Online Iterative Optimization for Angle Tracking of Electromagnetic Scanning Micro-Mirror With Unmatched Interference and Hysteresis

IF 6.4 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Automation Science and Engineering Pub Date : 2024-08-05 DOI:10.1109/TASE.2024.3406166
Qingmei Cao;Yonghong Tan
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Abstract

In this paper, a precise angle tracking control strategy of electromagnetic driven scanning micro-mirror (EDSM) using online iterative optimization control (OIOC) scheme is addressed. Considering modeling difficulty caused by nonlinear hysteresis and complex dynamic characteristics, a simplified model (SM) is applied to describe the essential motion trait of EDSM approximately, more than that, the predictive model (PM) is developed based on the SM to improve the accuracy of the model. As for the omitted section caused by unmolded nonlinear and dynamic factor with unmatched interference (e.g., oscillation, nonlinear hysteresis and stochastic noise), that’s all being introduced into the angular deviation compensator (ADC) once again. Subsequently, a compensating structure SM+ADC is acquired to describe the dynamic performance and to design angular tracking control. Due to the nonlinear performance of multi-valued mapping, the generalized gradient is applied to optimize the control variables located in the nonlinear interval aiming to suppress the model deviation and eliminate unmatched interference. Then, a new iterative optimization control OIOC+ADC is obtained on the basis of compensation structure and generalized gradient. Besides, by designing Lyapunov function, the proposed control design incorporated by the relationship between optimized step-size and optimization gradient that needs to be satisfied guarantees the high accuracy positioning and stability. Conducted quantitative experiment results are provided to validate the effectiveness of the proposed control strategy in precise angle tracking to the fast dynamic system.
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无匹配干扰和滞后电磁扫描微镜角度跟踪的在线迭代优化
本文研究了一种基于在线迭代优化控制(OIOC)的电磁驱动扫描微镜(EDSM)精确角度跟踪控制策略。考虑到非线性迟滞和复杂的动力学特性给建模带来的困难,采用简化模型(SM)近似地描述了电火花切割机床的基本运动特性,并在此基础上建立了预测模型(PM),以提高模型的精度。对于由于未成形的非线性和动态因素与不匹配的干扰(如振荡、非线性迟滞、随机噪声)所导致的省略部分,将再次引入角偏差补偿器(ADC)中。在此基础上,提出了一种补偿结构SM+ADC来描述系统的动态性能,并设计了角度跟踪控制。由于多值映射的非线性特性,采用广义梯度对非线性区间内的控制变量进行优化,以抑制模型偏差,消除不匹配干扰。然后,基于补偿结构和广义梯度,得到了一种新的迭代优化控制OIOC+ADC。此外,通过设计Lyapunov函数,将优化步长与需要满足的优化梯度之间的关系纳入所提出的控制设计,保证了系统的高精度定位和稳定性。定量实验结果验证了所提出的控制策略对快速动态系统进行精确角度跟踪的有效性。
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来源期刊
IEEE Transactions on Automation Science and Engineering
IEEE Transactions on Automation Science and Engineering 工程技术-自动化与控制系统
CiteScore
12.50
自引率
14.30%
发文量
404
审稿时长
3.0 months
期刊介绍: The IEEE Transactions on Automation Science and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. T-ASE welcomes results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, security, service, supply chains, and transportation. T-ASE addresses a research community willing to integrate knowledge across disciplines and industries. For this purpose, each paper includes a Note to Practitioners that summarizes how its results can be applied or how they might be extended to apply in practice.
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