Development of a MATLAB/Simulink - Arduino environment for experimental practices in control engineering teaching

This project presents the steps followed when implementing a platform based on MATLAB/Simulink and Arduino for the restoration of digital control practices. During this project, an Arduino shield has being designed. Along with this, a web page has also been created where all the material done during all this project is available and can be freely used. So anyone interested on doing a project can have a starting point instead of starting a project from scratch, which most of times this results hard to implement. Taking all this into account, the document is structured in the following manner. The first chapter talks about the hardware used and designed. The second one explains the software used and the configurations done on the laboratory’s PCs. After that, the web page Duino-Based Learning is explained, where you can find the five projects carried out in the "Control Automàtic" subject with their corresponding results. In this section too, as an additional research, the implemented indirect adaptive control will be explained, where the parameter estimation has been done by the Recursive Least Square algorithm. The last four sections before presenting the conclusions of the work, correspond to a satisfaction questionnaire done to the teachers that have used the setup, the costs and saves of the project, the environmental impact and the planning of the project respectively

Design and Implementation of Takagi-Sugeno Fuzzy Tracking Control for a DC-DC Buck Converter

This paper presents the design and implementation of a Takagi-Sugeno (T-S) fuzzy controller for a DC-DC buck converter using Arduino board. The proposed fuzzy controller is able to pilot the states of the buck converter to track a reference model. The T-S fuzzy model is employed, firstly, to represent exactly the dynamics of the nonlinear buck converter system, and then the considered controller is designed on the basis of a concept called Virtual Desired Variables (VDVs). In this case, a two-stage design procedure is developed: i) determine the reference model according to the desired output voltage, ii) determine the fuzzy controller gains by solving a set of Linear Matrix Inequalities (LMIs). A digital implementation of the proposed T-S fuzzy controller is carried out using the ATmega328P-based Microcontroller of the Arduino Uno board. Simulations and experimental results demonstrate the validity and effectiveness of the proposed control scheme

Power Flow Modelling of Dynamic Systems - Introduction to Modern Teaching Tools

As tools for dynamic system modelling both conventional methods such as transfer function or state space representation and modern power flow based methods are available. The latter methods do not depend on energy domain, are able to preserve physical system structures, visualize power conversion or coupling or split, identify power losses or storage, run on conventional software and emphasize the relevance of energy as basic principle of known physical domains. Nevertheless common control structures as well as analysis and design tools may still be applied. Furthermore the generalization of power flow methods as pseudo-power flow provides with a universal tool for any dynamic modelling. The phenomenon of power flow constitutes an up to date education methodology. Thus the paper summarizes fundamentals of selected power flow oriented modelling methods, presents a Bond Graph block library for teaching power oriented modelling as compact menu-driven freeware, introduces selected examples and discusses special features.Comment: 12 pages, 9 figures, 4 table

Model-based dependability analysis : state-of-the-art, challenges and future outlook

Abstract: Over the past two decades, the study of model-based dependability analysis has gathered significant research interest. Different approaches have been developed to automate and address various limitations of classical dependability techniques to contend with the increasing complexity and challenges of modern safety-critical system. Two leading paradigms have emerged, one which constructs predictive system failure models from component failure models compositionally using the topology of the system. The other utilizes design models - typically state automata - to explore system behaviour through fault injection. This paper reviews a number of prominent techniques under these two paradigms, and provides an insight into their working mechanism, applicability, strengths and challenges, as well as recent developments within these fields. We also discuss the emerging trends on integrated approaches and advanced analysis capabilities. Lastly, we outline the future outlook for model-based dependability analysis