Relevant bibliographies by topics / Automated fuzzy controllers

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Automated fuzzy controllers'

Author: Grafiati
Published: 4 June 2021
Last updated: 4 February 2022

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Journal articles on the topic "Automated fuzzy controllers"

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Kropyvnytska, V. B., O. V. Yefremov, and H. N. Sementsov. "The improvement of the method for developing the knowledge data base for the intelligent support system of decision making on the Fuzzy Logic principles." Oil and Gas Power Engineering, no. 1(29) (April 30, 2018): 26–41. http://dx.doi.org/10.31471/1993-9868-2018-1(29)-26-41.

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The article deals with the issue of Fuzzy-simulation of controllers for solving practical problems of automated control. The peculiarities of Fuzzy-simulation of cascade controllers in the Matlab environment are studied. The presentation is accompanied by examples of the development of individual Fuzzy models and an illustration of conducting all necessary operations with fuzzy sets.
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Kharola, Ashwani, and Pravin P. Patil. "Automated Control and Optimisation of Overhead Cranes." International Journal of Manufacturing, Materials, and Mechanical Engineering 7, no. 3 (July 2017): 41–68. http://dx.doi.org/10.4018/ijmmme.2017070103.

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This study considers a fuzzy based computing technique for control and optimising performance of overhead gantry crane. The objective is to minimise load swing and stabilise crane position in the least possible time. The fuzzy controllers were designed using nine gaussian and triangular shape membership functions. The results clearly confirmed the effect of shape of memberships on performance of fuzzy controllers. Performance of overhead crane was measured in terms of settling time and overshoot. The study also demonstrates the influence of varying mass of the load, mass of crane and length of crane bar on stability of the crane. A mathematical model of the crane system has been derived to develop a simulink model of proposed system and performing simulations.
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Kato, Shigeru, and Kok Wai Wong. "Intelligent Automated Guided Vehicle Controller with Reverse Strategy." Journal of Advanced Computational Intelligence and Intelligent Informatics 15, no. 3 (May 20, 2011): 304–12. http://dx.doi.org/10.20965/jaciii.2011.p0304.

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This paper describes the intelligent Automated Guided Vehicle (AGV) control system using Fuzzy Rule Interpolation (FRI) method. The AGV used in this paper is a virtual vehicle simulated using computer. The purpose of the control system is to control the simulated AGV by moving along the given path towards a goal. Some obstacles can be placed on or near the path to increase the difficulties of the control system. The intelligent AGV should follow the path by avoiding these obstacles. This system consists of two fuzzy controllers. One is the original FRI controller that mainly controls the forward movement of the AGV. Another one is the proposed reverse movement controller that deals with the critical situation. When the original FRI controller faces the critical situation, our proposed reverse controller will control the AGV to reverse and move forward towards the goal. Our proposed reverse controller utilizes the advantage of FRI method. In our system, we also develop a novel switching system to switch from original to the developed reverse controller.
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Vesselenyi, Tiberiu, Simona Dzițac, Ioan Dzițac, and Mișu-Jan Manolescu. "Fuzzy and Neural Controllers for a Pneumatic Actuator." International Journal of Computers Communications & Control 2, no. 4 (December 1, 2007): 375. http://dx.doi.org/10.15837/ijccc.2007.4.2368.

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There is a great diversity of ways to use fuzzy inference in robot control systems, either in the place where it is applied in the control scheme or in the form or type of inference algorithms used. On the other hand, artificial neural networks ability to simulate nonlinear systems is used in different researches in order to develop automated control systems of industrial processes. In these applications of neural networks, there are two important steps: system identification (development of neural process model) and development of control (definition of neural control structure). In this paper we present some modelling applications, which uses fuzzy and neural controllers, developed on a pneumatic actuator containing a force and a position sensor, which can be used for robotic grinding operations. Following the simulation one of the algorithms was tested on an experimental setup. The paper also presents the development of a NARMA-L2 neural controller for a pneumatic actuator using position feedback. The structure had been trained and validated, obtaining good results.
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Karar, Mohamed E., and Mohamed A. El-Brawany. "Automated Cardiac Drug Infusion System Using Adaptive Fuzzy Neural Networks Controller." Biomedical Engineering and Computational Biology 3 (January 2011): BECB.S6495. http://dx.doi.org/10.4137/becb.s6495.

