다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

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.

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

This paper studies a number of quantized feedback design problems for linear systems. We consider the case where quantizers are static (memoryless). The common aim of these design problems is to stabilize the given system or to achieve certain performance with the coarsest quantization density. Our main discovery is that the classical sector bound approach is nonconservative for studying these design problems. Consequently, we are able to convert many quantized feedback design problems to well-known robust control problems with sector bound uncertainties. In particular, we derive the coarsest quantization densities for stabilization for multiple-input-multiple-output systems in both state feedback and output feedback cases; and we also derive conditions for quantized feedback control for quadratic cost and H/sub /spl infin// performances.

The sector bound approach to quantized feedback control | NOVA. The University of Newcastle's Digital Repository

This work presents a general framework for nonlinear systems subject to disturbances using disturbance observer based control (DOBC) techniques. A two-stage design procedure to improve disturbance attenuation ability of current linear/nonlinear controllers is proposed where the disturbance observer design is separated from the controller design. To facilitate this concept, a nonlinear disturbance observer is developed for disturbances generated by an exogenous system, and global exponential stability is established under certain condition. Furthermore, semiglobal stability condition of the composite controller consisting of a nonlinear controller and the nonlinear disturbance observer is established. The developed method is illustrated by the application to control of a two-link robotic manipulator.

/pdf/disturbance-observer-based-control-for-nonlinear-systems-5gmmz4z7cy.pdf

Disturbance observer based control for nonlinear systems

Stability and L2-gain analysis for switched delay systems: A delay-dependent method

This paper discusses the on-line frequency identification problem for a measured sinusoidal signal by using the adaptive method and filter theory. The proposed method is based on an identity between the sinusoidal signal and its second order derivative. For a set of chosen parameters, the proposed method is robust to the initial phase, the amplitude, and the frequency in a wide range. The convergence rate can be adjusted by the chosen parameters. The estimation error mainly depends on the frequency of the sinusoid, the measurement noise and a key design parameter.

Robust On-Line Frequency Identification for a Sinusoid

In this article, an adaptive neural piecewise implicit inverse control strategy is proposed to effectively compensate for butterfly hysteresis effectively. First, a new butterfly Krasnoselskii–Pokrovskii (BKP) model is developed for the double-loop butterfly hysteresis characteristics. Second, an adaptive neural piecewise implicit inverse control strategy is designed to mitigate the butterfly-like hysteresis without constructing its analytical inverse model. Finally, experimental results on the dielectric elastomer actuator (DEA) motion control platform demonstrate the effectiveness of the adaptive neural piecewise implicit inverse control strategy.

Adaptive Neural Piecewise Implicit Inverse Controller Design for a Class of Nonlinear Systems Considering Butterfly Hysteresis

In this paper, an implicit inversion of the hysteresis described by Preisach model is introduced to avoid difficulties of the directly inverse construction for this kind of complex hysteresis models. Based on this inversion, the adaptive control for unknown linear dynamical systems preceded with hysteresis described by Presaich model is formulated. The stability of the controlled systems is analyzed and zero output tracking error can be eventually achieved. Finally, the proposed algorithm is applied to the position control of the nano-stage driven by magnetostrictive actuator.

Control for unknown systems preceded by hysteresis and its application to nanopositioner

Advanced control for the XY-table driven by piezo-actuators

The motion parameter estimation for a class of movements in the space by using stereo vision is considered by observing a group of points. The considered motion equation can cover a wide class of practical movements in the space. The observability of this class of movement is clarified. The estimation algorithm for the motion parameters which are all time-varying is developed based on the second method of Lyapunov. The assumptions about the perspective system are reasonable and have apparently physical interpretations. The proposed recursive algorithm requires minor a priori knowledge about the system. Experimental results show the proposed algorithm is effective even in the presence of measurement noises.

Xinkai Chen

Papers

Robust On-Line Frequency Identification for a Sinusoid

Adaptive Neural Piecewise Implicit Inverse Controller Design for a Class of Nonlinear Systems Considering Butterfly Hysteresis

Control for unknown systems preceded by hysteresis and its application to nanopositioner

Advanced control for the XY-table driven by piezo-actuators

Stereo vision based motion parameter estimation