磁悬浮自适应控制

以自适应PID结构针对磁悬浮系统设计非线性控制器，并在磁悬浮球装置上进行了试验，结果证实这种控制器具有完全的鲁棒性、良好的参数适应性，设计方法也有广泛的适用性。     

一类非线性系统的间接自适应模糊滑模控制

基于启发式知识的模糊控制是一种解决非线性系统控制问题的有效方法。然而其设计缺乏系统性,并且系统的稳定性和鲁棒性难以保证。本文利用滑模控制的概念和Lyapunov综合方法提出一种针对一类非线性系统的间接自适应模糊滑模控制（IAFSMC）方法。仿真研究表明即使在缺少系统先验知识和不确定性干扰的情况下,系统性能也十分理想。     

模糊自适应PID算法在磁悬浮实时控制系统中的应用研究

针对磁悬浮系统的复杂非线性及模型不确定的特点,采用模糊PID算法对其进行控制,以满足系统对动态性能和静态性能的要求;结合PID实时控制中的经验,建立合理的模糊规则,模糊推理机构根据不同的偏差e、偏差变化率ec对PID参数Kp、Ki和Kd进行自校正;在磁悬浮实验装置中进行实时控制实验,通过与常规PID控制效果的比较来验证模糊PID控制器的性能;在系统输入存在正弦扰动时,模糊PID控制器使系统响应过程中的振荡幅度得到明显减小,干扰对控制效果的影响被减弱;实验证明,模糊PID控制器具有较强的鲁棒性和抗干扰能力,对于磁悬浮这种非线性系统具有良好的控制效果。     

时滞系统的模糊自适应PID控制研究

将模糊控制和常规PID控制相结合,设计了一种模糊自适应PID控制器,该控制器根据偏差和偏差变化率的要求实时调整PID参数。通过仿真表明：该控制器既具有常规PID控制器高精度的优点,又具有模糊控制器快速、适应性强的特点,并可以迅速消除系统误差,保证了系统具有良好的动、静态特性。     

基于神经网络的模糊自适应PID控制方法

提出一种基于BP神经网络的模糊自适应PID控制器。该控制器综合模糊控制、神经网络与PID调节各自的优点，既具有模糊控制的简单和有效的非线性控制作用，又具有神经网络的学习和适应能力，同时具备PID控制的广泛适应性，仿真实验表明该控制器对模型、环境具有较好的适应能力和较强的鲁棒性。     

一类多变量非线性动态系统的模糊自适应控制

对一类非线性多变量未知动态系统，提出了一种模糊处在适应控制策略。证明了该控制算法能保证闭环系统稳定，跟踪误差收敛。     

磁悬浮系统的HOPF分岔自适应控制研究

磁悬浮固有系统是非线性的,也是本质不稳定的,其稳定性设计比较复杂,特别是在受到较大干扰和对象参数发生较大变化时,系统容易失去稳定并发散.理论分析与试验表明,这种现象的数学解释就是系统出现了HOPF分岔.为此,本文提出了一种用HOPF分岔规律调整非线性系统PID控制器参数的自适应设计方法,通过辨识干扰或者对象参数的变化,自动调整控制参数,使闭环系统远离HOPF分岔点,从而继续保持稳定.以悬浮质量突变为例的仿真表明,由此整定悬浮控制比例增益参数,可使磁悬浮系统获得较大的状态稳定范围,并有效回避自激振动.     

磁悬浮球系统模糊PID参数自调整控制方法

因磁悬浮系统具有非线性、迟滞性、不稳定性的特点,传统的控制方法难以达到较好的控制效果.针对这些问题,提出了一种不依赖系统精确数学模型的模糊PID控制算法.首先根据模糊控制理论和人工调整PID参数的实际经验,对PID参数制定了模糊控制规则袁,进而通过模糊推理和重心法解模糊过程得到PID参数的隶属度,最终实现了磁悬浮系统实...     

磁悬浮系统的非线性PID控制

在磁悬浮控制系统中采用线性PID控制方法时,如果只是靠增加比例反馈来提高系统的刚度,很可能降低系统的性能,有时甚至会引起系统不稳定。为了提高PID控制方法的刚度,同时又不影响系统的性能,提出了一种非线性PID反馈控制方法。线性PID控制方法的控制量是通过位置和速度的线性组合来求取,而非线性PID控制的控制量是通过位置和速度的非线性组合来求取,因此采用位置和速度信号的指数组合形式来求取控制量。非线性PID控制方法相对于线性PID控制方法的最大优势是其刚度大、抗外力冲击能力强。实验结果验证了非线性PID控制方法的优越性。     

磁悬浮轴承的模糊PID控制

针对磁悬浮轴承控制系统多变量强耦合、不易建立精确数学模型的特点,应用模糊PID控制技术。实现对5自由度磁悬浮轴承的数字控制。该控制方法简单实用,不仅可以简化磁悬浮轴承控制系统的设计,同时还能够提高系统的控制精度。为了进一步提高控制系统的快速性,采用DSP芯片TMS320VC33作为控制核心。试验结果表明,系统的控制效果良好,有一定的实用价值。     

Explicit nonlinear predictive control for a magnetic levitation system

The paper presents a methodology for the construction of an explicit nonlinear control law via approximation of the nonlinear constrained finite‐time optimal control (CFTOC). This is achieved through an approximate mapping of a general nonlinear system in a set of linear piecewise affine (PWA) systems. The key advantages of this methodology are two‐fold. First, the construction of an analytic solution of the CFTOC problem leads to an efficient explicit implementation. Second, by taking advantage of model predictive control's systematic fashion to handle constraints, an improved performance can be obtained for the closed‐loop system. The proposed theory is applied in real‐time for a system with fast dynamics: a magnetic levitation benchmark. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

