Robust Model-Free Fault-Tolerant Predictive Control for PMSM Drive System

Cheng, Shu; Zhou, Ruirui; Li, Zhuoxin; Xi, Zhen; Zhao, Jundong; Zhao, Kaihui; Xiang, Chaoqun

doi:10.1109/access.2024.3351509

Cited by 3 publications

(1 citation statement)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, a two-level, three-phase inverter that controls a three-phase motor only produces eight switching states. Thus, FCS-MPC estimates the switching state that allows getting the desired future response of the plant [6,7]. Generalized Predictive Control (GPC) is another predictive control approach, which is based on an augmented prediction model and an optimization process that allows calculating a set of future control actions that reduces the future errors [8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Variable Frequency Resonant Controller Based on Generalized Predictive Control for Biased-Sinusoidal Reference Tracking and Multi-Layer Perceptron

Cordero,

Gonzales,

Estrabis

et al. 2024

Energies

View full text Add to dashboard Cite

Resonant controllers are widely used in power electronics to track sinusoidal references. According to the internal model principle (IMP), these controllers should embed the poles of the Laplace or Z transform of the reference for the closed-loop system to track the reference asymptotically. Thus, tracking a sinusoidal reference is difficult as the controller should adapt its structure to embed the poles of the sinusoidal reference with variable frequency, as those poles depend on that variable frequency. On the other hand, Generalized Predictive Control (GPC) is widespread in industry applications due to its fast response, robustness and capability to include constraints. Resonant controllers based on GPC, which satisfy IMP, have been developed. However, these controllers consider the sinusoidal frequency to be constant. This paper presents a new GPC-based resonant controller with an adaptive and simple control law to track references with variable frequencies. A PLL estimates the frequency of the reference. A multi-layer perceptron uses the estimated frequency to define the gain matrix required to calculate the GPC control action. The GPC control action and the estimated frequency define the control law, which satisfies IMP in steady-state conditions. The authors did not find in the literature the proposed mathematical development of an adaptive GPC resonant controller with a discrete-time augmented model whose control law satisfies IMP. Thus, the proposed approach is helpful to develop other adaptive predictive controllers. Experimental results show that the proposed controller can track sinusoidal references whose frequencies vary in time.

show abstract

Section: Introductionmentioning

confidence: 99%

Variable Frequency Resonant Controller Based on Generalized Predictive Control for Biased-Sinusoidal Reference Tracking and Multi-Layer Perceptron

Cordero,

Gonzales,

Estrabis

et al. 2024

Energies

View full text Add to dashboard Cite

show abstract

Model-free three-vector predictive current control of permanent magnet synchronous motor based on improved sliding mode observer

Huang,

Zhang,

Tian

2024

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

To address the complexity of vector selection in the conventional predictive current control strategy and the reduction of control system robustness when the motor parameters change, this paper proposes a finite-set model-free three-vector predictive current control method for permanent magnet synchronous motor based on the improved sliding-mode perturbation observer. According to the mathematical model of a permanent magnet synchronous motor under perturbation, a new hyperlocal model is established, and the conventional vector traversal optimization method is optimized to obtain the necessary basic voltage vector by analyzing the function with one judgment. Meanwhile, the sliding mode perturbation observer is designed using the fast exponential convergence law to observe the unknown part. Finally, by experimentally contrasting the proposed technique with the conventional three-vector model predictive current control, the method suggested in this paper can successfully reduce the current pulsation and inhibit the system perturbation caused by the parameter change, ensuring the steady state performance of the motor, as demonstrated by the experimental comparison with the conventional three-vector model predictive current control method.

show abstract