Adaptive LADRC Parameter Optimization in Magnetic Levitation

Ouyang, Qinghua; Fan, Kuangang; Liu, Yahui; Li, Na

doi:10.1109/access.2021.3062797

Cited by 16 publications

(3 citation statements)

References 23 publications

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“…The adaptive linear ADRC proposed in ref. [13] addresses the difficulty in parameter tuning and realizes the self‐adaptive adjustment of parameters, but its accuracy is lower than that of nonlinear ADRC. In ref.…”

Section: Introductionmentioning

confidence: 99%

Novel Active Disturbance Rejection‐Based Sliding‐Mode Control for Permanent Magnet Linear Synchronous Motor Drives

Yuan,

Guo,

Zhang

et al. 2023

IEEJ Transactions Elec Engng

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Active disturbance rejection control (ADRC) has been widely used in the permanent magnet linear synchronous motor (PMLSM) drive system for its strong anti‐disturbance ability and fast response speed. However, a large number of adjustment parameters add difficulties to its application. To solve this problem, a novel sliding mode‐based active disturbance rejection control (SM‐ADRC) with autotuned parameters is proposed in this paper. In this control strategy, the SM is incorporated with extended state observer (ESO) and nonlinear state error feedback (NLSEF) to reduce the number of adjustment parameters. The simulated annealing particle swarm optimization (SAPSO) algorithm is carried out to achieve the optimal configuration and realize parameter self‐tuning. The experimental results of the PMLSM speed servo system demonstrate the proposed control method has better suppression of chattering effect, disturbance rejection ability and fast dynamic response. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

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Section: Introductionmentioning

confidence: 99%

Novel Active Disturbance Rejection‐Based Sliding‐Mode Control for Permanent Magnet Linear Synchronous Motor Drives

Yuan,

Guo,

Zhang

et al. 2023

IEEJ Transactions Elec Engng

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“…Consequently, how to realise its stable suspension control [5][6][7] has been a popular research topic amongst researchers. Ouyang et al [8] proposed an adaptive linear active disturbance rejection method for magnetic levitation ball control based on the error elimination criteria, and it has achieved good dynamic performance but no experimental verification. Yu and Mu [9] introduced pure linear active disturbance rejection control (LADRC) to manage the magnetic suspension.…”

Section: Introductionmentioning

confidence: 99%

Based on Sliding Mode and Adaptive Linear Active Disturbance Rejection Control for a Magnetic Levitation System

Wu,

Fan,

Zhang

et al. 2023

Journal of Sensors

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The magnetic levitation system has evident advantages in reducing energy consumption, but its nonlinear characteristics increase the difficulty of control. This study proposes a control method that combines the improved particle swarm optimisation algorithm with sliding mode control and adaptive linear active disturbance rejection control (IPSO–SMC–ALADRC) to address the problems of weak anti-interference ability and stability in the application of traditional control methods in single-point magnetic levitation ball systems. First, a mathematical model of a single-point magnetic levitation ball is established. Second, the proportional and differential coefficients of LADRC are adjusted using adaptive laws, and the adaptive LADRC is combined with SMC to achieve stable control of the magnetic levitation ball. Moreover, an improved particle swarm optimisation algorithm is proposed to address the considerable number of adjustable parameters in the controller. The convergence and stability of the control algorithm were demonstrated using the Lyapunov equation. Finally, PID and LADRC are introduced for simulation and experimental comparison to verify the effectiveness of this control method. Results indicate that IPSO–SMC–ALADRC has excellent stability and anti-interference performance. This study addresses the problem of weak stability and anti-interference performance in the application of traditional control methods in the maglev system and further promotes the application of active disturbance rejection control in the magnetic levitation system.

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“…Nevertheless, due to the characteristics of high nonlinearity, strong coupling, and inherent instability of the MS [6][7][8][9][10], it is a challenge to achieve stable suspension, especially the strong disturbance in low wind speed areas will bring great challenges to MS. At present, the traditional suspension strategy employed the linear control theory to construct the control law [11][12][13][14][15][16]. However, as the operating point often changes and deviates from the operating point, the effective control cannot be obtained for this MS.…”

mentioning

confidence: 99%

Suspension Strategy of Maglev Vertical Axis Wind Turbine Based on Sliding Mode Adaptive Neural Network Predictive Control

2022

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The magnetic levitation system of the maglev vertical axis wind turbine is presented in this paper. The design and implement of the magnetic levitation controller are discussed, and the nonlinear mathematical model of the magnetic levitation system is established. However, the magnetic levitation system is extremely susceptible to disturbance. To suppress the external disturbance and parameter perturbations, a sliding mode adaptive neural network predictive control method is presented, which is composed of the sliding mode control, an adaptive neural network and a model predictive control. The sufficient simulation and experimental results show that the proposed suspension method reduces the impact of the external disturbance and improves the dynamic response speed. INDEX TERMSMaglev vertical axis wind turbine, Magnetic levitation system, Adaptive neural network, Model predictive control I. INTRODUCTION

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Adaptive LADRC Parameter Optimization in Magnetic Levitation

Cited by 16 publications

References 23 publications

Novel Active Disturbance Rejection‐Based Sliding‐Mode Control for Permanent Magnet Linear Synchronous Motor Drives

Novel Active Disturbance Rejection‐Based Sliding‐Mode Control for Permanent Magnet Linear Synchronous Motor Drives

Based on Sliding Mode and Adaptive Linear Active Disturbance Rejection Control for a Magnetic Levitation System

Suspension Strategy of Maglev Vertical Axis Wind Turbine Based on Sliding Mode Adaptive Neural Network Predictive Control

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