Vicente Feliu-Batlle

Bio: Vicente Feliu-Batlle is an academic researcher from University of Castilla–La Mancha. The author has contributed to research in topics: PID controller & Control theory. The author has an hindex of 16, co-authored 66 publications receiving 1050 citations. Previous affiliations of Vicente Feliu-Batlle include Ferdowsi University of Mashhad.

Direct continuous-time system identification of the purification process of the nimotuzumab, a humanized monoclonal antibody

Abstract: In this paper by applying the direct continuous-time system identification methods an accurate and reliable control oriented model of the conductivity in the polishing phase of the purification process of the nimotuzumab, a monoclonal antibody, is derived A brief introduction to the theoretical aspects of the direct continuous-time system identification methods is presented The complete direct system identification procedure, from the design of the experiment to model validation is developed For this purpose, the CONTSID toolbox is used The model validation results show that the model obtained reproduces with high accuracy the observed data, and therefore it can be used in the design of control systems and/or for prediction purposes

Adaptive Sliding Mode Impedance Control of Single-Link Flexible Manipulators interacting with the Environment at an Unknown Intermediate Point

Abstract: This paper proposes an adaptive robust impedance control for a single-link flexible arm when it encounters an environment at an unknown intermediate point. First, the intermediate collision point is estimated using a collision detection algorithm. The controller, then, switches from free to constrained motion mode. In the unconstrained motion mode, the exerted force to environment is nearly zero. Thus, the reference trajectory is a prescribed desired trajectory in position control. In the constrained motion mode, the reference trajectory is determined by the desired target dynamic impedance. The simulation results demonstrate the efficiency of proposed control scheme.

Image Processing

Abstract: MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

Linear systems

Abstract: 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:

Art of electronics

Abstract: Our goal is always to offer you an assortment of cost-free ebooks too as aid resolve your troubles. We have got a considerable collection of totally free of expense Book for people from every single stroll of life. We have got tried our finest to gather a sizable library of preferred cost-free as well as paid files. Whatever our proffesion, the art of electronics can be excellent resource for reading. Find the existing reports of word, txt, kindle, ppt, zip, pdf, as well as rar in this site. You can definitely check out online or download this book by below. Currently, never miss it. This is really going to save you time and your money in something should think about. If you're seeking then search around for online. Without a doubt there are several these available and a lot of them have the freedom. However no doubt you receive what you spend on. An alternate way to get ideas would be to check another the art of electronics. GO TO THE TECHNICAL WRITING FOR AN EXPANDED TYPE OF THIS THE ART OF ELECTRONICS, ALONG WITH A CORRECTLY FORMATTED VERSION OF THE INSTANCE MANUAL PAGE ABOVE.