There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

关于Semigroups of Linear Operators and Applications to Partial Differential Equations的两个注解

Differential-Difference Equations. By Richard Bellman and Kenneth L. Cooke. Pp. xvi, 465. 1963. (Academic Press)

Disturbance-observer-based control (DOBC) and related methods have been researched and applied in various industrial sectors in the last four decades. This survey, at first time, gives a systematic and comprehensive tutorial and summary on the existing disturbance/uncertainty estimation and attenuation techniques, most notably, DOBC, active disturbance rejection control, disturbance accommodation control, and composite hierarchical antidisturbance control. In all of these methods, disturbance and uncertainty are, in general, lumped together, and an observation mechanism is employed to estimate the total disturbance. This paper first reviews a number of widely used linear and nonlinear disturbance/uncertainty estimation techniques and then discusses and compares various compensation techniques and the procedures of integrating disturbance/uncertainty compensation with a (predesigned) linear/nonlinear controller. It also provides concise tutorials of the main methods in this area with clear descriptions of their features. The application of this group of methods in various industrial sections is reviewed, with emphasis on the commercialization of some algorithms. The survey is ended with the discussion of future directions.

/pdf/disturbance-observer-based-control-and-related-methods-an-795w6vym5o.pdf

Disturbance-Observer-Based Control and Related Methods—An Overview

Most of the signal processing that we will study in this course involves local operations on a signal, namely transforming the signal by applying linear combinations of values in the neighborhood of each sample point. You are familiar with such operations from Calculus, namely, taking derivatives and you are also familiar with this from optics namely blurring a signal. We will be looking at sampled signals only. Let's start with a few basic examples. Local difference Suppose we have a 1D image and we take the local difference of intensities, DI(x) = 1 2 (I(x + 1) − I(x − 1)) which give a discrete approximation to a partial derivative. (We compute this for each x in the image.) What is the effect of such a transformation? One key idea is that such a derivative would be useful for marking positions where the intensity changes. Such a change is called an edge. It is important to detect edges in images because they often mark locations at which object properties change. These can include changes in illumination along a surface due to a shadow boundary, or a material (pigment) change, or a change in depth as when one object ends and another begins. The computational problem of finding intensity edges in images is called edge detection. We could look for positions at which DI(x) has a large negative or positive value. Large positive values indicate an edge that goes from low to high intensity, and large negative values indicate an edge that goes from high to low intensity. Example Suppose the image consists of a single (slightly sloped) edge:

http://ieeexplore.ieee.org/iel5/5/31307/01456462.pdf

Linear systems

On the convergence of an extended state observer for nonlinear systems with uncertainty

