基于时间尺度的一类典型高阶系统的二阶线性自抗扰控制

高阶系统由于其本身的性质,使得控制它变得很困难。为了控制一类典型的可用传递函数描述的高阶对象,用二阶线性自抗扰(LADRC)控制器对高阶系统进行参数整定。将已整定好的高阶系统作为基准系统,通过时间尺度概念将基准系统参数转换为需要控制的新的高阶系统的参数,使得新系统具有基准系统的响应特性。该方法能方便、快捷地算出新系统的参数,通过仿真证明了该方法的可行性,具有广泛的参考价值。     

基于移动数据窗的传递函数多新息随机梯度辨识方法

一些工业过程可以近似用一个传递函数描述,结合统计辨识方法和非线性优化策略提出传递函数参数辨识方法.该方法采用动态数据方案,使用系统观测数据获得系统更多的模态信息.基于动态观测数据,提出传递函数随机梯度参数辨识方法.为进一步提高辨识精度,利用动态窗数据将随机梯度参数辨识方法中的标量新息扩展为新息向量,提出传递函数多新息随机梯度参数估计方法.最后通过仿真例子对所提出的方法进行了性能分析和模型验证.     

控制系统的一种直接盲辨识方法

提出一种在时域中直接盲辨识系统传递函数的方法。首先利用过采样方法，将SISO系统转换为具有相同零极点的SIMO系统进行处理；然后通过对新的SIMO模型先估计分子参数、后估计分母参数的方法，即可获得原SISO模型的参数估计。该方法也可用于辨识非最小相位系统。     

非线性动态系统建模方法研究

讨论了一类非线性动态系统建模的新方法。首先,假设原非线性动态系统可以用Hammerstein模型来表示。然后,将Hammerstein模型的非线性传递函数转换为等价的线性形式,从而建立起中间模型。接下来,利用粒子群优化（Particle Swarm Optimization,PSO）算法辨识出中间模型参数。最后,通过中间模型参数与Hammerstein模型参数之间的关系,推出非线性静态环节和线性动态环节的参数,从而实现原非线性动态系统建模。为了进一步增强建模的性能,提出了利用一种改进的粒子群优化（Improved Particle Swarm Optimization,IPSO）算法。仿真结果说明了该方法的合理性和有效性。     

交通网络车流量的分布式协同优化方法研究

针对城市交通网络主干道车流量密度非连续特性,分析了交通网络车流量分段仿射模型.从最小化车流量延迟角度,给出了优化目标函数并进行凸分析.在此基础上,将城市交通网络系统描述为非完整性约束条件的非线性动态系统,利用反步法通过控制变量代换和状态转换将该系统转化为时变可控协同标准型的一般形式,并设计城市交通网络系统的分布式协同控制律.然后在城市主干道交通网络模型中,分别对协同分布式优化方法、定时控制、感应控制三种交通控制算法进行对比仿真分析,从仿真结果可以看出,本文所提出的协同分布式优化方法具有较好的性能,有效的降低了交通网络中车辆平均等待时间.     

环境试验室热工系统规则自提取模糊控制仿真

以某环境试验室室内温度、送风系统和热水系统多回路在线控制为背景, 针对其存在的多参数、大滞后、非线性等控制难题, 讨论了各个回路热工特性传递函数建立和自组织模糊控制仿真问题. 首先, 提出了规则自提取模糊控制(self-abstracting rules fuzzy control, SARFC)方法. 然后, 根据各被控回路的动态热工特性和参数辨识要求, 试验研究了各回路的动态响应特性, 完成了各回路传递函数模型参数的辨识, 得到了各回路的传递函数模型. 最后, 采用SARFC方法, 仿真研究了基于送风系统调节和热水系统调节的环境试验室温度模糊控制仿真, 得到了较好的控制仿真效果, 为进一步试验研究环境试验室热工系统模糊控制提供了理论基础.     

基于MATLAB和IBA软件的轧制力系统辨识应用

本文以某平整机轧制力系统为实例,通过IBA软件将现场数据读入MATLAB工作空间,在MATLAB中通过辨识算法对现场数据处理获得轧制力系统传递函数,仿真结果表明,该方法得到的模型可以准确的描述轧制力系统工作特性。     

基于Hopfield神经网络的线性系统参数辨识

基于Ｈｏｐｆｉｅｌｄ神经网络的优化计算原理,提出了一种新的线性系统参数辨识方法,利用连续型ＨＮＮ辨识线性系统Ｉ／Ｏ差分方程计算系统的传递函数矩阵,最终获得了可观标准型的状态空间表达式,仿真结果证明了这种只方法的有效性。     

Z—S变换及其应用

利用Ｚ域（离散系统传递函数Ｇ（Ｚ）到Ｓ域（连续系统传递函数Ｇ（Ｓ）的直接变换公式，得到了系统的连续时间系统传递函数，数值仿真例子说明Ｚ－Ｓ变换比双线性变换有更高的模型转换精度。     

基于目标函数的递推子空间辨识算法

针对实际工程中要求对系统参数进行在线估计的问题, 提出一种递推子空间辨识的新方法. 通过引入辅助变量关系将递推子空间辨识问题转化为目标函数的迭代最小化问题. 采用递推最小二乘算法在线估计参数并由传播方法得到更新的广义能观性矩阵, 进而求得子空间辨识模型系统参数. 该算法简单有效且对初值具有鲁棒性. 最后, 通过仿真实例验证算法的有效性.     