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This paper presents a fuzzy neural network (FNN) control system to automatically manage the hemodynamic variables of patients with hypertension and congestive heart failure (CHF) via simultaneous infusion of cardiac drugs such as vasodilators and inotropic agents. The developed system includes two FNN sub-controllers for regulating cardiac output (CO) and mean arterial pressure (MAP) by cardiac drugs, considering interactive pharmacological effects. The adaptive FNN controller was tested and evaluated on a cardiovascular model. Six short-term therapy conditions of hypertension and CHF are presented under different sensitivities of a vasodilator drug. The results of the automated system showed that root mean square errors were ≤ 5.56 mmHg and ≤ 0.22 L min-1 for regulating MAP and CO, respectively, providing short settling time responses of MAP (≤ 10.9 min) and CO (≤ 8.22 min) in all therapy conditions. The proposed FNN control scheme can significantly improve the performance of cardiac drug infusion System.
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Shahsavari Pour, N., H. Asadi, and M. Pour Kheradmand. "Fuzzy Multiobjective Traffic Light Signal Optimization." Journal of Applied Mathematics 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/249726.

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Traffic congestion is a major concern for many cities throughout the world. In a general traffic light controller, the traffic lights change at a constant cycle time. Hence it does not provide an optimal solution. Many traffic light controllers in current use are based on the “time-of-the-day” scheme, which use a limited number of predetermined traffic light patterns and implement these patterns depending upon the time of the day. These automated systems do not provide an optimal control for fluctuating traffic volumes. In this paper, the fuzzy traffic light controller is used to optimize the control of fluctuating traffic volumes such as oversaturated or unusual load conditions. The problem is solved by genetic algorithm, and a new defuzzification method is introduced. The performance of the new defuzzification method (NDM) is compared with the centroid point defuzzification method (CPDM) by using ANOVA. Finally, an illustrative example is presented to show the competency of proposed algorithm.
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Miraftab, V., and R. R. Mansour. "Fully Automated RF/Microwave Filter Tuning by Extracting Human Experience Using Fuzzy Controllers." IEEE Transactions on Circuits and Systems I: Regular Papers 55, no. 5 (June 2008): 1357–67. http://dx.doi.org/10.1109/tcsi.2008.916614.

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Batayneh, Wafa, and Yusra AbuRmaileh. "Decentralized Motion Control for Omnidirectional Wheelchair Tracking Error Elimination Using PD-Fuzzy-P and GA-PID Controllers." Sensors 20, no. 12 (June 22, 2020): 3525. http://dx.doi.org/10.3390/s20123525.

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The last decade observed a significant research effort directed towards maneuverability and safety of mobile robots such as smart wheelchairs. The conventional electric wheelchair can be equipped with motorized omnidirectional wheels and several sensors serving as inputs for the controller to achieve smooth, safe, and reliable maneuverability. This work uses the decentralized algorithm to control the motion of omnidirectional wheelchairs. In the body frame of the omnidirectional wheeled wheelchair there are three separated independent components of motion including rotational motion, horizontal motion, and vertical motion, which can be controlled separately. So, each component can have its different sub-controller with a minimum tracking error. The present work aims to enhance the mobility of wheelchair users by utilizing an application to control the motion of their attained/unattained smart wheelchairs, especially in narrow places and at hard detours such as 90˚ corners and U-turns, which improves the quality of life of disabled users by facilitating their wheelchairs’ maneuverability. Two approaches of artificial intelligent-based controllers (PD-Fuzzy-P and GA-PID controllers) are designed to optimally enhance the maneuverability of the system. MATLAB software is used to simulate the system and calculate the Mean Error (ME) and Mean Square Error (MSE) for various scenarios in both approaches, the results showed that the PD-Fuzzy-P controller has a faster convergence in trajectory tracking than the GA-PID controller. Therefore, the proposed system can find its application in many areas including transporting locomotor-based disabled individuals and geriatric people as well as automated guided vehicles.
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Dayev, Zh A., G. E. Shopanova, and B. A. Toksanbayeva. "Experience of fuzzy sets organizing on programmable logic controllers for developing automated control systems." Automation, Telemechanization and Communication in Oil Industry, no. 8 (2020): 45–49. http://dx.doi.org/10.33285/0132-2222-2020-8(565)-45-49.

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Mashadi, B., A. Kazemkhani, and R. Baghaei Lakeh. "An automatic gear-shifting strategy for manual transmissions." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 221, no. 5 (August 1, 2007): 757–68. http://dx.doi.org/10.1243/09596518jsce253.

