Genetic fuzzy-based steering wheel controller using a mass-produced car

Intelligent Transportation Systems (ITS) cover a broad range of methods and technologies that provide answers to many problems of transportation. Unmanned control of the steering wheel is one of the most important challenges facing researchers in this area. This paper presents a method to adjust automatically a fuzzy controller to manage the steering wheel of a mass-produced vehicle to reproduce the steering of a human driver. To this end, information is recorded about the car's state while being driven by human drivers and used to obtain, via genetic algorithms, appropriate fuzzy controllers that can drive the car in the way that humans do. These controllers have satisfy two main objectives: to reproduce the human behavior, and to provide smooth actions to ensure comfortable driving. Finally, the results of automated driving on a test circuit are presented, showing both good route tracking (similar to the performance obtained by persons in the same task) and smooth driving.

Autonomous Landing of an Unmanned Aerial Vehicle using Image-Based Fuzzy Control

This paper presents a vision based autonomous landing control approach for unmanned aerial vehicles (UAV). The 3D position of an unmanned helicopter is estimated based on the homographies estimated of a known landmark. The translation and altitude estimation of the helicopter against the helipad position are the only information that is used to control the longitudinal, lateral and descend speeds of the vehicle. The control system approach consists in three Fuzzy controllers to manage the speeds of each 3D axis of the aircraft s coordinate system. The 3D position estimation was proven rst, comparing it with the GPS + IMU data with very good results. The robust of the vision algorithm against occlusions was also tested. The excellent behavior of the Fuzzy control approach using the 3D position estimation based in homographies was proved in an outdoors test using a real unmanned helicopter.

Cooperative controllers for highways based on human experience

The AUTOPIA program has been working on the development of intelligent autonomous vehicles for the last 10 years. Its latest advances have focused on the development of cooperative manœuvres based on communications involving several vehicles. However, so far, these manœuvres have been tested only on private tracks that emulate urban environments. The first experiments with autonomous vehicles on real highways, in the framework of the grand cooperative driving challenge (GCDC) where several vehicles had to cooperate in order to perform cooperative adaptive cruise control (CACC), are described. In this context, the main challenge was to translate, through fuzzy controllers, human driver experience to these scenarios. This communication describes the experiences deriving from this competition, specifically that concerning the controller and the system implemented in a Citröen C3.

Detecção de interface em tanques de petróleo usando transmissores de nível e controladores Fuzzy

This work presents a proposal to detect interface in atmospheric oil tanks by installing a differential pressure level transmitter to infer the oil-water interface. The main goal of this project is to maximize the quantity of free water that is delivered to the drainage line by controlling the interface. A Fuzzy Controller has been implemented by using the interface transmitter as the Process Variable. Two ladder routine was generated to perform the control. One routine was developed to calculate the error and error variation. The other was generate to develop the fuzzy controller itself. By using rules, the fuzzy controller uses these variables to set the output. The output is the position variation of the drainage valve. Although the ladder routine was implemented into an Allen Bradley PLC, Control Logix family it can be implemented into any brand of PLCs

Ambiente para avaliação de controladores fuzzy aplicados ao método de elevação artificial por bombeio centrífugo submerso

From their early days, Electrical Submergible Pumping (ESP) units have excelled in lifting much greater liquid rates than most of the other types of artificial lift and developed by good performance in wells with high BSW, in onshore and offshore environments. For all artificial lift system, the lifetime and frequency of interventions are of paramount importance, given the high costs of rigs and equipment, plus the losses coming from a halt in production. In search of a better life of the system comes the need to work with the same efficiency and security within the limits of their equipment, this implies the need for periodic adjustments, monitoring and control. How is increasing the prospect of minimizing direct human actions, these adjustments should be made increasingly via automation. The automated system not only provides a longer life, but also greater control over the production of the well. The controller is the brain of most automation systems, it is inserted the logic and strategies in the work process in order to get you to work efficiently. So great is the importance of controlling for any automation system is expected that, with better understanding of ESP system and the development of research, many controllers will be proposed for this method of artificial lift. Once a controller is proposed, it must be tested and validated before they take it as efficient and functional. The use of a producing well or a test well could favor the completion of testing, but with the serious risk that flaws in the design of the controller were to cause damage to oil well equipment, many of them expensive. Given this reality, the main objective of the present work is to present an environment for evaluation of fuzzy controllers for wells equipped with ESP system, using a computer simulator representing a virtual oil well, a software design fuzzy controllers and a PLC. The use of the proposed environment will enable a reduction in time required for testing and adjustments to the controller and evaluated a rapid diagnosis of their efficiency and effectiveness. The control algorithms are implemented in both high-level language, through the controller design software, such as specific language for programming PLCs, Ladder Diagram language.

