Approximate feedback linearization of discrete-time non-linear systems using virtual input direct design

The design of feedback-linearization and poles-placement controllers for discrete-time non-linear plants, using Input/Output/State measurements only, is typically addressed via indirect design. In this paper we propose the use of a new technique, based on a Virtual Input Direct Design (VID²) approach. The main feature of such a technique is to reduce the control design problem into a standard non-linear mapping approximation problem, without calling for the preliminary construction of an appropriate model of the plant. As compared with the existing methods, the new one requires less computational effort, while taking full advantage of the non-linear approximation software tools already available. In this paper, the new method is described, a simple theoretical analysis is given, and some numerical examples are presented.     

A complete VARMA modelling methodology based on scalar components

Abstract. This article proposes an extension to scalar component methodology for the identification and estimation of VARMA models. The complete methodology determines the exact positions of all free parameters in any VARMA model with a predetermined embedded scalar component structure. This leads to an exactly identified system of equations that is estimated using full information maximum likelihood.     

Linear deterministic adaptive control: fundamental limitations?

This paper is concerned with the achievable performance of adaptive control algorithms. We show that when the only uncertainty is in the form of fixed parameter errors, then there exists an adaptive feedback law whose performance can be made arbitrarily close to that achievable when the system is a priori known. The result is not intended as a practical strategy. Instead, we use it to make the, perhaps obvious, point that meaningful results on performance of adaptive control algorithms must account for non-ideal factors including, at a minimum, noise, parameter time variations and unstructured uncertainty.     

Subspace identification of MIMO LPV systems using a periodic scheduling sequence

A novel subspace identification method is presented which is able to reconstruct the deterministic part of a multivariable state-space LPV system with affine parameter dependence, in the presence of process and output noise. It is assumed that the identification data is generated with the scheduling variable varying periodically during the course of the identification experiment. This allows to use methods from LTI subspace identification to determine the column space of the time-varying observability matrices. It is shown that the crucial step in determining the original LPV system is to ensure the obtained observability matrices are defined with respect to the same state basis. Once the LPV model has been identified, it is valid for other nonperiodic scheduling sequences as well.     

Steady-state weights solution to affine projection algorithm

A new expression of the weights update equation for the affine projection algorithm (APA) is proposed that improves the convergence rate of an adaptive filter,particularly for highly colored input sign...     

直流伺服系统模型及其辨识

伺服系统又称为随动系统,是构成自动化体系的一种基本环节,是由若干元件和部件组成的具有功率放大作用的一种自动控制系统。系统辨识是指当用户无法从物理上得出所研究系统的数学模型,但可以通过适当的实验手段测试出系统的某种响应信息时,就可以根据它来获得系统的数学模型。本文完成了对直流伺服系统的建模以及辨识,尤其是利用系统的阶跃响应数据对直流伺服系统的模型进行了直接辨识,即由系统阶跃响应采样数据构造线性方程组,通过对方程组求解估计出系统参数。最后,对辨识出的系统进行了仿真,将仿真结果与原阶跃响应数据比较,表明所采用的辨识方法取得了良好的效果。     

四旋翼无人机的系统模型与辨识

研究无人机系统优化控制问题,为实现四旋翼微型飞行器的自动控制飞行,需要得到正确的系统模型参数,实现精确控制。子空间辨识法可以直接地反应出多输出多输出系统模型,算法比较容易实现。首先从四旋翼的力学模型出发,建立了在小角度假设下的线性系统模型,并首次将子空间辨识方法运用到四旋翼飞行器的辨识中。用仿真实例实验,假设飞行器在缓慢上升过程,采用由子空间辨识方法获得的系统模型输出与原系统在同样输入条件下的输出进行了比较。结果表明在假设条件下的辨识具有可行性,为中旋翼无人机优化控制提供了依据。     

基于RGB颜色特征的印鉴图像预处理

针对票据印鉴在RGB颜色空间分布的特点,通过算法将红色印鉴从杂乱的背景和噪声中分离出来,得到二值化的印鉴图像,再通过去噪得到较好的预处理印鉴图像。实验证明,该方法的计算速度较快,并能在一定程度上恢复出被背景覆盖的印鉴部分,使得提取的印章有较理想的视觉效果。     

智能家居的发展方向与新技术

智能家居是人们对家居生活的一种理想。随着高新技术的不断发展,各技术领域智能程度的提高,智能家居也有了新的发展方向。本文首先给出了智能家居的发展方向,接着根据这些发展方向介绍了与此相关的信息技术、通信技术和无线射频技术等等,为智能家居的发展提供了有益的参考。     

相关函数脉冲响应法系统实时辨识

结合了相关函数法和脉冲响应法两种经典系统辨识方法原理,在随机信号干扰的情况下,设计对系统实现实时辨识的仿真软件,获得系统的非参数模型。该仿真设计中,以M序列作为输入信号,白噪声信号作为干扰信号,进行了Matlab仿真实验,讨论了M序列的幅值,采样时间和周期长度对系统辨识效果的影响,以及分析M序列的选取方法来减少系统辨识误差。