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Based on two different criteria, namely the engine working conditions and the driver's intention, the governing parameters in decision making for gear shifting of an automated manual transmission are discussed. The gear-shifting strategy was designed by taking into consideration the effects of these parameters, with the application of a fuzzy control method. The controller structure is formed in two layers. In the first layer, two fuzzy inference modules are used to determine the necessary outputs. In the second layer a fuzzy inference module makes the decision of shifting by upshift, downshift, or maintain commands. The behaviour of the fuzzy controller is examined by making use of ADVISOR software. It is shown that at different driving conditions the controllers make correct decisions for gear shifting accounting for the dynamic requirements of the vehicle. It is also shown that the controller based on both the engine state and the driver's intention eliminates unnecessary shiftings that are present when the intention is overlooked. A microtrip is designed in which a required speed in the form of a step function is demanded for the vehicle on level or sloping roads. Both strategies for the vehicle to reach the maximum speed starting from rest allow the gear shift to be made consecutively. Considerable differences are observed between the two strategies in the deceleration phase. The engine-state strategy is less sensitive to downshift, taking even unnecessary upshift decisions. The state intention strategy, however, interprets the driver's intention correctly for decreasing speed and utilizes engine brake torque to reduce the vehicle speed in a shorter time.
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Dissertations / Theses on the topic "Automated fuzzy controllers"

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Hugo, Etienne Martin. "Automated design of multi-mode fuzzy controllers." Thesis, Stellenbosch : Stellenbosch University, 2000. http://hdl.handle.net/10019.1/51631.

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Dissertation (PhD)--University of Stellenbosch, 2000.
ENGLISH ABSTRACT: A standard fuzzy logic controller is not robust enough to guarantee consistent closed-loop performance for highly non-linear plants. A finely tuned closed-loop response loses relevance as the system dynamics change with operating conditions. The self-adaptive fuzzy logic controller can track changes in the system parameters and modify the controller parameters accordingly. In most cases, self-adaptive fuzzy logic controllers are complex and rely on some form of mathematical plant model. The multi-mode fuzzy logic controller extends the working range of a standard fuzzy logic controller by incorporating knowledge of the non-linear system dynamics into the control rule-base. The complexity of the controller and difficulty in finding control rules have limited the application of multi-mode fuzzy logic controllers. An automated design algorithm is proposed for the design of a multi-mode control rule-base using qualitative plant knowledge. The design algorithm is cost function-based. The closed-loop response, local to a domain of the non-linear state space, can be tuned by manipulation of the cost function weights. Global closed-loop response tuning can be done by manipulation of the controller input gains. Alternatively, a self-learning or self-adaptive algorithm can be used in a model reference adaptive control architecture to optimise the control rule-base. Control rules responsible for unacceptable closed-loop performance are identified and their consequences modified. The validity of the proposed design method is evaluated in five case studies. The case studies illustrate the advantages of the multi-mode fuzzy logic controller. The results indicate that the proposed self-adaptive algorithm can be used to optimise a rule-base given a required closed-loop specification. If the system does not conform to the model reference adaptive architecture then the intuitive nature of the cost function based design algorithm proves to be an effective method for rule-base tuning.
AFRIKAANSE OPSOMMING: Standaard wasige logika beheerders is nie noodwendig robuust genoeg om goeie geslote lus werkverrigting vir hoogs nie-liniere aanlegte te waarborg nie. In Perfek ge-optimeerde beheerder se geslote lus werkverrigting mag verswak indien die aanleg-parameters weens bedryfstoestande verander. Self-aanpassende beheerders kan die verandering in die aanleg-parameters volg en die beheerder dienooreenkomstig optimeer. As In reël is In self-aanpassende beheerder kompleks en afhanklik van In wiskundige model van die aanleg. Die multi-modus wasige logika beheerder vergroot die werksbereik van die standaard wasige logika beheerder deur kennis aangaande die stelsel se bedryfstoestand en stelselparameters in die reël-basis in te bou. Die aanwending van die multi-modus beheerder word tans beperk deur die struktuur kompleksiteit en moeilike optimering van die reël-basis. In Ge-outomatiseerde multi-modus reël-basis ontwerps-algoritme wat gebruik maak van kwalitatiewe kennis van die aanleg en In kostefunksie word in hierdie proefskrif voorgestel. Die geslote lus gedrag beperk tot In gebied in die toestands-ruimte kan ge-optimeer word deur die kostefunksie gewigte te manipuleer. Die globale werkverrigting kan ge-optimeer word met die beheerder intree aanwinste. In Self-aanpassende algoritme in In model-verwysings aanpassende argitektuur word as altematieftot reël-basis optimering voorgestel. Reëls verantwoordelik vir swak werkverrigting word ge-identifiseer en verbeter deur modifikasie van die reëls se gevolgtrekkings. Die voorgestelde ontwerps-metode word deur middel van vyf gevallestudies ondersoek. Die studies dui die voordele van die multi-modus struktuur aan. Die self-aanpassende argitektuur is In kragtige hulpbron om In reël-basis te optimeer vir In gegewe geslote lus spesifikasie. Hierdie proefskrif toon aan dat indien die stelsel nie aan die vereistes van In model verwysingstelsel voldoen nie, is die kostefunksie benadering tot reël-basis ontwerp In aantreklike en intuïtief verstaanbare opsie om die reël-basis te optimeer.
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Danishvar, Morad. "Modelling and design of the eco-system of causality for real-time systems." Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/12105.