基于MATLAR的磁悬浮球系统PID控制器设计与实现

介绍了磁悬浮球系统的结构和工作原理,建立了磁悬浮系统的数学模型并进行线性化处理;设计PID控制器,在Simulink环境下搭建控制系统的模型进行仿真研究,并在固高GML1001系列磁悬浮装置上进行实时控制实验。实验结果表明,采用PID控制,能使钢球快速地悬浮在期望位置,并且有一定的抗干扰能力。     

基于BP的PID算法在磁轴承控制系统中研究

磁悬浮轴承数学模型复杂，常规PID很难达到预期控制效果。本文综合常规PID及BP网络的优点，设计出一种基于BP网络的PID自调整算法控制器。仿真结果表明：使用该算法的PID控制器，可在线获得最优的比例、积分及微分参数值，使整个系统得到最优化配置。     

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.     

模糊PID控制器在自适应巡航控制系统中的应用

车辆的油门控制算法是自适应巡航控制系统(ACC：Adaptive Cruise Control)中的核心算法之一。这里采用的模糊PID算法(Fuzzy PID)是对常用的两输入单输出模糊控制算法的改进。通过使用Matlab／Simulink建立车辆动力学模型和控制器模型,对控制器的性能进行了仿真分析,验证了算法的合理性。     

Adaptive control based on fast online algebraic identification and GPI control for magnetic levitation systems with time-varying input gain

This paper considers the position tracking problem of a voltage-controlled magnetic levitation system (MLS) in the presence of modelling errors caused by uncertainties in the system’s physical parameters. An adaptive control based on fast online algebraic parameter estimation and generalised proportional integral (GPI) output feedback control is considered as a control scheme candidate. The GPI controller guarantees an asymptotically exponentially stable behaviour of the controlled ball position and the possibilities of carrying out rest-to-rest trajectory tracking tasks. The nature of the control input gain in an MLS is that of a state-dependent time-varying gain, reflecting the nonlinear character of the magnetic force with regard to the distance and the properties of the metallic ball. The system gain has therefore been locally approximated using a periodically updated time polynomial function (of second degree), where the coefficients of the polynomial are estimated during a very short period of time. This estimation is achieved using the recently introduced algebraic online parameter estimation approach. The stability of the closed-loop system is demonstrated under the assumption that no external factors cause changes in the parameter during the time interval in which the stability is analysed. Finally, experimental results are presented for the controlled MLS demonstrating the excellent stabilisation and position tracking performance of the control system designed in the presence of significant nonlinearities and uncertainties of the underlying system.     

Trajectory tracking for the magnetic ball levitation system via exact feedforward linearisation and GPI control

The output feedback control of the popular magnetic ball levitation system is addressed from a suitable combination of several complementary viewpoints. We use: first, recent developments on exact feedforward linearisation controllers for nonlinear flat systems to substantially reduce the linear feedback controller efforts through pre-compensation. Second, an on-line ball velocity estimation strategy is proposed by using a model-based integral reconstructor, which is a linear combination of iterated integrals of the input and the output of the system, thus avoiding the use of traditional observers or noisy derivative estimations. Finally, we use a generalised proportional integral (GPI) controller which compensates the errors in the integral reconstructor and further bestows the enhanced robustness on the closed-loop system via output tracking error iterated integration feedback. This methodology only requires the measurements of the position of the levitated ball and of the control input voltage. The proposed feedback regulation scheme is shown to locally guarantee an asymptotically exponentially stable behaviour of the controlled ball position and, definitely, allows for the possibilities of safely carrying out the rest-to-rest trajectory tracking tasks on the ball position. The proposed output feedback controller is actually implemented on a laboratory prototype with excellent experimental results for, both, stabilisation and trajectory tracking tasks.     

受控磁悬浮系统非线性随机响应分析

讨论了非线性磁悬浮控制系统随机振动响应预测问题．基于等效非线性微分方程方法,从理论上对非线性磁悬浮控制系统的随机响应进行了深入分析,建立了此高维系统非线性模型;根据中心流形理论对系统进行约化、降维,给出了此系统响应的近似解析解．这对此系统实现进一步稳定控制提供了有效的理论依据．     

Nonlinear model predictive control of a magnetic levitation system

The paper presents a fast nonlinear model predictive control (MPC) scheme for a magnetic levitation system. A nonlinear dynamical model of the levitation system is derived that additionally captures the inductor current dynamics of the electromagnet in order to achieve a high MPC performance both for stabilization and fast setpoint changes of the levitating mass. The optimization algorithm underlying the MPC scheme accounts for control constraints and allows for a time and memory efficient computation of the single iteration. The overall control performance of the levitation system as well as the low computational costs of the MPC scheme is shown both in simulations and experiments with a sampling frequency of 700 Hz on a standard dSPACE hardware.     

一种新的ARX模型在磁悬浮系统建模中的应用

采用一种新的ARX模型（RBF-ARX模型）对磁悬浮系统进行离线建模,讨论了RBF-ARX模型的原理、结构的选取、模型参数辨识和RBF参数优化等问题。文章分别采用不同的序列作为状态变量,分别建立RBF-ARX模型,并分析了各模型的性能及可靠性。模型的预测输出和仿真结果,证实了RBF-ARX模型在非线性系统建模和辨识中的有效性。通过与ARX模型的比较,证明了RBF-ARX模型在非线性系统建模中效果更好。