REAL TIME FUZZY CONTROLLER FOR QUADROTOR STABILITY CONTROL

In this report, we develop an intelligent adaptive neuro-fuzzy controller by using adaptive neuro fuzzy inference system (ANFIS) techniques. We begin by starting with a standard proportional-derivative (PD) controller and use the PD controller data to train the ANFIS system to develop a fuzzy controller. We then propose and validate a method to implement this control strategy on commercial off-the-shelf (COTS) hardware. An analysis is made into the choice of filters for attitude estimation. These choices are limited by the complexity of the filter and the computing ability and memory constraints of the micro-controller. Simplified Kalman filters are found to be good at estimation of attitude given the above constraints. Using model based design techniques, the models are implemented on an embedded system. This enables the deployment of fuzzy controllers on enthusiast-grade controllers. We evaluate the feasibility of the proposed control strategy in a model-in-the-loop simulation. We then propose a rapid prototyping strategy, allowing us to deploy these control algorithms on a system consisting of a combination of an ARM-based microcontroller and two Arduino-based controllers. We then use a combination of the code generation capabilities within MATLAB/Simulink in combination with multiple open-source projects in order to deploy code to an ARM CortexM4 based controller board. We also evaluate this strategy on an ARM-A8 based board, and a much less powerful Arduino based flight controller. We conclude by proving the feasibility of fuzzy controllers on Commercial-off the shelf (COTS) hardware, we also point out the limitations in the current hardware and make suggestions for hardware that we think would be better suited for memory heavy controllers.

Controlo difuso de um AGV

Neste trabalho pretende-se introduzir os conceitos associados à lógica difusa no controlo de sistemas, neste caso na área da robótica autónoma, onde é feito um enquadramento da utilização de controladores difusos na mesma. Foi desenvolvido de raiz um AGV (Autonomous Guided Vehicle) de modo a se implementar o controlador difuso, e testar o desempenho do mesmo. Uma vez que se pretende de futuro realizar melhorias e/ou evoluções optou-se por um sistema modular em que cada módulo é responsável por uma determinada tarefa. Neste trabalho existem três módulos que são responsáveis pelo controlo de velocidade, pela aquisição dos dados dos sensores e, por último, pelo controlador difuso do sistema. Após a implementação do controlador difuso, procedeu-se a testes para validar o sistema onde foram recolhidos e registados os dados provenientes dos sensores durante o funcionamento normal do robô. Este dados permitiram uma melhor análise do desempenho do robô. Verifica-se que a lógica difusa permite obter uma maior suavidade na transição de decisões, e que com o aumento do número de regras é possível tornar o sistema ainda mais suave. Deste modo, verifica-se que a lógica difusa é uma ferramenta útil e funcional para o controlo de aplicações. Como desvantagem surge a quantidade de dados associados à implementação, tais como, os universos de discurso, as funções de pertença e as regras. Ao se aumentar o número de regras de controlo do sistema existe também um aumento das funções de pertença consideradas para cada variável linguística; este facto leva a um aumento da memória necessária e da complexidade na implementação pela quantidade de dados que têm de ser tratados. A maior dificuldade no projecto de um controlador difuso encontra-se na definição das variáveis linguísticas através dos seus universos de discurso e das suas funções de pertença, pois a definição destes pode não ser a mais adequada ao contexto de controlo e torna-se necessário efectuar testes e, consequentemente, modificações à definição das funções de pertença para melhorar o desempenho do sistema. Todos os aspectos referidos são endereçados no desenvolvimento do AGV e os respectivos resultados são apresentados e analisados.

A fast electric load forecasting using adaptive neural networks

This work presents a procedure for electric load forecasting based on adaptive multilayer feedforward neural networks trained by the Backpropagation algorithm. The neural network architecture is formulated by two parameters, the scaling and translation of the postsynaptic functions at each node, and the use of the gradient-descendent method for the adjustment in an iterative way. Besides, the neural network also uses an adaptive process based on fuzzy logic to adjust the network training rate. This methodology provides an efficient modification of the neural network that results in faster convergence and more precise results, in comparison to the conventional formulation Backpropagation algorithm. The adapting of the training rate is effectuated using the information of the global error and global error variation. After finishing the training, the neural network is capable to forecast the electric load of 24 hours ahead. To illustrate the proposed methodology it is used data from a Brazilian Electric Company. © 2003 IEEE.

A multiagent architecture for supervisory and control system

Supervising and controlling the many processes involved in petroleum production is both dangerous and complex. Herein, we propose a multiagent supervisory and control system for handle continuous processes like those in chemical and petroleum industries In its architeture, there are agents responsible for managing data production and analysis, and also the production equipments. Fuzzy controllers were used as control agents. The application of a fuzzy control system to managing an off-shore installation for petroleum production onto a submarine separation process is described. © 2008 IEEE.