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The purpose of this research work is to propose an improved method for real-time sensitivity analysis (SA) applicable to large-scale complex systems. Borrowed from the EventTracker principle of the interrelation of causal events, it deploys the Rank Order Clustering (ROC) method to automatically group every relevant system input to parameters that represent the system state (i.e. output). The fundamental principle of event modelling is that the state of a given system is a function of every acquirable piece of knowledge or data (input) of events that occur within the system and its wider operational environment unless proven otherwise. It therefore strives to build the theoretical and practical foundation for the engineering of input data. The event modelling platform proposed attempts to filter unwanted data, and more importantly, include information that was thought to be irrelevant at the outset of the design process. The underpinning logic of the proposed Event Clustering technique (EventiC) is to build causal relationship between the events that trigger the inputs and outputs of the system. EventiC groups inputs with relevant corresponding outputs and measures the impact of each input variable on the output variables in short spans of time (relative real-time). It is believed that this grouping of relevant input-output event data by order of its importance in real-time is the key contribution to knowledge in this subject area. Our motivation is that components of current complex and organised systems are capable of generating and sharing information within their network of interrelated devices and systems. In addition to being an intelligent recorder of events, EventiC could also be a platform for preliminary data and knowledge construction. This improvement in the quality, and at times the quantity of input data, may lead to improved higher level mathematical formalism. It is hoped that better models will translate into superior controls and decision making. It is therefore believed that the projected outcome of this research work can be used to predict, stabilize (control), and optimize (operational research) the work of complex systems in the shortest possible time. For proof of concept, EventiC was designed using the MATLAB package and implemented using real-time data from the monitoring and control system of a typical cement manufacturing plant. The purpose for this deployment was to test and validate the concept, and to demonstrate whether the clusters of input data and their levels of importance against system performance indicators could be approved by industry experts. EventiC was used as an input variable selection tool for improving the existing fuzzy controller of the plant. Finally, EventiC was compared with its predecessor EventTracker using the same case study. The results revealed improvements in both computational efficiency and the quality of input variable selection.
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Swartz, Andre Michael. "Methods for designing and optimizing fuzzy controllers." Thesis, Rhodes University, 2000. http://hdl.handle.net/10962/d1005226.

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We start by discussing fuzzy sets and the algebra of fuzzy sets. We consider some properties of fuzzy modeling tools. This is followed by considering the Mamdani and Sugeno models for designing fuzzy controllers. Various methods for using sets of data for desining controllers are discussed. This is followed by a chapter illustrating the use of genetic algorithms in designing and optimizing fuzzy controllers.Finally we look at some previous applications of fuzzy control in telecommunication networks, and illustrate a simple application that was developed as part of the present work.
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McCrate, Mark P. "Modern Mechanical Automata." University of Cincinnati / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1291146053.

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Fifarek, Aaron W. "Examination of Gain Scheduling and Fuzzy Controllers with Hybrid Reachability." Wright State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=wright1547498667336372.

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Birkin, Philip. "A novel dual surface type-2 fuzzy logic controller for a micro robot." Thesis, University of Nottingham, 2010. http://eprints.nottingham.ac.uk/12544/.

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Over the last few years there has been an increasing interest in the area of type-2 fuzzy logic sets and systems in academic and industrial circles. Within robotic research the majority of type-2 fuzzy logic investigations has been centred on large autonomous mobile robots, where resource availability (memory and computing power) is not an issue. These large robots usually have a variation of a Unix operating system on board. This allows the implementation of complex fuzzy logic systems to control the motors. Specifically the implementation of interval and geometric type-2 fuzzy logic controllers is of interest as they are shown to outperform type-1 fuzzy logic controllers in uncertain environments. However when it comes to using micro robots it is not practical to use type-1 and type-2 fuzzy logic controllers, due to the lack of memory and the processor time needed to calculate a control output value. The choice of motor controller is usually either fixed pre-set values, a variable scaled value or a PID controller to generate wheel velocities. In this research novel ways of implementing type-1 and interval type-2 fuzzy logic controllers on micro robots with limited resources are investigated. The solution thatis being proposed is the use of pre-calculated 3D surfaces generated by an off-line Fuzzy Logic System covering the expected ranges of the input and output variables. The surfaces are then loaded into the memory of the micro robots and can be accessed by the motor controller. The aim of the research is to test if there is an advantage of using type-2 fuzzy logic controllers implemented as surfaces over type-1 and PID controllers on a micro robot with limited resources. Control surfaces were generated for both type-1 and average interval type-2 fuzzy logic controllers. Each control surface was then accessed using bilinear interpolation to provide the crisp output value that was used to control the motor. Previously when this method has been used a single surface was employed to hold the information. This thesis presents the novel approach of the dual surface type-2 fuzzy logic controller on micro robots. The lower and upper values that are averaged for the classic interval type-2 controller are generated as surfaces and installed on the micro robots. The advantage is that nuances and features of both the lower and upper surfaces are available to be exploited, rather than being lost due to the averaging process. Having conducted the experiments it is concluded that the best approach to controlling micro robots is to use fuzzy logic controllers over the classical PID controllers where ever possible. When fuzzy controllers are used then type-2 fuzzy controllers (dual or single surface) should be used over type-1 fuzzy controllers when applied as surfaces on micro robots. When a type-2 fuzzy controller is used then the novel dual surface type-2 fuzzy logic controller should be used over the classic average surface. The novel dual surface controller offers a dynamic, weighted, adaptive and superior response over all the other fuzzy controllers examined.
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Butt, Casey Benjamin. "Simplified fuzzy logic controller based vector control of an interior permanent magnet motor /." Internet access available to MUN users only, 2003. http://collections.mun.ca/u?/theses,155545.

