车辆四轮转向控制平台研究

针对机-电-液复合结构的四轮转向平台具有非线性、快时变的特点，提出了模糊自适应PID控制策略。将模糊自适应补偿器与PID控制器并联，提高系统的鲁棒性和抗干扰能力。使用PID控制器稳定系统的线性标称部分，应用模糊自适应补偿器调节PID参数来补偿系统参数摄动、非线性和外界扰动对系统控制性能的影响。仿真和外加扰动实验结果验证了提出的控制策略对四轮转向平台的控制具有快速性、准确性、稳定性和鲁棒性。     

不确定机械系统的二阶逼近模糊滑模控制

针对不确定机械系统,利用模糊逻辑系统的万能逼近特性对未知非线性函数建模,以便设计控制方法。基于一阶逼近精度的模糊逻辑系统需要足够多的模糊规则才能保证一定的逼近精度,然而规则数的增多必然导致计算量的增大,不利于实时控制。本文中设计了具有二阶逼近精度的模糊逻辑系统对机械系统中的非线性未知部分进行实时逼近,并结合鲁棒性能好的滑模控制对不确定机械系统进行轨迹跟踪控制。从仿真实验证明,具有二阶逼近精度的模糊系统可以以很少的规则高精度的逼近任意非线性函数,并以此为基础构成的模糊滑模控制器不仅可以达到所希望的控制精度,比起规则数量多得多的模糊滑模控制,甚至位置误差和速度误差更小,跟踪速度更快。故采用特殊隶属函数所设计的自适应模糊逻辑系统,解决了逼近精度和模糊规则数量之间的矛盾,为机械系统的高精度的实时控制提供了保证。     

机械模糊可靠性仿真

本文将计算机仿真技术用于机械模糊可靠性分析中，建立了机械零件及机械系统的模糊可靠性仿真模型，给出了模糊可靠性仿真的一般方法，该方法适用于任意隶属函数、任意参数分布、零件间或失效模式间存在相关性的一般机械零件和机械系统的模糊可靠性分析。     

用于连续体的间隙非线性参数辨识方法

间隙在机械系统中是不可避免的,由间隙引起的接触非线性会严重影响系统的动态响应,使其偏离理想状态,进而降低机械系统的性能和使用寿命。若能利用系统的动态信息识别出间隙非线性参数,就能为机械系统的间隙控制提供依据。针对含间隙连续体系统,提出一种改进的恢复力-位移曲线和条件逆向路径法相结合的间隙非线性参数辨识方法。将哈密尔顿原理推导得到的微分方程简化为空间缩减模型,在获取系统输入和输出的基础上,使用改进的恢复力-位移曲线方法识别连续体系统的间隙值,再利用条件逆向路径法识别间隙接触刚度。整个识别过程在Matlab软件中进行仿真,并在设计的含间隙悬臂梁试验台上进行了参数辨识试验,仿真和试验结果均显示了较高的识别精度,验证了该方法的有效性。     

整车多体动力学模型的建立、验证及仿真分析

随着车速的不断提升，整车的稳定性能备受瞩目。作为复杂的机械系统，人、车、外界载荷环境等相互作用下，一直是汽车动力学模型建立、分析的难题。本文以某轿车的整车非线性动力学模型建立为理论主体，考虑转向系统及前后悬架的几何参数，以及阻尼器与橡胶衬套等非线性特征，对所建模型进行多元化实验，分析样车的稳定性能及可操控性等相关特点，结果表明所建模型就较高的精度，在动力学研究中起到了关键作用。     

一种基于卡尔曼滤波的非线性模型在线模糊辨识算法

文章提出一种用于非线性模型在线辨识的模糊算法。该算法将非线性输入输出系统用时变线性系统模型来拟和，并把此非线性系统模型表示成模糊模型的形式，用在线调节模糊模型的方法来辨识时变线性模型的相关参数。本文将递推模糊聚类方法与卡尔曼滤波法用于在线调整模糊模型参数。仿真算例表明了此算法的有效性。     

一种单力臂机械系统的鲁棒自适应控制

针对具有参数不确定性的单力臂机械系统,引入模型参考自适应控制思想,研究了一种鲁棒模型参考自适应控制方法;在具有参数不确定性和未知非线性摩擦特性的情况下,使系统的跟踪误差趋于零。通过理论推导和MATLAB仿真,均说明该方法的有效性。     

