一类时变非线性系统的模型偏差补偿控制

本文通过对滑模控制进行改进,提出了适用于一类时变非线性系统的模型偏差补偿控制方案,用于实现高精度的连续轨迹跟踪控制,并指出了该方案和 PID 控制方案的一些联系.     

具有间隙非线性系统的控制加权自适应控制

本文对具有间隙的非线性系统提出一种可控制开环不稳定及非最小相位系统的控制加权自适应算法,并给出了稳定性收敛性定理及其证明。仿真结果表明,该算法可明显地改善系统的控制性能。     

混沌系统的RBF神经网络非线性补偿控制

设计RBF神经网络非线性补偿控制器,提出了混沌系统线性状态反馈的复合控制方法,将可调系统混沌行为镇定到期望目标位置或者变成周期运动.用Lorenz方程作仿真实验,结果证明了该方法的有效性.     

非线性系统近似最优PD动态补偿控制

本文研究了一类基于动态补偿的非线性系统的近似最优PD控制的问题.用微分方程的逐次逼近理论将非线性系统的最优控制问题转化为求解线性非齐次两点边值序列问题,并提供了从时域最优状态反馈到频域最优PD控制器参数的优化方法,从而获取系统最优的动态补偿网络,设计出最优PD整定参数,给出其实现算法.最后仿真示例将所提出的方法与传统的线性二次型调节器（LQR）逐次逼近方法相比较,表明该方法具有良好的动态性能和鲁棒性.     

非线性系统多步预测控制的复合神经网络实现

提出一种基于神经网络的非线性多步预测控制,采用由线性网络和动态递归神经网络构成的复合神经网络。在此基础上将线性系统的广义预测控制器扩展为非线性系统的多步预测控制器。通过对非线性过程ＣＳＴＲ的仿真表明,该方法的稳定性和鲁棒性明显优于线性ＤＭＣ预测控制。     

非线性复合邻域人脸光照补偿

变化的光照是提高人脸正确检测率的瓶颈,提出了非线性复合邻域光照补偿方法来解决人脸检测的光照问题。非线性复合邻域光照补偿方法用对数函数做为基函数,设置的平移系数和分界值系数可以同时对过亮和偏光的图像进行补偿,引入了邻域光照补偿公式解决了传统非线性方法不能针对同一灰度值像素在不同局部应该进行不同补偿的问题。实验结果表明,该方法对过暗和过亮的人脸图像都可以进行有效的光照补偿,熵比较优于传统非线性光照补偿、Gamma校正和直方图归一化。     

多输入单输出Wiener-Hammerstein 模型的集群辨识

讨论了集群辨识的概念和特点.针对多输入单输出Wiener-Hammerstein模型提出了一种集群辨识方法.方法的基本思想是将模型辨识问题转化为参数空间上非线性函数的最优化问题,然后采用集群智能方法对整个参数空间进行高效并行搜索以获得模型参数的最优估计.仿真结果显示了本方法的有效性.     

具有间隙非线性系统的自适应控制*

本文对具有间隙非线性系统提出了自适应控制算法,在确定和随机情况下,控制算法都具有大范围渐近收敛性质,仿真结果表明该算法能有效地改善系统的控制性能。     

具有间隙与补偿的分线性预测控制

本文通过引入间隙非线性预补偿器,讨论了具有间隙非线性特性及白噪声干扰的系统的预测控制问题。     

死区非线性系统特性分析及补偿控制

针对含有非线性"死区"环节的热工控制对象,用线性系统理论和描述函数方法分析了系统的动态特性,给出了可选择的控制器的类型和参数的极限值;为了克服"死区"对闭环系统性能的影响,建立了偏差信息与死区参数之间的关系,构造了一个动态"死区逆模型"来修正控制器的输出,试验结果表明,所设计的动态逆模型可以完全补偿死区特性的影响,这种方法简单、可行.     

Observer‐based compensation control of servo systems with backlash

For compensating backlash phenomenon in servo systems, the authors propose an observer method in this paper to estimate both system states and vibration torque before controller design. First, a systematic scheme is given to obtain plant parameters, which is very important in observing system states. This is a parameter estimation principle that gives a crude estimation and computes the differences between the crude and true values. As a result, the precise value of the parameters is obtained by adding together the crude value and the difference. Then, based on the precise estimated parameters, an extended state observer (ESO) is designed to obtain feedback and feedforward signals. Consequently, robust compensation control is achieved by designing an output feedback controller, consisting of a feedback term and a feedforward term. Finally, in order to validate the proposed approach, extensive experiments are performed on a practical servo system with backlash nonlinearity.     

输入具有齿隙非线性特性的周期系统的自适应控制

针对一类输入含齿隙非线性动态特性的周期时变系统, 在周期不确定性可时变参数化的条件下设计自适应控制器. 对周期时变参数进行傅里叶级数展开, 并采用微分自适应律估计未知傅里叶系数和齿隙动态特性参数, 通过鲁棒方法消除截断误差和齿隙模型的有界误差项对系统性能的影响. 采用双曲函数替代符号函数确保控制器可微, 同时能有效抑制颤振. 引入Δ函数, 避免参数估计发散, 并保证系统输出渐近跟踪理想轨迹. 理论分析与仿真结果表明, 闭环系统所有信号有界.     