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Cruz, Shermila Guerra Santa. "Sistema de navegação para veículo autônomo utilizando lógica difusa." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/18/18152/tde-09092009-082215/.

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Este trabalho teve por objetivo o desenvolvimento de um sistema de controle de navegação para um veículo autônomo utilizando lógica difusa. Atribui-se o nome de SNAT (Sistema de navegação-autônoma para um triciclo). O sistema é responsável pela automatização do processo de navegação de um veículo de testes monitorado e controlado de uma base remota mediante enlace de telemetria de dados. O usuário do sistema, pela tela principal da aplicação indica os pontos a seguir, cada um destes é referenciado pela sua latitude e longitude no mapa. Uma vez iniciada a navegação, o sistema de controle recebe periodicamente pacotes de dados da posição e direção do veículo; estes dados são processados pelo controlador difuso que gera os comandos para atuação sobre o veículo. O controlador difuso traduz as expressões qualitativas, comuns na comunicação humana em valores numéricos que representam a direção e a velocidade para manter ou corrigir a navegação do veículo de testes pelo rumo desejado. Nesta dissertação são apresentados diversos aspectos do desenvolvimento do controlador de navegação difusa, os mecanismos de comunicação e acionamento do veículo de uma base remota e os testes realizados que mostram os resultados do SNAT controlando automaticamente a navegação do veículo de testes.
This work had as a goal the development of a fuzzy logic based navigation control system for an autonomous vehicle. The developed control system was named SNAT (from the equivalent in portuguese of autonomous navigation system for a tricycle). The system controls and monitors the navigation of the vehicle from a remote base station using a telemetry data link. The user indicates, using a developed application, the navigation waypoints, referencing them by their latitude and longitude coordinates in a map. When the navigation starts, the system receives periodically data packets indicating the position and direction of the vehicle, these data are processed by the fuzzy control which returns commands to actuate over the vehicle. The fuzzy control translates qualitative expressions, common in human communication, into numerical values that represent the speed and the direction to keep the vehicle as near as possible to the desired navigation route. Many development aspects of the fuzzy controller and of the communication and actuation over the vehicle from the remote base are presented. Also are presented some results of the control system over navigation of the vehicle, which demonstrate that the system operates in a quite satisfactory manner.
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Pena, Jailson Silvério. "Eficiência energética por meio de um controlador PI autossintonizado por lógica fuzzy em sistema de distribuição de água de um setor da grande Curitiba." Universidade Tecnológica Federal do Paraná, 2018. http://repositorio.utfpr.edu.br/jspui/handle/1/3116.

