http://disciplinas.stoa.usp.br/pluginfile.php/166516/mod_resource/content/1/Radiomics.pdf

Radiomics: the process and the challenges

In this paper, we present two novel algorithms to realize a finite dimensional, linear time-invariant state-space model from input-output data. The algorithms have a number of common features. They are classified as one of the subspace model identification schemes, in that a major part of the identification problem consists of calculating specially structured subspaces of spaces defined by the input-output data. This structure is then exploited in the calculation of a realization. Another common feature is their algorithmic organization: an RQ factorization followed by a singular value decomposition and the solution of an overdetermined set (or sets) of equations. The schemes assume that the underlying system has an output-error structure and that a measurable input sequence is available. The latter characteristic indicates that both schemes are versions of the MIMO Output-Error State Space model identification (MOESP) approach. The first algorithm is denoted in particular as the (elementary MOESP scheme)...

Subspace model identification-Part 1. The output-error state-space model identification class of algorithms

Control strategies for crane systems: A comprehensive review

Introduction Part I: Preliminaries Linear Algebra and Preliminaries Disctrete-time Linear Systems Stochastic Processes Kalman Filter Part II: Realization Theory Realization of Deterministic Problems Stochastic Realization Theory I Stochastic Realization Theory II Part III: Subspace Identification Subspace Identification I: ORT Subspace Identification II: CCA Identification of Closed-loop System Appendices Least-squares Method Input Signals for System Identification Overlapping Parametrization Matlab(R) Programs Solutions to Problems

Subspace methods for system identification

In this paper, an efficient face recognition method using AGA and ANFIS-ABC has been proposed. At first stage, the face images gathered from the database are preprocessed. At Second stage, an interest point which is used to improve the detection rate consequently. The parameters used in the interest point determination are optimized using the Adaptive Genetic Algorithm. Finally using ANFIS, face images are classified by using extracted features. During the training process, the parameters of ANFIS are optimized using Artificial Bee Colony Algorithm (ABC) in order to improve the accuracy. The performance of the proposed ANFIS-ABC technique is evaluated using an ORL database with 400 images of 40 individuals, YALE-B database with 165 images of 15 individuals and finally with real time video the detection rate and false alarm rate is compared with proposed and existing methods to prove the system efficiency.

Interest point based face recognition using adaptive neuro fuzzy inference system

This paper deals with modelling and control of an overhead crane with a flexible cable. The developed dynamical model includes both transverse vibrations of the flexible cable and large swing angles of cable while the trolley is moving horizontally. To carry out the modelling, Rayleigh-Ritz discretization method is used to achieve an ordinary differential equation (ODE) model for transverse deflection of the cable with finite generalized degrees of freedom. Using the Euler–Lagrange formulation, a nonlinear dynamic model of the crane system with a flexible cable is obtained. The control objective is to move the payload position to the desired point and at the same time, to reduce the payload swing and to suppress the cable’s transverse vibration. To this end, a static state feedback control combined with integral error feedback is proposed. Simulations are performed using the developed nonlinear model under various conditions to illustrate the effectiveness of the proposed control system. Keyword: Overhead crane system; Cable vibration; Vibration suppression, Anti-swing

https://journals.sagepub.com/doi/pdf/10.1260/0263-0923.33.4.395

Modelling and Control of an Overhead Crane System with a Flexible Cable and Large Swing Angle

In this paper, the problem of disturbance attenuation with internal stability for a class of nonlinear singularly perturbed systems via nonlinear H∞ approach is studied. It is shown through a useful theorem that under appropriate assumptions, the problem of disturbance attenuation for the main system may be related to the problem of disturbance attenuation for the reduced-order system. This is carried out by a new approach in which we use the quasi-steady state of fast variables. Therefore, the problem of existence of a positive definite solution for the Hamilton–Jacobi–Isaacs (HJI) inequality related to the main system leads to the problem of existence of a solution of a simpler HJI inequality related to the reduced-order system.

Robust Stabilization for a Class of Nonlinear Singularly Perturbed Systems

This paper aims to develop an advanced control system for an overhead crane with transverse vibrations of flexible cable while considering large angle of the cable swing. The control objective is to move the payload to a desired position and at the same time, to reduce the payload swing and to suppress the cable transverse vibrations only by applying a directional (horizontal) driving force to the trolley. The crane system with cable vibrations and large swing angle is categorized as a multi-degree under-actuated system whose characteristics impose serious challenges when applying control methods. One reasonable way to overcome the challenges is to separate the degrees of under actuation. To do so, singular perturbation approach is used to divide the dynamical system into a fast subsystem for cable vibrations (with flexible un-actuated coordinates) and a slow subsystem for trolley motion and cable swing (with one degree of under actuation). Based on two-time scale control method, a composite control syste...

https://journals.sagepub.com/doi/pdf/10.1260/0263-0923.34.3.361

Using Singular Perturbation Method for Controlling a Crane System with a Flexible Cable and Large Swing Angle

Lip Segmentation Using Geometrical Model of Color Distribution

The congestion control problem of the intermediate nodes in the Internet has received extensive attention in control community. In this study, a novel intelligent sigmoid random early detection controller based on a genetic algorithm is presented to solve the problem of active queue management. In this work, an optimisation theoretic method is used to achieve a better performance in queue management in transmission control protocol networks. A covariance control based on the proposed method is implemented to stabilise and control the fluctuation of the queue length, which in turn results in minimum jitter. The authors illustrate their results with NS2 simulations.

Roya Amjadifard

Papers

Modelling and Control of an Overhead Crane System with a Flexible Cable and Large Swing Angle

Robust Stabilization for a Class of Nonlinear Singularly Perturbed Systems

Using Singular Perturbation Method for Controlling a Crane System with a Flexible Cable and Large Swing Angle

Lip Segmentation Using Geometrical Model of Color Distribution

Genetic-sigmoid random early detection covariance control as a jitter controller