Fourier Transform

The application of Fourier transform (FT) in signal processing and physical sciences has increased in the past decades. Almost all the textbooks on signal processing or physics have a section devoted to the FT theory. For this reason, this book focuses on signal processing and physical sciences. The book chapters are related to fast hybrid recursive FT based on Jacket matrix, acquisition algorithm for global navigation satellite system, determining the sensitivity of output parameters based on FFT, convergence of integrals of products based on Riemann-Lebesgue Lemma function, extending the real and complex number fields for treating the FT, nonmaterial structure, Gabor transform, and chalcopyrite bioleaching. The book provides applications oriented to signal processing and physics written primarily for engineers, mathematicians, physicians and graduate students, will also find it useful as a reference for their research activities

Performance Analysis of Batch Reactor Temperature Control Systems

The aim of this project was to investigate the performance of a number of key control strategies in the temperature control of batch reactors. A bench scale model was built and a batch production system was then implemented on this model. As there was no a priori knowledge of the system a number of common system identification methods were investigated. The system was controlled using a Mitsubishi FX(2)N Programmable Logic Controller which was interfaced with a PC running ICONICS, a Supervisory Control And Data Acquisition software package. The system identification methods produced two different models for the system and these models were examined against the actual system using Matlab/SIMULINK, a software package used for technical computing. Then a number of tuning rules were investigated and implemented on both models with the results compared and contrasted. The standard Industry criteria were used to compare the performance of the servo response for each controller. The PI controller using Zeigler-Nichols tuning rules was set as the bench mark. The Cascaded control strategy offered no increase in performance in the servo response in either the actual process or the SIMULINK models. However the regulatory response of the Cascaded strategy would offer an improvement on the performance of the PI controller. The performance of the Smith Predictor was limited due to the minimal time delay relative to the time constant. The Integrating method proved to offer an improvement on the two point method in terms of system performance and in the time required to identify the initial controller. Also the Smith Predictor offered a slight improvement in both the laboratory model and in the Matlab/SIMULINK simulations

Enabling garment-agnostic laundry tasks for a Robot Household Companion

Domestic chores, such as laundry tasks, are dull and repetitive. These tasks consume a significant amount of daily time, and are however unavoidable. Additionally, a great portion of elder and disabled people require help to perform them due to lack of mobility. In this work we present advances towards a Robot Household Companion (RHC), focusing on the performance of two particular laundry tasks: unfolding and ironing garments. Unfolding is required to recognize the garment prior to any later folding operation. For unfolding, we apply an interactive algorithm based on the analysis of a colored 3D reconstruction of the garment. Regions are clustered based on height, and a bumpiness value is computed to determine the most suitable pick and place points to unfold the overlapping region. For ironing, a custom Wrinkleness Local Descriptor (WiLD) descriptor is applied to a 3D reconstruction to find the most significant wrinkles in the garment. These wrinkles are then ironed using an iterative path-following control algorithm that regulates the amount of pressure exerted on the garment. Both algorithms focus on the feasibility of a physical implementation in real unmodified environments. A set of experiments to validate the algorithms have been performed using a full-sized humanoid robot.This work was supported by RoboCity2030-III-CM project (S2013/MIT-2748), funded by Programas de Actividades I+D in Comunidad de Madrid, Spain and EU and by a FPU grant funded by Ministerio de Educación, Cultura y Deporte, Spain. It was also supported by the anonymous donor of a red hoodie used in our initial trials. We gratefully acknowledge the support of NVIDIA, United States Corporation with the donation of the NVIDIA Titan X GPU used for this research