent magnet synchronous motors

Song,

Xiao,

Yang

et al. 2023

Measurement and Control

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To enhance the anti-inertia disturbance ability of permanent magnet synchronous motor (PMSM) speed system, an adaptive sliding mode control with inertia identification is proposed. A novel sliding mode control (NSMC) based on a new reaching law coupled with model reference adaptive system (MRAS) inertia identification is realized the adaptive control, named MRAS+NSMC. In the NSMC construct process, an integral sliding mode surface and a variable speed reaching law are introduced to avoid speed differentiation and improve dynamics, respectively. And the new reaching law imported a successive sigmoid( s) to replace the traditional sign( s) to suppress chattering phenomena. For the problem that the performance deteriorated by rotational inertia variation caused by load changes, the inertia is estimated in real time according to the MRAS theory, and the identification value is updated to the NSMC controller to realize adaptive MRAS+NSMC speed control. Experimental results show that the proposed adaptive MRAS+NSMC control has a faster speed response, and the speed response time is reduced from 85 to 49 ms compared with conventional SMC control. In addition, it has strong robustness to inertia disturbances and high speed tracking accuracy. Compared with conventional SMC, the speed tracking accuracy of proposed MRAS+NSMC is increased from 12% to 4%. This makes the proposed MRAS+NSMC control has great potential practical significance for speed control of PMSM.

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High precision tracking control for linear servo system based on intelligent second-order complementary sliding mode

Jin,

Gong,

Zhao

2023

Electr Eng

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Recurrent Neural Network-Based Robust Adaptive Model Predictive Speed Control for PMSM With Parameter Mismatch

Cited by 27 publications

References 36 publications

An Adaptive Backstepping Sliding-Mode Control for Improving Position Tracking of a Permanent-Magnet Synchronous Motor With a Nonlinear Disturbance Observer

An Adaptive Backstepping Sliding-Mode Control for Improving Position Tracking of a Permanent-Magnet Synchronous Motor With a Nonlinear Disturbance Observer

A novel sliding mode control with MRAS inertia identification for permanent magnet synchronous motors

High precision tracking control for linear servo system based on intelligent second-order complementary sliding mode

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