Improved adaptive fuzzy backstepping control of a magnetic levitation system based on Symbiotic Organism Search

Magnetic levitation systems have become very important in many applications. Due to their instability and high nonlinearity, such systems pose a challenge to many researchers attempting to design high-performance and robust tracking control. This paper proposes an improved adaptive fuzzy backstepping control for systems with uncertain input nonlinear function (uncertain parameters and structure), and applies it to a magnetic levitation system, which is a typical representative of such systems. An adaptive fuzzy system is used to approximate unknown, partially known or uncertain input nonlinear functions of a magnetic levitation system. An adaptation law is obtained based on Ljapunov analysis in order to guarantee closed-loop stability and good tracking performance. Initial adaptive and control parameters have been initialized with Symbiotic Organism Search optimization algorithm, due to strong non-linearity and instability of the magnetic levitation system. The theoretical background of the proposed control method is verified with a simulation study and implementation on a laboratory experimental application.     

Mathematical modelling of cylindrical electromagnetic vibration energy harvesters

In this paper the first steps for the derivation of a mathematical model to describe the mechanical behaviour of a cylindrical electromagnetic vibration energy harvester, designed to extract energy from human gait to power biomedical implantable devices, are provided. As it is usual, in the modelling of such devices, the proposed mechanical model is also based on the solution of Newton's second law, but here a nonlinear closed-form expression is used for the resulting magnetic force of the system, unlike what has been done in previous works where, traditionally, that expression is a linear or is a nonlinear approximation of the real one. The main feature of this mechanical model is that it depends on several parameters which are related to the main characteristics of this kind of devices, which constitutes a major advantage with respect to the usual models available in the literature since these characteristics can always be changed in order to optimize the device.     

单电磁悬浮系统的神经网络模糊滑模控制

为实现单电磁悬浮系统悬浮气隙的精确控制,提出一种基于神经网络的模糊滑模控制方案.根据单电磁悬浮系统的动态非线性数学模型,设计使系统状态在有限时间内到达稳定点的滑模面,同时根据滑模切换状态,通过引入神经网络的模糊控制方法对滑模切换控制量的增益进行评估,实时对滑模控制量进行调整,实现切换控制信号的柔化.基于神经网络的模糊滑模控制系统不仅能很好地跟踪给定信号,而且能削弱滑模控制抖振,对外部扰动具有完全的鲁棒性.仿真结果表明,所设计的控制系统零超调,具有速度跟踪性能,对外部扰动具有很强的鲁棒性.     

磁悬浮平台电磁悬浮系统的模糊滑模控制

为实现开环不稳定且高度非线性的磁悬浮平台悬浮气隙的精确控制,采用模糊滑模控制方案,根据电磁悬浮系统的动态非线性数学模型,设计使系统状态在有限时间内到达稳定点的滑模面,通过等效控制和切换控制律实现对参数摄动和外部扰动的完全鲁棒性.根据滑模切换状态,利用模糊推理方法柔化切换控制.基于模糊滑模控制器的控制系统能够有效地削弱滑模控制抖振,并较好地抑制外部扰动,且对参数变化具有完全鲁棒性,实现磁悬浮平台的高刚度稳定悬浮.结果表明,所设计的控制系统对参数变化及周期性扰动具有很强的鲁棒性.     

直线电机悬浮平台的μ-Η∞鲁棒控制

针对直线电机悬浮平台系统采用直接驱动方式易受参数变化、负载扰动、端部效应和齿槽效应等不确定性因素影响的问题,在系统模型反馈线性化的基础上,结合鲁棒控制器的设计方法和μ综合D-K迭代法,分别对悬浮平台系统的水平方向和竖直方向设计μ-Η_∞速度控制器.与速度控制器相比,该控制器具有更好的鲁棒性和快速性.仿真结果表明,采用了μ-Η_∞控制策略的系统对不确定性因素的影响有很好的抑制能力,实现了悬浮平台系统对定位精度、快速性和鲁棒性的要求.     