Controle semi-ativo de vibrações usando lógica nebulosa e fluido magnetoreológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Multi-agent location system in wireless networks

In this paper we propose a flexible Multi-Agent Architecture together with a methodology for indoor location which allows us to locate any mobile station (MS) such as a Laptop, Smartphone, Tablet or a robotic system in an indoor environment using wireless technology. Our technology is complementary to the GPS location finder as it allows us to locate a mobile system in a specific room on a specific floor using the Wi-Fi networks. The idea is that any MS will have an agent known at a Fuzzy Location Software Agent (FLSA) with a minimum capacity processing at its disposal which collects the power received at different Access Points distributed around the floor and establish its location on a plan of the floor of the building. In order to do so it will have to communicate with the Fuzzy Location Manager Software Agent (FLMSA). The FLMSAs are local agents that form part of the management infrastructure of the Wi-Fi network of the Organization. The FLMSA implements a location estimation methodology divided into three phases (measurement, calibration and estimation) for locating mobile stations (MS). Our solution is a fingerprint-based positioning system that overcomes the problem of the relative effect of doors and walls on signal strength and is independent of the network device manufacturer. In the measurement phase, our system collects received signal strength indicator (RSSI) measurements from multiple access points. In the calibration phase, our system uses these measurements in a normalization process to create a radio map, a database of RSS patterns. Unlike traditional radio map-based methods, our methodology normalizes RSS measurements collected at different locations on a floor. In the third phase, we use Fuzzy Controllers to locate an MS on the plan of the floor of a building. Experimental results demonstrate the accuracy of the proposed method. From these results it is clear that the system is highly likely to be able to locate an MS in a room or adjacent room.

Aplicación de la energía solar térmica en una incubadora comercial de perdiz roja y supervisión de la actividad biológica mediante sensores inteligentes

La perdiz roja es la especie cinegética por excelencia en la península ibérica, cuya cría en cautividad y suelta controlada comenzó a regularse en los años 70 con la aparición del ICONA. La incubación controlada de huevos de perdiz es imprescindible, con fines cinegéticos y de preservación de la especie, y se desarrolla con incubadoras comerciales de pequeña y mediana escala, distribuidas en zonas rurales con acceso limitado y/o deficiente al suministro eléctrico. En nuestras latitudes el aporte de energía solar térmica se perfila como una posibilidad de mejorar la eficiencia energética de éstas y otras instalaciones y de reducir la dependencia energética exterior. Hay diversos factores físico-químicos que influyen en la calidad de la incubación: temperatura, humedad relativa, y concentración de gases, de los cuales sólo los dos primeros son habitualmente supervisados y controlados en este tipo de incubadoras. Esta Tesis surge en el marco de dos proyectos de cooperación con la AECID, y tiene como objetivos: la caracterización espacial de variables relevantes (temperatura (T), humedad relativa (HR)) en la incubadora comercial durante el proceso de incubación, la determinación de la relación existente entre la evolución de variables ambientales durante el proceso de incubación y la tasa de nacimientos (35-77%), así como el diseño y evaluación del sistema de apoyo solar térmico para determinar su potencial de utilización durante las incubaciones comerciales. La instalación de un número limitado de sensores permite la monitorización precisa del proceso de incubación de los huevos. Los resultados más relevantes indican que en incubaciones comerciales los gradientes de T y HR han sido despreciables (1ºC de diferencia entre las posiciones con mayor y menor T media y un 4,5% de diferencia entre las posiciones con mayor y menor HR), mientras que el seguimiento y ajuste (mediante modelos de crecimiento) de la concentración de CO2 (r2 entre 0,948 y 0,987 en las 5 incubaciones, para un total de 43315 huevos) permite valorar la actividad fisiológica de los huevos e incluso predecir la tasa de éxito (nacimientos), basándose en la concentración de CO2 estimada mediante modelos de crecimiento en el día 20 de incubación (r2 entre 0,997 y 0,994 según el modelo de estimación empleado). El sistema ha sido valorado muy positivamente por los productores (Finca Cinegética Dehesa Vieja de Galapagar). El aporte térmico se ha diseñado (con mínima intrusión en el sistema comercial) sobre la base de un sistema de enfriamiento de emergencia original de la incubadora, al que se han incorporado un colector solar, un depósito, un sistema de electroválvulas, una bomba de circulación y sensores de T en distintos puntos del sistema, y cuyo control ha sido automatizado. En esta Tesis se muestra que la contribución solar puede aportar hasta un 42% de las demandas de energía en nuestras condiciones geográficas para una temperatura de consigna dentro de la incubadora de 36.8ºC, sin afectar a la estabilidad de la temperatura. Además, el rendimiento del colector solar se ha acotado entre un 44% y un 85%, de acuerdo con los cálculos termodinámicos; valores que se mantienen dentro del rango aportado por el fabricante (61%). En el futuro se plantea evaluar el efecto de distintas estrategias de control, tales como controladores difusos, que incorporan el conocimiento experto al control automático. ABSTRACT The partridge is the quintessential game species in the Iberian Peninsula, which controlled breeding and release, began to be regulated in the 70s with the emergence of ICONA. The controlled incubation of eggs is essential, and takes place in commercial incubators of small and medium scale, distributed in rural areas with limited and/or inadequate access to power. In our latitudes the contribution of solar thermal energy is emerging as a possibility to improve the energy efficiency of the facilities and to reduce external energy dependence. There are various physicochemical factors influencing the quality of incubation: temperature, relative humidity and concentration of gases, of which only the first two are typically monitored and controlled in such incubators. This PhD comes within the framework of two cooperation projects with AECID and aims: the spatial characterization of relevant variables in a commercial incubator (temperature (T), and relative humidity (HR)), determining the relationships in the changes in environmental variables during incubation and birth rates (35-77%) as well as the design and evaluation of solar thermal support system to determine its potential use during commercial incubations; the installation of a limited number of sensors has allowed accurate monitoring of incubation of eggs. The most relevant results indicate that in commercial incubations, the gradients in T and HR have been negligible (1°C difference between the highest and lowest positions T and average 4.5% difference between the highest and lowest positions HR), while monitoring and fit using growth models of the concentration of CO2 (r2 between 0.948 and 0.987 in 5 incubations, for a total amount of 43,315 eggs) allows assessing the physiological activity of the eggs and even predict the success rate (hatchability), based on the estimated concentration of CO2 by using growth models on day 20 of incubation (r2 between 0.997 and 0.994 depending on the fit model).The system has been highly valued by producers (Finca Cinegética Dehesa Vieja de Galapagar). The hybrid heat system is designed (with minimal intrusion into the commercial system) based on an emergency cooling device, original in the incubator. New elements have been incorporated: a solar collector, a tank, a system of solenoid valves, a circulating pump and T sensors at various points of the system, whose control has been automated. This PhD shows that the solar contribution is responsible for up to 42% of energy demands in our geographical conditions for a setpoint temperature inside the incubator of 36.8ºC, without questioning the stability of the temperature. Furthermore, the efficiency of the solar collector has been bounded between 44% and 85%, according to thermodynamic calculations; values remain within the range provided by the manufacturer (61%). In the future it is proposed to evaluate the effect of different control strategies, such as fuzzy controllers, which incorporate the expertise to automated control.