电液比例位置控制系统的参数自整定Fuzzy-PI控制

文章针对电液比例位置控制系统非线性、时变性等特点，采用了一种参数自整定模糊PI控制器，井应用在锻造操作机的位置控制系统中。参数自整定模糊PI控制能根据偏差和偏差变化率在线调整控制器的参数，优化了模糊控制器的性能。仿真及实践表明，该控制器具有良好的稳态控制精度和较强的鲁棒性，也满足了系统实时控制的要求。     

基于全局代价函数优化的立体标定方法

提出了一种基于全局代价函数的立体标定方法.以张正友的单日摄像机标定算法为基础,同时选择合适的径向畸变模型,将左右摄像机的内参数、摄像机与标定板之间的外参数、镜头畸变系数,以及两个摄像机之间的外参数标定相互融合,使用一种约束性更强的全局代价函数作为优化目标进行非线性优化,经过一次优化便可以得到立体视觉系统中的摄像机参数.与通常的立体标定方法相比,该方法在目标函数中引入了左右摄像机之间外参数保持不变这一约束条件,从而使得重投影残差更小、标定精度更高,并且整个算法具有更强的鲁棒性.对比实验结果证明,这种基于全局代价函数优化的标定方法具有精度高、标定结果稳定等优点.     

基于反馈线性化和保性能控制的轴向磁轴承单侧线圈故障容错控制

针对轴向永磁偏置磁轴承一侧线圈无电流时磁轴承承载能力下降且非线性增强的情况,提出一种反馈线性化与保性能控制相结合的组合容错控制策略来提高轴向磁轴承在故障情况下的承载能力并使其能在承重时稳定悬浮转子。首先,建立了故障情况下后轴向磁轴承-转子系统的非线性动力学模型,通过反馈线性化方法使系统大范围线性化。然后,在考虑参数摄动的基础上设计最优保性能控制器使转子稳定悬浮。最后,在轴向一侧线圈无电流的永磁偏置磁悬浮转子上进行了多项实验。实验结果表明,所设计的组合容错控制器实现了承重情况下转子的稳定悬浮,摄动最大的参数变化约35%时位移跳动量峰值为2.6μm,超调量小于3%,调节时间为82ms。结果验证了该方法不仅能实现容错控制,而且具有良好的动静态性能及鲁棒性。     

机电非线性振动系统参、强联合激励的分岔

建立机电耦联非线性电机模型的数学方程：利用非线性振动理论中的非固定参数的渐近法，研究由电磁力激发的参数激励、强迫激励联合作用下非线性振动系统的动力学特性，由理论分析、数值计算得到系统的分岔转迁集和四种分岔响应曲线。在实验的基础上揭示各种电磁参数及机械参数对主参数共振的振幅、运动稳定性及共振曲线的拓扑结构的影响，同时显示系统的运动状态及其稳定域，分析结果为有效地控制电机的稳定运行提供依据。     

齿轮齿条进给伺服系统综合模型的研究

为分析齿轮齿条进给伺服系统中各参数对系统动态性能的影响,利用机械动力学原理以及控制理论方法,推导出进给系统数学模型并构建了包括刚度、非线性间隙、非线性摩擦的参数化结构图,为系统的结构参数设计以及性能的提高提供理论分析依据.     

完全参数激励下索梁耦合系统非线性动力学分析

研究完全参数激励下弹性拉索与悬臂梁耦合结构的非线性动力学问题。建立索梁耦合结构力学模型,利用Hamilton 原理建立索－梁耦合系统的非线性动力学方程,利用Galerkin方法将索－梁耦合系统的非线性运动偏微分方程离散为一组常微分方程。利用多尺度法分析研究索－梁耦合动力学系统的非线性振动,用Runge-Kutta法对数学模型进行数值计算,得到当梁与索的频率比为2:1时,系统发生严重的参数共振,同时探讨阻尼参数对索－梁耦合系统非线性动力学的影响,并提出对工程有实际意义的结论。     

考虑结构非线性特征的参数化形状优化方法

提出并实现一种将参数化设计技术应用于考虑结构非线性特征的形状优化设计领域的新方法。参数化设计技术是近年来发展起来的新一代CAD软件平台的核心技术之一。文中基于三维参数化CAD平台，将参数化设计技术、有限元建模技术与有限元分析优化系统集成为参数化的形状优化系统；引入非线性分析技术，以解决工程上大量存在的非线性形状优化问题。该方法克服了以往形状优化方法应用于三维实体结构时所面临的几何形状描述、约束与驱动的困难，为机械产品三维结构优化设计提供一个新途径。     

Adaptive fuzzy approach for a class of uncertain nonlinear systems in strict-feedback form

Adaptive fuzzy control is proposed for a class of affine nonlinear systems in strict-feedback form with unknown nonlinearities. The unknown nonlinearities include two types of nonlinear functions: one satisfies the "triangularity condition" and can be directly approximated by fuzzy logic system, while the other is assumed to be partially known and consists of parametric uncertainties. Takagi-Sugeno type fuzzy approximators are used to approximate unknown system nonlinearities and the design procedure is a combination of adaptive backstepping and generalized small gain design techniques. It is proved that the proposed adaptive control scheme can guarantee the uniformly ultimately bounded (UBB) stability of the closed-loop systems. Simulation studies are shown to illustrate the effectiveness of the proposed approach.     