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Esta dissertação apresenta uma aplicação de inteligência artificial, a lógica fuzzy, estruturada como um controlador fuzzy, para a sintonia dos ganhos Kp e Ki de um controlador PI. Este último, configurado num conversor de frequência para a operação de um conjunto motor-bomba do sistema de abastecimento de água potável na região denominada de Recalque Mercês (RMER), na cidade de Curitiba, compreendendo 4 bairros com 140 km de tubulação e mais de 13 mil ligações a clientes. Hoje, o sistema funciona com controle PI tradicional de ganhos fixos, variando a velocidade do conjunto motorbomba, controlados por um sensor de pressão à jusante do bombeamento. Contudo, a variação de consumo de água potável fornecida é muito grande durante o período de um dia, sendo máxima no entardecer e mínima durante a madrugada, e com características sazonais, o consumo aumenta com o calor e diminui no frio, o que faz esse tipo de controle fixo ser ineficiente em determinados momentos. A proposta é adotar o controle fuzzy para alterar os coeficientes do controlador PI ao longo do dia, de forma autônoma, de acordo com o consumo instantâneo e assim, alcançar uma melhor eficiência energética do sistema, prezando pela qualidade do serviço prestado à população. Isto é, garantindo a vazão e a pressão de água para o consumidor. Por meio do MatLab®, mais precisamente os toolbox’s de simulação, Simulink® e SimScape®, foram criados dois modelos, um com o controle atual e o outro com a proposta inteligente, de uma abreviação da rede e do sistema de bombeamento da elevatória existente, a diminuição de 4 conjuntos motor-bomba para apenas 1 (um) e num trajeto único, perfazendo 5,4 km de distância, até o local denominado de ponto crítico, onde é mais longe, alto e difícil de se manter a pressão no patamar de 10 m.c.a. (1 bar), por norma. O controlador fuzzy desenvolvido possui 2 entradas, o nível do reservatório e a pressão à jusante do conjunto motor-bomba, e 2 saídas, os ganhos proporcional e integral para o PI. Com a estrutura baseado em regras, foram criadas 123 regras de inferência para que o sistema obtenha um desempenho favorável. As simulações foram realizadas com a referência de dados – 3 meses de histórico – de medições do reservatório e do sensor de pressão que é a realimentação do controle PI existente. Assim, a eficiência energética de 6,15% ao mês, em termos de energia elétrica consumida, foi conseguida, comparando com o modelo de controle tradicional.
This dissertation presents an application of artificial intelligence, the fuzzy logic, structured as a fuzzy controller, for the tuning of the Kp and Ki gains of a PI controller. The latter, configured in a frequency converter for the operation of a motor-pump assembly of the drinking water supply system in the region called Recalque Mercês (RMER), in the city of Curitiba, comprising 4 districts with 140 km of pipeline and more than 13 thousand connections to customers. Today, the system operates with PI traditional control with fixed gains, varying the speed of the motor-pump assembly, controlled by a pressure sensor downstream to the pumping. However, the variation in the consumption of potable water supplied is very large during the period of one day, being maximum at dusk and minimum during the dawn, and with seasonal characteristics, consumption increases with heat and decreases in the cold, which makes static control inefficient at certain times. The proposal is to adopt the fuzzy control to change the coefficients of the PI controller throughout the day, autonomously, according to the instantaneous consumption and thus achieve a better energy efficiency of the system, appreciating the quality of service provided to the population. That is, ensuring the flow and pressure of water to the consumer. Through MatLab®, simulation tools, Simulink® and SimScape®, two models were created, one with the current control and the other with the intelligent proposal. An abbreviation of the network and the existing pumping system of the lift, the reduction of 4 engine-pump assemblies to only 1 (one) and a single path, making 5.4 km distance, to the socalled critical point location, where it is further, higher and more difficult to keep the pressure at the 10 mwg (1 bar), as a rule. The developed fuzzy controller has 2 inputs, the reservoir level and the downstream pressure of the motor-pump assembly, and 2 outputs, proportional and integral gains for the PI. With the rulesbased framework, 123 inference rules were created for the system to perform favorably. The simulations were carried out with the reference of data – 3 months of historical – of measurements of the reservoir and pressure sensor that is the feedback of the existing PI control. Thus, the energy efficiency of 6.15% per month, in terms of electric power consumed, was achieved, compared to the traditional control model.
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Huang, Po Zhao, and 黃博昭. "Automated Design of Track Seeking Fuzzy Controllers for DVD-ROM." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/88371728715595575806.

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碩士
國立臺北科技大學
機電整合研究所
92
For the sake of reducing the seeking time of DVD-ROM, this thesis proposed a hybrid track seeking fuzzy controller (HTSFC) for DVD ROM's track seeking control. It is composed of the switching time controller, the speed controller and the start-up voltage regulator in long track seeking, and the speed controller was designed based on modulated span membership functions. An on-line design scheme based on genetic algorithm is also proposed for learning these 3 fuzzy controllers in long track seeking. Furthermore, we use the fuzzy gain regulator to do short track seeking of DVD-ROM in this thesis. An on-line design scheme based on modulated span membership functions and two kinds of genetic algorithm are also proposed for this regulator. By reducing the searching time through the HTSFC of auto learning on-line for DVD-ROM's track seeking to get the best performance of DVD-ROM is the prime object of this paper.
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Books on the topic "Automated fuzzy controllers"

1

Fuzzy controllers. Oxford: Newnes, 1997.

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Stjepan, Bogdan, ed. Fuzzy controller design: Theory and applications. Boca Raton, FL: CRC Press/Taylor & Francis Group, 2005.

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Kovacic, Zdenko. Fuzzy controller design: Theory and applications. Boca Raton, FL: CRC Press/Taylor & Francis Group, 2006.

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Palm, Rainer. Model based fuzzy control: Fuzzy gain schedulers and sliding mode fuzzy controllers. Berlin: Springer, 1997.

