Robust predictive extended state observer for a class of nonlinear systems with time-varying input delay

ABSTRACT

This paper deals with asymptotic stabilisation of a class of nonlinear input-delayed systems via dynamic output feedback in the presence of disturbances. The proposed strategy has the structure of an observer-based control law, in which the observer estimates and predicts both the plant state and the external disturbance. A nominal delay value is assumed to be known and stability conditions in terms of linear matrix inequalities are derived for fast-varying delay uncertainties. Asymptotic stability is achieved if the disturbance or the time delay is constant. The controller design problem is also addressed and a numerical example with an unstable system is provided to illustrate the usefulness of the proposed strategy.     

Probabilistic output admissible set for systems with time-varying uncertainties

This paper considers time-varying uncertain constrained systems, and develops a method for computing a probabilistic output admissible (POA) set. This set consists of the initial states probabilistically assured to satisfy the constraint. The time-invariant counterpart has already been investigated in Hatanaka and Takaba [Computations of probabilistic output admissible set for uncertain constrained systems, Automatica 44 (2) (2008), to appear]. We first define the POA set for time-varying uncertainties with finite dimensional probability space. Then, we show that an algorithm similar to Hatanaka and Takaba [Computations of probabilistic output admissible set for uncertain constrained systems, Automatica 44 (2) (2008), to appear] provides the POA set also in the time-varying case, as long as an upper bound of a what we call future output admissibility (FOA) index is available. We moreover present two methods for computing the upper bound of the FOA index: probabilistic and deterministic methods. A numerical simulation demonstrates the effectiveness of our algorithm.     

Control of discrete time nonlinear systems with a time-varying structure

In this paper, we present a control methodology for a class of discrete time nonlinear systems that depend on a possibly exogenous scheduling variable. This class of systems consists of an interpolation of nonlinear dynamic equations in strict feedback form, and it may represent systems with a time-varying nonlinear structure. Moreover, this class of systems is able to represent some cases of gain scheduling control, Takagi-Sugeno fuzzy systems, as well as input-output realizations of nonlinear systems which are approximated via localized linearizations. We present two control theorems, one using what we call a “global” approach (akin to traditional backstepping), and a “local” approach, our main result, where backstepping is again used but the control law is an interpolation of local control terms. An aircraft wing rock regulation problem with varying angle of attack is used to illustrate and compare the two approaches.     

An adaptive tracking problem for a family of retarded time-delay plants

Most of the existing switching control techniques are developed specifically for finite-dimensional linear time-invariant (LTI) systems. In many practical applications, however, it is essential to take time delay into consideration in the modelling as the control system can be highly sensitive to delay. In this paper, a multi-model switching control algorithm is proposed for retarded time-delay systems. It is assumed that the plant is represented by a family of known multi-input multi-output, observable, LTI models with multiple delays in the states, and that corresponding to each model in the known family, there exists a high-performance finite-dimensional LTI controller. In addition, it is supposed that a bound on the magnitude of the external inputs and disturbances is available. It is then shown that the proposed switching controller can stabilize the uncertain system, and that under some mild conditions, output tracking can be achieved in the given problem setting. Copyright © 2007 John Wiley & Sons, Ltd.     

视觉诱发脑电波的时变最优滤波估计

本文提出了一个自修正的非平稳信号模型,并设计了时变最优滤波器于视觉诱发脑电波 的估计.估计出的信号与原始信号的各波峰潜伏期严格保持一致,而波峰幅值略有衰减.给 出的仿真与实体试验结果都证明了本方法的有效性.     

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.     

Generalized adaptive notch filters with frequency debiasing for tracking of polynomial phase systems

Generalized adaptive notch filters are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. For general patterns of frequency variation the generalized adaptive notch filtering algorithms yield biased frequency estimates. We show that when system frequencies change slowly in a smooth way, the estimation bias can be substantially reduced by means of post-filtering of the frequency estimates. The modified (debiased) algorithm has better tracking capabilities than the original algorithm.     

无线ILC系统测控信号延时效应补偿方法

针对通过无线信道进行测控信号传输的远程迭代学习控制( ILC)系统,研究信号传输延时对控制系统性能的影响.分析了测控信号延时情况下ILC系统的收敛性问题,通过引入预控制向量,提出了ILC系统信道延时效应补偿的向量更新方法.数值仿真结果表明了所提方法的有效性.     

一种新的码片内多径时延估计方法

根据信道冲激响应的稀疏特性,提出了一种频域的时延估计压缩感知模型,将时延估计问题转化为基于欠采样数据的稀疏向量估计问题.利用离散傅里叶变换(Discrete Fourier transform,DFT)矩阵的子矩阵所满足的受限等距性(Restricted isometry property,RIP)以及信道冲激响应的稀疏特性充分降低了时延估计所需数据量的要求.分析了本文模型具有码片内多径分辨能力以及良好抗噪性能的原因,并与多信号分类(Multiple signal classification,MUSIC)和旋转不变技术的信号参数估计(Estimation of signal parameters via rotational invariance technique,ESPRIT)算法的时延估计性能进行仿真比较.仿真结果表明,本文提出的方法不需要预知多径的条数,对码片内多径时延具有较高的估计精度,其时延估计性能在特定条件下优于MUSIC和ESPRIT算法.