Adaptive inverse compensation for actuator backlash with piecewise time-varying parameters

Existing adaptive inverse compensation methods for cancelling actuator backlash nonlinearity are all restricted to handle constant backlash parameters. In other words, when discontinuity and time variation as both ubiquitous phenomena in practical actuators exist, such inverse compensation methods are no longer applicable theoretically. So far, no result has been reported in addressing such an issue, regardless of its importance in practice. In this paper, we solve this problem by developing a new piecewise Lyapunov function analysis and using parameter projection adaptation mechanism. Based on such approaches, an adaptive inverse compensation control scheme is designed to compensate for piecewise time-varying actuator backlash nonlinearity. It is proved that all signals of closed-loop system are ensured bounded. Moreover, the steady-state error is bounded by an adjustable scalar approaching to zero arbitrarily. Simulation also illustrates the obtained theoretical results.     

考虑齿隙伺服系统的反步自适应模糊控制

针对具有未知参数和齿隙非线性的机电伺服系统,引入一种近似死区函数建立了系统的数学模型,给出了死区函数中参数的选取方法.用两个自适应模糊逻辑系统在线逼近机电伺服系统中的未知参数和非线性环节,从而避免了对每个未知参数推导自适应律.基于反步法设计了自适应模糊控制器,可抑制未知参数和齿隙非线性对系统性能的影响.采用Lyapunov方法证明了位置跟踪误差的指数收敛性.与PID控制方法对比的仿真实验表明,本文方法能够显著减小齿轮间传递力矩的振荡,并具有很好的控制精度和鲁棒性.     

Synchronization and tracking control for multi‐motor driving servo systems with backlash and friction

This paper presents a novel switching controller incorporated with backlash and friction compensations, which is utilized to achieve speed synchronization among multi‐motor and load position tracking. The proposed controller consists of two parts: synchronization and tracking control in contact mode and robust control in backlash mode, where a function characterizing whether backlash occurs is used for switching between two modes. Using the proposed switching controller, several control objectives are achieved. Firstly, the coupling problem of speed synchronization and load tracking in contact mode is addressed by introducing a switching plane. Secondly, based on the switching plane, an improved prescribed performance function is introduced to attain load tracking with prescribed performances, and L_∞ performance of speed synchronization is guaranteed by initialization method, maintaining the transient performance of synchronization behavior. Thirdly, the lumped uncertain nonlinearity including friction and other uncertain functions is compensated by Chebyshev neural network in contact mode. Furthermore, a robust control is adopted in backlash mode to make system traverse backlash at an exponential rate and simultaneously eliminate low‐speed crawling phenomenon of LuGre friction. Finally, comparative simulations on four‐motor driving servo system are provided to verify the effectiveness and reliability. Copyright © 2015 John Wiley & Sons, Ltd.     

间隙三明治系统的改进卡尔曼状态估计

控制工程中许多实际系统都可以描述为带间隙的三明治系统,由于间隙具有非光滑、局部记忆性和多值映射等复杂非线性特性,使得整个三明治系统的内部状态估计工作具有很大挑战性.首先根据间隙三明治系统的特性引入了几个自动切换函数,采用关键项分离原理,建立了随机噪声干扰下间隙三明治系统的非光滑整体伪线性状态空间模型.针对该系统提出了一种非光滑的改进卡尔曼滤波算法以估计系统状态,其工作机制能够随系统当前工作区间的转变而自动切换模式.仿真和实验结果表明,针对含噪声的间隙三明治系统,非光滑的改进卡尔曼滤波算法对系统状态的估计准确度要高于传统卡尔曼滤波算法.     

基于反步自适应控制的伺服系统齿隙补偿

齿隙是影响机电伺服系统动/静态性能的一个重要因素. 为了减小其不利影响, 该文以存在不确定参数的机电位置伺服系统为研究对象, 针对系统中存在的齿隙非线性, 应用反步积分方法, 通过逐步递推选择Lyapunov函数,设计了基于状态反馈的自适应控制器. 通过理论分析以及与传统PID控制的仿真结果比较表明, 该方案显著地降低了齿隙对伺服性能的影响, 提高了系统的跟踪精度和鲁棒性.     

Adaptive robust control for four-motor driving servo system with uncertain nonlinearities

A novel adaptive robust control (ARC) is presented for the four-motor driving servo systems with the uncertain nonlinearities and actuation failures, such that the load tracking control is achieved with the proximate optimal-time. By applying the proposed scheme, several control objectives are achieved. First, the nonlinear synchronization algorithm is presented to maintain the velocity synchronization of each motor, which provides fast convergence without chatting. Moreover, the time-varying bias torque is applied to eliminate the effect of backlash and reduce the waste of energy. Then, the ARC is designed to achieve the proximate optimal-time output tracking with the transient performance in $L_2$ norm, where the friction and actuation failures are addressed by the adaptive scheme based on the norm estimation of unknown parameter vector. Finally, the extensive simulated and experimental results validate the effectiveness of the proposed method.