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Neuro-fuzzy controllers: Design and application. Lausanne: Presses polytechniques et universitaires romandes, 1997.

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Hellendoorn, Hans, Dimiter Driankov, and Rainer Palm. Model Based Fuzzy Control: Fuzzy Gain Schedulers and Sliding Mode Fuzzy Controllers. Springer, 1996.

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Anderson, James D. Filling a rough-mill cutting order using a fuzzy logic controller. 1996.

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Anderson, James D. Filling a rough-mill cutting order using a fuzzy logic controller. 1996.

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A fuzzy logic based controller for the automated alignment of a laser-beam-smoothing spatial filter. [Washington, DC]: National Aeronautics and Space Administration, 1993.

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N, Lea Robert, Villarreal James, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., eds. Proceedings of the Second Joint Technology Workshop on Neural Networks and Fuzzy Logic: Proceedings of a workshop sponsored by the National Aeronautics and Space Administration ... and cosponsored by Lyndon B. Johnson Space Center and the University of Houston, Clear Lake, Houston, Texas, April 10-13, 1990. [Washington, DC]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1991.

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Book chapters on the topic "Automated fuzzy controllers"

1

Preitl, Stefan, and Radu-Emil Precup. "Fuzzy Controllers with Dynamics, a Systematic Design Approach." In Advances in Automatic Control, 283–96. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4419-9184-3_20.

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Carvajal, R. G., M. A. Aguirre Echanova, A. J. Torralba Silgado, and L. G. Franquelo. "AFAN — A Tool for the Automatic Design of Digital and Analog Neuro-Fuzzy Controllers." In Fuzzy Hardware, 77–89. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-4090-8_4.

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Shan, Weiwei, Xiqun Zhu, and Yuan Ma. "Adaptive Fuzzy Logic Controller and Its Application in MEMS Mirror Actuation Feedback Control." In Intelligent Data Engineering and Automated Learning - IDEAL 2009, 74–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04394-9_10.

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Kłosowski, Grzegorz, Arkadiusz Gola, and Antoni Świć. "Application of Fuzzy Logic Controller for Machine Load Balancing in Discrete Manufacturing System." In Intelligent Data Engineering and Automated Learning – IDEAL 2015, 256–63. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24834-9_31.

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Jain, Parveen. "Automatic Traffic Signal Controller for Roads by Exploiting Fuzzy Logic." In Computer Networks and Information Technologies, 273–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19542-6_46.

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Naranjo, J. E., J. Reviejo, C. González, R. García, and T. de Pedro. "A Throttle and Brake Fuzzy Controller: Towards the Automatic Car." In Computer Aided Systems Theory - EUROCAST 2003, 291–301. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45210-2_27.

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Carvajal, R. G., A. Torralba, F. Colodro, and L. G. Franquelo. "AFAN, a tool for the automatic design of fuzzy and neural controllers." In Biological and Artificial Computation: From Neuroscience to Technology, 825–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0032542.

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Attolico, G., A. Itta, G. Cicirelli, and T. D’Orazio. "ART-based Automatic Generation of Membership Functions for Fuzzy Controllers in Robotics." In Lecture Notes in Computer Science, 259–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48774-3_31.

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Ignatyev, Vladimir, Viktor Soloviev, Denis Beloglazov, Viktor Kureychik, Kovalev Andrey, and Alexandra Ignatyeva. "The Fuzzy Rule Base Automatic Optimization Method of Intelligent Controllers for Technical Objects Using Fuzzy Clustering." In Communications in Computer and Information Science, 135–52. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29750-3_11.

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Fang, Gu, Ngai Ming Kwok, and Dalong Wang. "Automatic Rule Tuning of a Fuzzy Logic Controller Using Particle Swarm Optimisation." In Artificial Intelligence and Computational Intelligence, 326–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16527-6_41.

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Conference papers on the topic "Automated fuzzy controllers"

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Shill, Pintu Chandra, and Kazuyuki Murase. "Designing a fully automated hierarchical fuzzy logic controllers using evolutionary algorithms." In 2013 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES). IEEE, 2013. http://dx.doi.org/10.1109/cies.2013.6611731.

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Miraftab, V., and R. Mansour. "Automated Microwave Filter Tuning by Extracting Human Experience in Terms of Linguistic Rules using Fuzzy Controllers." In 2006 IEEE MTT-S International Microwave Symposium Digest. IEEE, 2006. http://dx.doi.org/10.1109/mwsym.2006.249541.

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Al-mousa, Amjed A., Ali H. Nayfeh, and Pushkin Kachroo. "Control of Rotary Cranes Using Fuzzy Logic." In ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/vib-21598.

