Model Predictive Control of a Direct Current Motor Utilizing Lookup Tables

Anuchin, Alecksey; Bogdanov, Andrei; Demidova, Galina L.; Savkin, Dmitrii; Fedorova, Ksenya; Gulyaeva, Maria

doi:10.1109/icepds47235.2020.9249336

Cited by 5 publications

(4 citation statements)

References 9 publications

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“…To prove the stability, which represents the dynamic the equation of the error in the ultimate closed-loop system, we can express the Lyapunov function from the equation ( 7) and its derivative from the equation (8)…”

Section: -4-proof Of System Stability By Applying Mpsmc Controllermentioning

confidence: 99%

“…This allows MPC to take into account both the current and future states of the system and adjust control inputs accordingly. Anuchin et al [8] proposed the continuous control set MPC strategy for DC motors to address the issue of unpredictable noise and switching rate encountered with finite control set MPCs. Model Predictive Sliding Mode Control (MPSMC) is a type of control strategy that combines the predictive capabilities of MPC with the robustness of SMC [9].…”

Section: -Introductionmentioning

confidence: 99%

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Model Predictive Sliding Mode Control of Direct Current Motors

Eghbal,

Seyedeh-Solmaz

2024

Preprint

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In this paper, a cascade controller is designed for controlling the speed of a direct current motor, which includes a combination of a model predictive controller and a sliding mode controller. The main goal is to precisely control the speed and angle of the motor shaft by adjusting the input voltage, taking into account the voltage limitations. We design a model predictive sliding mode controller in such a way that in the inner loop, the model predictive controller controls the voltage to follow the reference current, and in the outer loop, the sliding mode controller generates the reference current to follow the desired speed. The sliding mode controller, with its resistance to external disturbances, reduces their effects and the uncertainties of modeling. By extracting the reference current based on the speed tracking error and the presence of uncertainty, the optimal terminal voltage of the motor is predicted in the inner loop, leading to the tracking of the desired rotational speed by the motor. This paper also proves the stability of the system in the presence of the motor terminal input voltage constraint, and the simulation results confirm the effectiveness of the proposed controller in dealing with uncertainty and external disturbances.

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Section: -4-proof Of System Stability By Applying Mpsmc Controllermentioning

confidence: 99%

Section: -Introductionmentioning

confidence: 99%

Model Predictive Sliding Mode Control of Direct Current Motors

Eghbal,

Seyedeh-Solmaz

2024

Preprint

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“…Yet, given the nonlinear inductance of the SRM, directly estimating the current requires first addressing its nonlinearity. One way to tackle this challenge is the predictive current control method using the lookup table technique [91,92].…”

Section: Predictive Modelmentioning

confidence: 99%

A Review on Predictive Control Technology for Switched Reluctance Motor System

Zhu

Yao

Sun

2023

WEVJ

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The significance of employing control strategies on a switched reluctance motor (SRM) is that they can reduce vibration noise and torque ripple. With the rapid development of digital system processors, predictive control (PC), as a modern control approach, is increasingly applied to enhance the dynamic performance and operational efficiency of SRMs. This review provides a comprehensive overview of the current state of research on PC strategies of SRMs and classifies PC technologies, such as generalized predictive control (GPC), hysteresis predictive control (HPC), deadbeat predictive control (DPC), and model predictive control (MPC). It summarizes the PC schemes from the aspects of predictive current control (PCC), predictive torque control (PTC), and other PC, and it discusses the current trends in technology development, as well as potential research directions. The insights presented herein aim to facilitate further investigations into predictive control techniques for SRM.

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“…e use of electric drives makes the industrial process more robust and reliable and reduces the cost of operation [1,2]. is is because the industrial drive requires less electronic components while providing greater exibility, which makes the system more reliable and adaptable to the adverse situation that occurs in industrial drives [3,4].…”

Section: Introductionmentioning

confidence: 99%

Direct Torque Control of Induction Motor Using ConvLSTM Based on Gaussian Pillbox Surface

Potturi

Reddy

Dash

et al. 2022

Mathematical Problems in Engineering

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This article introduces long short-term memory (LSTM)-enabled direct torque control (DTC) for induction motor under a wide range of operation. Low-power applications of industrial drives are more as compared to high-power applications. The main objective of this paper is to address high torque, poor dynamic response, and flux ripple problems observed in low-power induction motor drives. The voltage selector switching table is replaced by LSTM encoder and embedding layer with hysteresis comparator. This will ensure robust control against induction motor disturbances and at the same time will enhance the stator flux trajectory prediction for DTC. Most of the studies describe DTC at a higher speed. In this article, the DTC has been applied to lower speed IM, typically in the range of 100 RPM. Different LSTM models have also been presented in terms of response time. A detailed comparative analysis between LSTM and fuzzy and ANFIS-based DTC has been carried out using MATLAB/Simulink model. The performance has been evaluated under steady and transient conditions as well.

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Model Predictive Control of a Direct Current Motor Utilizing Lookup Tables

Cited by 5 publications

References 9 publications

Model Predictive Sliding Mode Control of Direct Current Motors

Model Predictive Sliding Mode Control of Direct Current Motors

A Review on Predictive Control Technology for Switched Reluctance Motor System

Direct Torque Control of Induction Motor Using ConvLSTM Based on Gaussian Pillbox Surface

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