Fuzzy linguistic controllers applied to decouple control loop effects

A fuzzy linguistic controller has been developed and implemented with the aim to cope with interactions between control loops due to coupling effects. To access the performance of the proposed approach several experiments have also been conducted using the classical PID controllers in the control loops. A mixing process has been used as test bed of all controllers experimented and the corresponding dynamic model has been derived. The successful results achieved with the fuzzy linguistic controllers suggests that they can be an alternative to classical controllers when in the presence of process plants where automatic control as to cope with coupling effects between control loops. © 2014 IEEE.

Comparing fuzzy and intelligent PI controllers in stop-and-go manoeuvres

The aim of this work was twofold: on the one hand, to describe a comparative study of two intelligent control techniques-fuzzy and intelligent proportional-integral (PI) control, and on the other, to try to provide an answer to an as yet unsolved topic in the automotive sector-stop-and-go control in urban environments at very low speeds. Commercial vehicles exhibit nonlinear behavior and therefore constitute an excellent platform on which to check the controllers. This paper describes the design, tuning, and evaluation of the controllers performing actions on the longitudinal control of a car-the throttle and brake pedals-to accomplish stop-and-go manoeuvres. They are tested in two steps. First, a simulation model is used to design and tune the controllers, and second, these controllers are implemented in the commercial vehicle-which has automatic driving capabilities-to check their behavior. A stop-and-go manoeuvre is implemented with the two control techniques using two cooperating vehicles.

Fuzzy pole placement based on piecewise Lyapunov functions

This paper presents a controller design method for fuzzy dynamic systems based on piecewise Lyapunov functions with constraints on the closed-loop pole location. The main idea is to use switched controllers to locate the poles of the system to obtain a satisfactory transient response. It is shown that the global fuzzy system satisfies the requirements for the design and that the control law can be obtained by solving a set of linear matrix inequalities, which can be efficiently solved with commercially available softwares. An example is given to illustrate the application of the proposed method. Copyright (C) 2009 John Wiley & Sons, Ltd.