1 Introduction.- 1.1 Overview and examples of infinite dimensional systems.- 1.2 Organization and brief summary.- 1.3 Remarks on notation.- 1.4 Notes and references.- 2 Semigroups of Linear Operators.- 2.1 Motivation and definitions.- 2.2 Properties of semigroups.- 2.3 Generation theorems for semigroups.- 2.4 Relation with the Laplace transform.- 2.5 Differentiability and analytic semigroups.- 2.6 Compact semigroups.- 2.7 Abstract Cauchy problem.- 2.7.1 Homogeneous initial value problems.- 2.7.2 Inhomogeneous initial value problems.- 2.7.3 Lipschitz perturbations.- 2.8 Integrated semigroups.- 2.9 Nonlinear semigroups of contractions.- 2.10 Notes and references.- 3 Stability of C0-Semigroups.- 3.1 Spectral mapping theorems.- 3.2 Spectrum-determined growth condition.- 3.3 Weak stability and asymptotic stability.- 3.4 Exponential stability - time domain criteria.- 3.5 Exponential stability - frequency domain criteria.- 3.6 Essential spectrum and compact perturbations.- 3.7 Invariance principle for nonlinear semigroups.- 3.8 Notes and references.- 4 Static Sensor Feedback Stabilization of Euler-Bernoulli Beam Equations.- 4.1 Modeling of a rotating beam with a rigid tip body.- 4.2 Stabilization using strain or shear force feedback.- 4.3 Damped second order systems.- 4.4 Exponential stability and spectral analysis.- 4.4.1 Exponential stability.- 4.4.2 Spectral analysis.- 4.5 Shear force feedback control of a rotating beam.- 4.5.1 Well-posedness and exponential stability.- 4.5.2 Asymptotic behavior of the spectrum.- 4.6 Stability analysis of a hybrid system.- 4.6.1 Well-posedness and exponential stability.- 4.6.2 Spectral analysis.- 4.7 Gain adaptive strain feedback control of Euler-Bernoulli beams.- 4.8 Notes and references.- 5 Dynamic Boundary Control of Vibration Systems Based on Passivity.- 5.1 A general framework for system passivity.- 5.1.1 Uncontrolled case.- 5.1.2 Controlled case.- 5.2 Dynamic boundary control using positive real controllers.- 5.2.1 Positive real controllers and their characterizations.- 5.2.2 Stability analysis of control systems with SPR controllers.- 5.3 Dynamic boundary control of a rotating flexible beam.- 5.3.1 Stabilization problem using SPR controllers.- 5.3.2 Orientation problem using positive real controllers.- 5.4 Stability robustness against small time delays.- 5.5 Notes and references.- 6 Other Applications.- 6.1 A General linear hyperbolic system.- 6.2 Stabilization of serially connected vibrating strings.- 6.3 Two coupled vibrating strings.- 6.4 A vibration cable with a tip mass.- 6.5 Thermoelastic system with Dirichlet - Dirichlet boundary conditions.- 6.6 Thermoelastic system with Dirichlet - Neumann boundary conditions.- 6.7 Renardy's counter-example on spectrum-determined growth condition.- 6.8 Notes and references.

Stability and Stabilization of Infinite Dimensional Systems with Applications

In this paper, the global and semiglobal convergence of the nonlinear active distur- bance rejection control (ADRC) for a class of multi-input multi-output nonlinear systems with large uncertainty that comes from both dynamical modeling and external disturbance are proved. As a result, a class of linear systems with external disturbance that can be dealt with by the ADRC is classified. The ADRC is then compared both analytically and numerically to the well-known in- ternal model principle. A number of illustrative examples are presented to show the efficiency and advantage of the ADRC in dealing with unknown dynamics and in achieving fast tracking with lower overstriking.

/pdf/on-convergence-of-the-nonlinear-active-disturbance-rejection-2rbwd0xlqs.pdf

On convergence of the nonlinear active disturbance rejection control for mimo systems

http://flyingv.ucsd.edu/papers/PDF/92.pdf

Output-feedback stabilization of an unstable wave equation

This paper considers nonfragile exponential synchronization for complex dynamical networks (CDNs) with time-varying coupling delay. The sampled-data feedback control, which is assumed to allow norm-bounded uncertainty and involves a constant signal transmission delay, is constructed for the first time in this paper. By constructing a suitable augmented Lyapunov function, and with the help of introduced integral inequalities and employing the convex combination technique, a sufficient condition is developed, such that the nonfragile exponential stability of the error system is guaranteed. As a result, for the case of sampled-data control free of norm-bound uncertainties, some sufficient conditions of sampled-data synchronization criteria for the CDNs with time-varying coupling delay are presented. As the formulations are in the framework of linear matrix inequality, these conditions can be easily solved and implemented. Two illustrative examples are presented to demonstrate the effectiveness and merits of the proposed feedback control.

Bao-Zhu Guo

Papers

On the convergence of an extended state observer for nonlinear systems with uncertainty

Stability and Stabilization of Infinite Dimensional Systems with Applications

On convergence of the nonlinear active disturbance rejection control for mimo systems

Output-feedback stabilization of an unstable wave equation

Nonfragile Exponential Synchronization of Delayed Complex Dynamical Networks With Memory Sampled-Data Control