Hybrid Nonlinear MPC of a Solar Cooling Plant

Solar energy for cooling systems has been widely used to fulfill the growing air conditioning demand. The advantage of this approach is based on the fact that the need of air conditioning is usually well correlated to solar radiation. These kinds of plants can work in different operation modes resulting on a hybrid system. The control approaches designed for this kind of plant have usually a twofold goal: (a) regulating the outlet temperature of the solar collector field and (b) choosing the operation mode. Since the operation mode is defined by a set of valve positions (discrete variables), the overall control problem is a nonlinear optimization problem which involves discrete and continuous variables. This problems are difficult to solve within the normal sampling times for control purposes (around 20–30 s). In this paper, a two layer control strategy is proposed. The first layer is a nonlinear model predictive controller for regulating the outlet temperature of the solar field. The second layer is a fuzzy algorithm which selects the adequate operation mode for the plant taken into account the operation conditions. The control strategy is tested on a model of the plant showing a proper performance.Unión Europea OCONTSOLAR ID 78905

Engineering Emergence: A Survey on Control in the World of Complex Networks

Complex networks make an enticing research topic that has been increasingly attracting researchers from control systems and various other domains over the last two decades. The aim of this paper was to survey the interest in control related to complex networks research over time since 2000 and to identify recent trends that may generate new research directions. The survey was performed for Web of Science, Scopus, and IEEEXplore publications related to complex networks. Based on our findings, we raised several questions and highlighted ongoing interests in the control of complex networks.publishedVersio

Solar Energy Dependent Supercapacitor System with ANFIS Controller for Auxiliary Load of Electric Vehicles

Innovations are required for electric vehicles (EVs) to be lighter and more energy efficient due to the range anxiety issue. This article introduces an intelligent control of an organic structure solar supercapacitor (OSSC) for EVs to meet electrical load demands with solar renewable energy. A carbon fibreȬreinforced polymer, nano zinc oxide (ZnO), and copper oxide (CuO) fillers have been used in the development of OSSC prototypes. The organic solar cell, electrical circuits, converter, controller, circuit breaker switch, and batteries were all integrated for the modelling of OSSCs. A carbon fibre (CF)Ȭreinforced CuOȬdoped polymer was utilised to improve the concentration of elecȬ trons. The negative electrodes of the CF were strengthened with nano ZnO epoxy to increase the mobility of electrons as an nȬtype semiconductor (energy band gap 3.2–3.4 eV) and subsequently increased to 3.5 eV by adding 6%ȱΔȬcarbon. The electrodes of the CF were strengthened with epoxyȬ filled nanoȬCuO as a pȬtype semiconductor to facilitate bore/positive charging. They improve the conductivity of the OSSC. The OSSC power storage was controlled by an adaptive neuroȬfuzzy inȬ telligent system controller to meet the load demand of EVs and auxiliary battery charging. MoreoȬ ver, a fully charged OSSC (solar irradiance = 1000 W/m2) produced 561 Wȉh/m2 to meet the vehicle load demand with 45 A of auxiliary battery charging current. Therefore, the OSSC can save 15% in energy efficiency and contribute to emission control. The integration of an OSSC with an EV battery can minimise the weight and capacity of the battery by 7.5% and 10%, respectively

Virtual Structure Based Formation Tracking of Multiple Wheeled Mobile Robots: An Optimization Perspective

Today, with the increasing development of science and technology, many systems need to be optimized to find the optimal solution of the system. this kind of problem is also called optimization problem. Especially in the formation problem of multi-wheeled mobile robots, the optimization algorithm can help us to find the optimal solution of the formation problem. In this paper, the formation problem of multi-wheeled mobile robots is studied from the point of view of optimization. In order to reduce the complexity of the formation problem, we first put the robots with the same requirements into a group. Then, by using the virtual structure method, the formation problem is reduced to a virtual WMR trajectory tracking problem with placeholders, which describes the expected position of each WMR formation. By using placeholders, you can get the desired track for each WMR. In addition, in order to avoid the collision between multiple WMR in the group, we add an attraction to the trajectory tracking method. Because MWMR in the same team have different attractions, collisions can be easily avoided. Through simulation analysis, it is proved that the optimization model is reasonable and correct. In the last part, the limitations of this model and corresponding suggestions are given

Underwater Pipeline Leakage Detection Using Vision Based Techniques: Semi-AUV (SAUV) Approach

This thesis intends to convert a Remote Operated Vehicle (ROV) to a Semi-Autonomous Underwater Vehicle (SAUV) using a vision-based control system. The SAUV was used for automatic underwater gas pipeline tracking and leakage detection. the leakages in the pipeline using Computer Vision. The SAUV was designed to operate both manually and automatically in underwater conditions. The proposed SAUV has 6 thrusters to achieve 4 degrees of freedom controlled by the controller unit and powered by LiPo battery packs. Our underwater vehicle is equipped with sensors providing continuous feedback signals to automatically control the vehicle to track predefined trajectories. The SAUV can be self-stabilized as the center of gravity and center of buoyancy of the vehicle is positioned in such a way in the predefined plan. The SAUV captures images to perform line tracking along with the pipeline and gas bubble images during its mission. The multi-core umbilical cable is used here for the video signal, the feedback signal, and battery charging lines. This will be used only for development and test purposes and will be removed during autonomous missions. For performing all operations, various control schemes such as computer vision algorithm for object detection using python programming, OpenCV, Hough Transform Theory, etc. are applied. The proposed SAUV is expected to pave the way for the development of advanced underwater oil and gas pipeline industrial applications by ocean scientists

Hidden Markov Model-based Methods In Condition Monitoring of Machinery Systems

Ph.DDOCTOR OF PHILOSOPH

Optimal Control of Hybrid Systems and Renewable Energies

This book is a collection of papers covering various aspects of the optimal control of power and energy production from renewable resources (wind, PV, biomass, hydrogen, etc.). In particular, attention is focused both on the optimal control of new technologies and on their integration in buildings, microgrids, and energy markets. The examples presented in this book are among the most promising technologies for satisfying an increasing share of thermal and electrical demands with renewable sources: from solar cooling plants to offshore wind generation; hybrid plants, combining traditional and renewable sources, are also considered, as well as traditional and innovative storage systems. Innovative solutions for transportation systems are also explored for both railway infrastructures and advanced light rail vehicles. The optimization and control of new solutions for the power network are addressed in detail: specifically, special attention is paid to microgrids as new paradigms for distribution networks, but also in other applications (e.g., shipboards). Finally, optimization and simulation models within SCADA and energy management systems are considered. This book is intended for engineers, researchers, and practitioners that work in the field of energy, smart grid, renewable resources, and their optimization and control