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Abstract Rotary cranes (tower cranes) are common industrial structures that are used in building construction, factories, and harbors. These cranes are usually operated manually. With the size of these cranes becoming larger and the motion expected to be faster, the process of controlling them became difficult without using automatic control methods. In general, the movement of cranes has no prescribed path. Cranes have to be run under different operating conditions, which makes closed-loop control preferable. In this work a fuzzy logic controller is introduced with the idea of split-horizon; that is, fuzzy inference engines (FIE) are used for tracking the position and others are used for damping the load oscillations. The controller consists of two independent controllers: radial and rotational. Each of these controllers has two fuzzy inference engines (FTEs). Computer simulations are used to verify the performance of the controller. Three simulation cases are introduced: radial, compound, and damping. The results from the simulations show that the fuzzy controller is capable of keeping the load-oscillation angles small throughout the maneuvers while completing them in a relatively reasonable time.
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Shill, Pintu Chandra, Kishore Kumar Pal, Md Faijul Amin, and Kazuyuki Murase. "Genetic algorithm based fully automated and adaptive fuzzy logic controller." In 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2011. http://dx.doi.org/10.1109/fuzzy.2011.6007560.

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Acampora, Giovanni, Vincenzo Loia, and Autilia Vitiello. "Exploiting Timed Automata based Fuzzy Controllers for voltage regulation in Smart Grids." In 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2011. http://dx.doi.org/10.1109/fuzzy.2011.6007617.

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Garcia, Javier Gamez, Juan Gomez Ortega, Alejandro Sanchez Garcia, and Silvia Satorres Martinez. "Fuzzy controller for the high-accuracy automatic assembly of vehicle headlamps." In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2010. http://dx.doi.org/10.1109/fuzzy.2010.5584024.

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Couzon, Pierre-Yves, Johan Der Hagopian, and Luc Gaudiller. "Neuro-Fuzzy Active Control of Mechanical Structures." In ASME 2002 Engineering Technology Conference on Energy. ASMEDC, 2002. http://dx.doi.org/10.1115/etce2002/struc-29048.

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The abilities of neural networks combined with fuzzy logic offer interesting prospects for the active control of structures. By identification, they permit discarding the often delicate modeling step and they also permit the automatic regulation of the controllers that have non-linear characteristics. This study describes the application of neuro-fuzzy control to the dynamic behavior of structures. The study first explains the process chosen, which consists of two parts: • the first part is essential for the adjustment of the associated controller and concerns the neural identification of the structure studied; • the second part describes the controller development and the training stage; the controller is based on the simplest neural network model possible. This network is also able to translate Sugeno’s fuzzy function and optimize its performances according to a reference response. The study then presents two applications: the first deals with the identification and control of a linear mechanical system with two degrees of freedom. The second deals with the identification and control of the non-linear dynamic behavior of active electromagnetic actuators along one acting axis. In both cases, the results show the abilities and the efficiency of this process and underline the main advantage of this type of controller operating even on in a strongly non-linear system.
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Acampora, Giovanni. "Exploiting Timed Automata-based Fuzzy Controllers and data mining to detect computer network intrusions." In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2010. http://dx.doi.org/10.1109/fuzzy.2010.5584893.

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Li-Xin Wang. "Automatic design of fuzzy controllers." In Proceedings of the 1998 American Control Conference (ACC). IEEE, 1998. http://dx.doi.org/10.1109/acc.1998.707338.

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de Sam Lazaro, A., and W. Steffenhagan. "A Hybrid Fuzzy Controller for Industrial Power Plants." In ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium collocated with the ASME 1995 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/cie1995-0835.

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Abstract The automation of the control to a power plant is indeed a challenge mainly because of the occurrences of random and unpredictable variations in output demands as well as because of highly non-linear behavior of the system itself [1]. It is sometimes argued that the ‘best’ control for a power plant is the operators themselves. Experienced operators are capable of taking decisions on the basis of incomplete and imprecise information. The extent to which these decisions are correct is a matter of speculation. Erroneous conclusions, established post facto, are chalked up to the learning process and in fact, contribute to the forming of a good, experienced control team. The need to automate the control process for a plant is even more acutely felt when considering the complexity of the plants themselves and the volume of data that would have to be processed before a control decision can be taken. Factored into this decision would also be several governing parameters such as costs, reliability, other constraints and their interdependancy, as well as planned and unscheduled outages for maintenance and so on. In this paper, however, only one facet of a power plant operation is considered. It is intended to demonstrate that thermal efficiency may be improved by better techniques for automated control of throttle valves in the steam turbine of the plant. One of these options, fuzzy logic, is selected, and defended, as being the more effective than current techniques. A comparative analysis is conducted of control techniques for plant operations followed by a brief overview of fuzzy control and its application to control of non-linear systems. A method of applying this ‘new’ computer-based technique to control of non-linear, somewhat erratic plants is presented and discussed.
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