Al-Ti-C grain refiner made by ultrasonic levitation

An electrostrictive uniaxial ultrasonic levitation reaction system was designed to perform TiC synthesis reaction by suspending graphite powder in Al-3Ti melt and an Al-3Ti-0.15C grain refiner alloy was obtained. The results show that sound pressure node in which graphite suspends is formed in the melt between radiation block and reflecting board by ultrasonic and TiAl3 particles congregate around C powder. Meanwhile, due to ultrasonic cavitation, dissolved TiAl3 provides better surface condition for the synthesis reaction of TiC. The reaction route is that C and dissolved Ti react to form TiC. Ultrasonic cavitation has a thermal activation effect on TiC particles and Al-3Ti-0.15C refiner has excellent microstructural refining effect on α-Al.     

电磁悬浮和声悬浮过程的动态摄影研究

文章针对电磁悬浮和声悬浮过程的特点研究了获得悬浮样品图像信息的动态摄影技术。选取金属Ni和Al作为电磁悬浮的拍摄对象,通过研究不同光圈、快门速度和感光度获得的照片,发现获取高温悬浮金属液滴精确图像需要较高的快门速度同时需加以辅助光。声悬浮选取聚合物小球和水滴为拍摄对象,发现要获得不停振动的悬浮聚合物小球的清晰图像需要光圈、快门和感光度的完美配合。在上述基础上,选取合适的拍摄参数获得了悬浮液滴几何形状发生变化的清晰图像,同时探讨了生物活体的拍摄技术并获得了清晰生动的照片。     

移动式数控机床横梁磁浮系统的滑模-H_∞控制

针对龙门移动式数控机床在运行过程中参数摄动以及未建模动态参数可能对系统造成的影响,结合鲁棒H∞理论的控制方案设计出自适应积分滑模控制器.通过积分滑模变结构控制器对整个系统进行鲁棒控制,以确保磁悬浮系统的稳定性和精确性.为降低滑模控制器抖振的发生,采用自适应控制对控制律中的不确定值进行估测.考虑到刀具切削部件所引起的系统质量变化以及外力干扰等对系统的影响,在控制过程中结合了H∞的控制理论,以增加系统的鲁棒性.仿真研究结果表明,与传统控制器相比该控制器具有很强的抑制扰动能力,可以实现稳定悬浮.     

A modeling and control approach to magnetic levitation system based on state-dependent ARX model

Magnetic levitation (Maglev) systems are usually strongly nonlinear, open-loop unstable and fast responding. In order to control the position of the steel ball in a Maglev system, a data-driven modeling approach and control strategy is presented in this paper. A state-dependent AutoRegressive with eXogenous input (SD-ARX) model is built to represent the dynamic behavior between the current of electromagnetic coil and the position of the ball. State-dependent functional coefficients of the SD-ARX model are approximated by Gaussian radial basis function (RBF) neural networks. The model parameters are identified offline by applying the structured nonlinear parameter optimization method (SNPOM). Based on the model, a predictive controller is designed to stabilize the magnetic levitation ball to a given position or to make it track a desired trajectory. The real-time control results of the proposed approach and the comparisons with other two approaches are given, which demonstrate that the modeling and control method presented in this paper are very effective and superior in controlling the fast-responding, strongly nonlinear and open-loop unstable system. This paper gives the real experimental evidence that the RBF-ARX model is capable of not only globally, but also locally capturing and quantifying a nonlinear and fast-response system's behavior, and the model-based predictive control strategy is able to work quite well in a wide working-range of the nonlinear system.     

H∞与滑模融合控制算法在磁悬浮系统中的应用

磁悬浮系统在实际运行中会出现模型摄动和各种外界干扰,提高磁悬浮系统的鲁棒性非常重要,给出了磁悬浮系统的数学模型;结合H∞控制和滑模控制的优点,给出一种 H∞控制和滑模控制的融合算法,把该算法应用在磁悬浮系统中;通过Matlab仿真,验证了该算法能有效抑制磁悬浮系统中存在的确定性和不确定性干扰,从而使控制系统的性能得到提高。