Cascaded Robust Fault-Tolerant Predictive Control for PMSM Drives

This paper proposes a robust nonlinear predictive current control (RNPCC) method for permanent magnet synchronous motor (PMSM) drives, which can optimize the current control loop performance of the PMSM system with model parameter perturbation. First, the disturbance caused by parameter perturbation was considered in the modeling of PMSM. Based on this model, the influence of parameter perturbation on the conventional predictive current control (PCC) was analyzed. The composite integral terminal sliding mode observer (SMO) was then designed to estimate the disturbance caused by the parameter perturbation in real time. Finally, a RNPCC method is developed without relying on the mathematical model of PMSM, which can effectively eliminate the influence of parameter perturbation by injecting the estimated disturbance value. Simulations and experiments verified that the proposed RNPCC method was able to remove the current error caused by the parameter perturbation during steady state operation.

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“…The voltage equations of the PMSM in a synchronous rotating reference frame are written as in [10,21]:…”

Section: Machine Model Descriptionmentioning

confidence: 99%

Robust Nonlinear Predictive Current Control Techniques for PMSM

Lyu

Luo

et al. 2019

Energies

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“…In [24], a robust nonlinear predictive current control algorithm was developed for PM synchronous motor drives, which can optimize the current control loop performance under model parameter perturbation. In [25], a cascaded robust fault-tolerant predictive control strategy based on integral terminal sliding mode observer was presented for PM synchronous motor drives, which can obtain high performance speed loop and current loop. In [22][23][24][25], the predictive control method was aimed at three-phase PM synchronous motor, which can obtain perfect control performance.…”

Section: Introductionmentioning

confidence: 99%

“…In [25], a cascaded robust fault-tolerant predictive control strategy based on integral terminal sliding mode observer was presented for PM synchronous motor drives, which can obtain high performance speed loop and current loop. In [22][23][24][25], the predictive control method was aimed at three-phase PM synchronous motor, which can obtain perfect control performance. However, there are essential differences between N*3-phase PM energy storage motor and conventional three-phase PM synchronous motor.…”

Section: Introductionmentioning

confidence: 99%

Predictive Power Control of Novel N*3-phase PM Energy Storage Motor for Urban Rail Transit

Zhang

Rao

et al. 2020

Energies

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High power density energy storage permanent magnet (PM) motor is an important energy storage module in flywheel energy storage system for urban rail transit. To expand the application of the PM motor in the field of urban rail transit, a predictive power control (PPC) strategy for the N*3-phase PM energy storage motor is proposed in this paper. Firstly, the output characteristics of the N*3-phase PM energy storage motor are analyzed by using the finite element method, and the mathematical model of the N*3-phase PM energy storage motor is established. Then, the topological structure and operation principle of N*3-phase PM energy storage motor system is illustrated. Furthermore, the N*3-phase PM energy storage motor system driven by six parallel voltage source inverters (VSIs) is proposed to generate the required power. Finally, a novel predictive direct power control method is developed for the N*3-phase PM energy storage motor. The feasibility and effectively of the proposed PPC method are verified by experiment and simulation. Comprehensive simulation and experimental results both show that the proposed PPC method can obtain the lower torque/stator flux ripple, smaller values of THD of stator winding currents, and zero error tracking of stator winding flux.

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“…With the development of microprocessors, such as digital signal processors (DSPs) and field programmable gate arrays (FPGAs), the MPC method has been applied to PMSM control systems with a very short sampling period [15]. Given these advantages, some scholars have successfully employed the MPC method in PMSM control systems [16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM

Shao

Deng

et al. 2019

Energies

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This paper reports on the optimal speed control problem in permanent magnet synchronous motor (PMSM) systems. To improve the speed control performance of a PMSM system, a model predictive control (MPC) method is incorporated into the control design of the speed loop. The control performance of the conventional MPC for PMSM systems is destroyed because of system disturbances such as parameter mismatches and external disturbances. To implement the MPC method in practical applications and to improve its robustness, a compensated scheme with an extended sliding mode observer (ESMO) is proposed in this paper. Firstly, for observing if and when the system model is mismatched, the ESMO is regarded as an extended sliding mode parameter observer (ESMPO) to identify the main mechanical parameters. The accurately obtained mechanical parameters are then updated into the MPC model. In addition, to overcome the influence of external load disturbances on the system, the observer is regarded as an extended sliding mode disturbance observer (ESMDO) to observe the unknown disturbances and provide a feed-forward compensation item based on the estimated disturbances to the model predictive speed controller. The simulation and experimental results show that the proposed ESMO can accurately observe the mechanical parameters of the system. Moreover, the optimized MPC improves the dynamic response behavior and exhibits a satisfactory disturbance rejection performance.

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Cascaded Robust Fault-Tolerant Predictive Control for PMSM Drives

Cited by 16 publications

References 27 publications

Robust Nonlinear Predictive Current Control Techniques for PMSM

Robust Nonlinear Predictive Current Control Techniques for PMSM

Predictive Power Control of Novel N*3-phase PM Energy Storage Motor for Urban Rail Transit

Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM

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