前馈控制的工程实现

本文讨论了工程中常见的单回路和多回路前馈控制的工程实现,并把控制对象分为有自 平衡和无自平衡两大类,把每大类的传递函数化成标准表达式,用低阶近似方法求出各种前 馈控制及其参数的计算公式. 上述结果亦可推广到多变量控制系统.     

New reduction technique by step error minimization for multivariable systems

A method of reduction of system order is introduced, in which a lower-order transfer function/transfer matrix is obtained by minimizing an error function constructed from the time responses of the system and the reduced model. The denominator of the reduced model can be selected either by retaining dominant poles or by the Routh method. The numerator of the reduced model is obtained by minimizing the step response error along with a steady-state constraint. The error function is converted into the frequency domain and the minima operation is carried out in this domain. Since the numerator polynomial selection is independent of the denominator, the method is very general and can be applied for MIMO systems as well as for SISO systems. A numerical example of a multivariable system illustrates the procedure.     

Recursive identification for dynamic systems with backlash

A recursive algorithm for identification of nonlinear dynamic systems with backlash is proposed in this paper. In this method, the backlash, which is a non‐smooth function, is decomposed into a combination of a group of piecewise linearized models so that all the parameters of the backlash can be estimated separately. Moreover, the model of the backlash is embedded into a Hammerstein‐type model. Thus, a pseudo‐Hammerstein model with backlash is constructed. The estimation of the parameters for such a non‐smooth nonlinear system can be implemented through a so‐called recursive general identification algorithm (RGIA). Then, the corresponding convergence analysis of the RGIA for the model with backlash is also investigated. After that, two examples are presented to show the performance of the proposed method. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Fractional representations of linear systems

A fractional representation of an arbitrary linear system is obtained that can be viewed as a generalization of a classical fractional representation of a transfer function. Conversely, a state-space model, not necessarily observable or controllable, can be assigned to any such fractional model. It is then shown that the categories of state-space and fractional representations of a linear system are equivalent.     

Proportional integral-fractional filter controller design for first order lag plus time delay system

In this work, a design approach of proportional integral-fractional filter (PI-FF) controller for first order plus time delay (FOPTD) system is proposed in order to enhance the feedback control system performances characteristics. The controller design method is drawn up such that the transfer function of the overall closed-loop system is equivalent to the transfer function of the general fractional Bagley–Torvik reference model whose behaviour ranges from relaxation to oscillation for different values of the fractional order derivative and the damping ratio-like parameter. The tuning parameters of the PI-FF controller are derived analytically from the FOPTD process model and the general fractional Bagley–Torvik reference model parameters. Illustrative examples were presented to test the effectiveness and the usefulness of the proposed PI-FF controller on the feedback control system performance characteristics enhancement.     

Proportional integral-fractional filter controller design for first order lag plus time delay system

In this work, a design approach of proportional integral-fractional filter (PI-FF) controller for first order plus time delay system (FOPTD) is proposed in order to enhance the feedback control system performance characteristics. The controller design method is drawn up such that the transfer function of the overall closed-loop system is equivalent to the transfer function of the general fractional Bagley–Torvik reference model whose behaviour ranges from relaxation to oscillation for different values of the fractional order derivative and the damping ratio-like parameter. The tuning parameters of the PI-FF controller are derived analytically from the FOPTD process model and the general fractional Bagley–Torvik reference model parameters. Illustrative examples were presented to test the effectiveness and the usefulness of the proposed PI-FF controller on the feedback control system performance characteristics enhancement.     

Object matching in disjoint cameras using a color transfer approach

Object appearance models are a consequence of illumination, viewing direction, camera intrinsics, and other conditions that are specific to a particular camera. As a result, a model acquired in one view is often inappropriate for use in other viewpoints. In this work we treat this appearance model distortion between two non-overlapping cameras as one in which some unknown color transfer function warps a known appearance model from one view to another. We demonstrate how to recover this function in the case where the distortion function is approximated as general affine and object appearance is represented as a mixture of Gaussians. Appearance models are brought into correspondence by searching for a bijection function that best minimizes an entropic metric for model dissimilarity. These correspondences lead to a solution for the transfer function that brings the parameters of the models into alignment in the UV chromaticity plane. Finally, a set of these transfer functions acquired from a collection of object pairs are generalized to a single camera-pair-specific transfer function via robust fitting. We demonstrate the method in the context of a video surveillance network and show that recognition of subjects in disjoint views can be significantly improved using the new color transfer approach.     

Observer design for discrete systems with unknown exogenous inputs

A design procedure is developed for determining optimal discrete observers for estimating system states and unknown exogenous system inputs. This procedure is based on augmenting a standard system observer with an input model. The augmented model is then transformed into the discrete z-domain to determine relevant input/output transfer function matrices. The transfer function matrices are used to develop transfer function relationships between unknown exogenous inputs and the observer estimate of these inputs. It is shown that the optimal observer gains can be determined by implementing the observer as a Fisher filter. An example of the procedure is demonstrated with a third-order point-mass tracking filter