Modeling and control compensation of nonlinear friction using adaptive fuzzy systems

System performance in terms of control accuracy and stability is usually negatively affected by friction occurrences in mechanical systems. Thus, it is important to model the friction properly so that it can be used in controller design. This paper employs adaptive fuzzy systems to approximate unknown nonlinear friction functions, and applies the estimation of friction in proportional-derivative (PD) control law to enhance the control performance. On the basis of Lyapunov stability theory, a bound of tracking errors of the closed-loop control system is derived. Techniques proposed in this paper have been applied to a typical motion control system for simulation studies. The results obtained demonstrate that our proposed method in this paper has good potential in controlling many mechanical systems with unknown nonlinear friction.     

基于模糊神经网络的磁浮车悬浮控制器

以EMS型磁悬浮车单电磁铁为研究对象,建立了系统的数学模型.为增强悬浮系统的抗干扰能力和负载能力,针对其非线性特性,采用神经网络和模糊控制理论相结合的方法设计了非线性控制器FNNC.该控制器继承了模糊控制鲁棒性强以及神经网络的非线性逼近和自学习能力,运用加速反传训练方法对参数进行调整,并通过TMS320F2812型DSP实现单点悬浮用.实验及仿真表明,该控制器使系统悬浮稳定,动态性能好,与传统的PID控制器相比具有更好的快速跟踪性能和抗干扰能力.     

INDIRECT ACCELERATED ADAPTIVE FUZZY CONTROLLER

According to a type of normal nonlinear system, an indirect adaptive fuzzy （IAF） controller has been applied to those systems where no accurate mathematical models of the systems under control are available. To satisfy with system performance, an indirect accelerated adaptive fuzzy （IAAF） controller is proposed, and its general form is presented. The general form IAAF controller ensures necessary control criteria and system＇s global stability using Lyapunov Theorem. It has been proved that the close-loop system error converges to a small neighborhood of equilibrium point. The optimal IAAF controller is derived to guarantee the process＇s shortest settling time. Simulation results indicate the IAAF controller make the system more stable, accurate, and fast.     

Robust decentralized hybrid adaptive output feedback fuzzy control for a class of large-scale MIMO nonlinear systems and its application to AHS

This paper presents a novel observer-based decentralized hybrid adaptive fuzzy control scheme for a class of large-scale continuous-time multiple-input multiple-output (MIMO) uncertain nonlinear systems whose state variables are unmeasurable. The scheme integrates fuzzy logic systems, state observers, and strictly positive real conditions to deal with three issues in the control of a large-scale MIMO uncertain nonlinear system: algorithm design, controller singularity, and transient response. Then, the design of the hybrid adaptive fuzzy controller is extended to address a general large-scale uncertain nonlinear system. It is shown that the resultant closed-loop large-scale system keeps asymptotically stable and the tracking error converges to zero. The better characteristics of our scheme are demonstrated by simulations.     

Modeling and fuzzy control of the engine coolant conditioning system in an IC engine test bed

Mechanical and thermodynamical performance of internal combustion engines is significantly affected by the engine working temperature. In an engine test bed, the internal combustion engines are tested in different operating conditions using a dynamometer. It is required that the engine temperature be controlled precisely, particularly in transient states. This precise control can be achieved by an engine coolant conditioning system mainly consisting of a heat exchanger, a control valve, and a controller. In this study, constitutive equations of the system are derived first. These differential equations show the second-order nonlinear time-varying dynamics of the system. The model is validated with the experimental data providing satisfactory results. After presenting the dynamic equations of the system, a fuzzy controller is designed based on our prior knowledge of the system. The fuzzy rules and the membership functions are derived by a trial and error and heuristic method. Because of the nonlinear nature of the system the fuzzy rules are set to satisfy the requirements of the temperature control for different operating conditions of the engine. The performance of the fuzzy controller is compared with a PI one for different transient conditions. The results of the simulation show the better performance of the fuzzy controller. The main advantages of the fuzzy controller are the shorter settling time, smaller overshoot, and improved performance especially in the transient states of the system.