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首页> 外文期刊>Applied Soft Computing >Intelligent mixed H-2/H-infinity adaptive tracking control system design using self-organizing recurrent fuzzy-wavelet-neural-network for uncertain two-axis motion control system
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Intelligent mixed H-2/H-infinity adaptive tracking control system design using self-organizing recurrent fuzzy-wavelet-neural-network for uncertain two-axis motion control system

机译:基于自组织递归模糊小波神经网络的不确定两轴运动智能H-2 / H无限混合自适应跟踪控制系统设计

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摘要

In this paper, an intelligent adaptive tracking control system (IATCS) based on the mixed H-2/H-infinity approach under uncertain plant parameters and external disturbances for achieving high precision performance of a two-axis motion control system is proposed. The two-axis motion control system is an X-Ytable driven by two permanent-magnet linear synchronous motors (PMLSMs) servo drives. The proposed control scheme incorporates a mixed H-2/H-infinity controller, a self-organizing recurrent fuzzy-wavelet-neural-network controller (SORFWNNC) and a robust controller. The combinations of these control methods would insure the stability, robustness, optimality, overcome the uncertainties, and performance properties of the two-axis motion control system. The SORFWNNC is used as the main tracking controller to adaptively estimate an unknown nonlinear dynamic function that includes the lumped parameter uncertainties, external disturbances, cross-coupled interference and frictional force. Moreover, the structure and the parameter learning phases of the SORFWNNC are performed concurrently and online. Furthermore, a robust controller is designed to deal with the uncertainties, including the approximation error, optimal parameter vectors and higher order terms in Taylor series. Besides, the mixed H-2/H-infinity controller is designed such that the quadratic cost function is minimized and the worst case effect of the unknown nonlinear dynamic function on the tracking error must be attenuated below a desired attenuation level. The mixed H-2/H-infinity. control design has the advantage of both H-2 optimal control performance and H. robust control performance. The sufficient conditions are developed for the adaptive mixed H-2/H-infinity. tracking problem in terms of a pair of coupled algebraic equations instead of coupled nonlinear differential equations. The coupled algebraic equations can be solved analytically. The online adaptive control laws are derived based on Lyapunov theorem and the mixed H-2/H-infinity tracking performance so that the stability of the proposed IATCS can be guaranteed. Furthermore, the control algorithms are implemented in a DSP-based control computer. From the experimental results, the motions at X-axis and Y-axis are controlled separately, and the dynamic behaviors of the proposed IATCS can achieve favorable tracking performance and are robust to parameter uncertainties. (C) 2015 Elsevier B.V. All rights reserved.
机译:本文提出了一种基于混合H-2 / H-无穷大方法的智能自适应跟踪控制系统(IATCS),该方法在不确定的工厂参数和外部干扰下实现了两轴运动控制系统的高精度性能。两轴运动控制系统是X-Ytable,由两个永磁线性同步电动机(PMLSM)伺服驱动器驱动。提出的控制方案包括混合H-2 / H无穷大控制器,自组织递归模糊小波神经网络控制器(SORFWNNC)和鲁棒控制器。这些控制方法的组合将确保两轴运动控制系统的稳定性,鲁棒性,最优性,克服不确定性和性能。 SORFWNNC用作主要的跟踪控制器,以自适应地估计未知的非线性动态函数,该函数包括集总参数不确定性,外部干扰,交叉耦合干扰和摩擦力。此外,SORFWNNC的结构和参数学习阶段是同时并在线执行的。此外,设计了鲁棒控制器来处理不确定性,包括泰勒级数中的近似误差,最佳参数向量和高阶项。此外,混合H-2 / H-无穷控制器的设计应使二次成本函数最小化,并且必须将未知非线性动态函数对跟踪误差的最坏情况影响衰减到所需的衰减水平以下。混合的H-2 / H无穷大。控制设计具有H-2最佳控制性能和H.鲁棒控制性能的优势。为自适应混合H-2 / H-无穷大开发了充分的条件。跟踪问题是根据一对耦合代数方程而不是耦合非线性微分方程。耦合的代数方程可以解析地求解。基于Lyapunov定理和混合的H-2 / H无穷远跟踪性能,推导了在线自适应控制律,从而可以保证所提出的IATCS的稳定性。此外,控制算法在基于DSP的控制计算机中实现。从实验结果来看,分别控制X轴和Y轴的运动,所提出的IATCS的动态行为可以实现良好的跟踪性能,并且对参数不确定性具有鲁棒性。 (C)2015 Elsevier B.V.保留所有权利。

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