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Fuzzy logic and neurofuzzy technologies in embedded automotive applications 嵌入式汽车应用中的模糊逻辑和神经模糊技术
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324214
C. von Altrock, B. Krause
{"title":"Fuzzy logic and neurofuzzy technologies in embedded automotive applications","authors":"C. von Altrock, B. Krause","doi":"10.1109/IFIS.1993.324214","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324214","url":null,"abstract":"Most advanced control algorithms in automotive engineering can benefit from fuzzy logic and neurofuzzy techniques. Either by speeding up the development cycle or by rendering functionalities not achieved by other advanced control techniques, fuzzy logic complements conventional control by incorporating engineering \"know-how\" in the design process. Typical embedded applications are in the area of ABS, ASR, 4WD/4WS, suspension and powertrain control. This paper focuses on the implementational and design issues special to automotive applications. The integration of high-speed fuzzy logic software implementations into existing hardware platforms and the optimization and verification strategies for fuzzy logic systems are discussed with a case study of an anti-skid steering system implemented in a model car at the University of Aachen.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125168649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
Logical industrial controls using fuzzy rules 使用模糊规则的逻辑工业控制
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324198
C. Day, E. Dummermuth
{"title":"Logical industrial controls using fuzzy rules","authors":"C. Day, E. Dummermuth","doi":"10.1109/IFIS.1993.324198","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324198","url":null,"abstract":"Fuzzy logic controls are actively explored in an increasing number of manufacturing and process industries. The main goal is to improve manufacturing productivity. This paper is intended to fill the need of applying logical industrial control using fuzzy rules. With improved knowledge of fuzzy logic, users' interests and success rate of potential applications will grow. In this paper, we present idiosyncrasies of industrial control needs and understanding fuzzy logic for industrial controls. We then discuss the process of evolving applications and examples of industrial controls. Several justifications using fuzzy logic and practical ways to apply are presented. The overall goal is to increase successful applications of fuzzy logic controls in the manufacturing and process environment.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"226 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123718551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Hardware implementation issues of multivariable fuzzy control systems 多变量模糊控制系统的硬件实现问题
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324191
M. Patyra, J. Grantner
{"title":"Hardware implementation issues of multivariable fuzzy control systems","authors":"M. Patyra, J. Grantner","doi":"10.1109/IFIS.1993.324191","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324191","url":null,"abstract":"We show two models for synchronous finite state machines (FSM) based on fuzzy logic: the crisp-state-fuzzy-output (CSFO) FSM, and the fuzzy-state-fuzzy-output (CSFO) FSM. As a result of the introduction of the FSM models, improved architectures for fuzzy logic controller have been defined. The new method for linguistic fuzzy model building of multi-input-multi-output controllers is proposed. Due to the applied theoretic approach to the fuzzy model building, the fuzzy logic controller architecture features massively parallel fuzzy data inferencing is obtained. This architecture provides almost constant performance, independent on the number of inputs, on the number of outputs, and on the number of processed rules. The approach can be utilised for logic controller hardware to work in the real-time environment.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116187213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
A fuzzy-tuned adaptive Kalman filter 一种模糊调谐自适应卡尔曼滤波器
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324197
Y. Lho, J. Painter
{"title":"A fuzzy-tuned adaptive Kalman filter","authors":"Y. Lho, J. Painter","doi":"10.1109/IFIS.1993.324197","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324197","url":null,"abstract":"In this paper, fuzzy processing is applied to the adaptive Kalman filter. The filter gain coefficients are adapted over a 50 dB range of unknown signal/noise dynamics, using fuzzy membership functions. Specific simulation results are shown for a dynamic system model which has position-velocity states, as in vehicle tracking applications such as the global positioning system (GPS). The filter is single-input single-output, driven by measurements of position, corrupted by additive (Gaussian) noise. The fuzzy adaptation technique is also applicable to multiple-input multiple-output applications for the cases where the states are higher-order moments of motion. The fuzzy processing is driven by an inaccurate online estimate of signal-to-noise ratio for the signal being tracked. A robust Bayes scheme calculates the filter gain coefficients from the signal-to-noise estimate. In our implementation, the inaccurate signal-to-noise estimate is corrected by the use of fuzzy membership functions. Performance comparisons are given between optimum, fuzzy-tuned adaptive, and fixed-gain Kalman filters for the second-order position-velocity model.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116545953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
Model-based understanding of uncertain observational data for oil spill tracking 基于模型的溢油跟踪不确定观测数据理解
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324196
Jungfu Tsao, Jan Wolter, Haojin Wang
{"title":"Model-based understanding of uncertain observational data for oil spill tracking","authors":"Jungfu Tsao, Jan Wolter, Haojin Wang","doi":"10.1109/IFIS.1993.324196","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324196","url":null,"abstract":"Oil spill tracking is essential in oil spill clean-up. Usually, the oil spill tracking is treated by employing a mathematical oil spill model which describes the fate and transport behavior of an oil-spill. Before a model can predict where the spilled oil will go in the future, it must have a reasonably accurate understanding about what happened in the past. Typically, the input to the model such as wind, current, etc. is unreliable or sometimes not completely available so that interpolating the past behavior of an oil spill becomes extremely difficult. In this paper, we regard the oil spill tracking as a control problem in which we reduce the errors between the oil observations and the model outputs by iteratively adjusting the model inputs and cope with the uncertainty of the model inputs by using fuzzy logic techniques. Through the process, we can construct a plausible history of the oil spill that is consistent with our observations and can be effectively extrapolated into the future.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122629688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Off-line-access to remote databases with fuzzy searching elements 离线访问具有模糊搜索元素的远程数据库
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324184
V.V. Senkevich
{"title":"Off-line-access to remote databases with fuzzy searching elements","authors":"V.V. Senkevich","doi":"10.1109/IFIS.1993.324184","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324184","url":null,"abstract":"The author presents some approaches for the development of a wide area distributed databases system with remote off-line access. On the basis of such approaches different systems of commercial information processing may be constructed. He attempts to overcome the negative moments by comparing the texts of commercial offers and calculation criteria of its \"likeness\". An uncertainty, obtained after such comparison, is analyzed and handled by a special algorithm. He also describes an algorithm of text identity comparison based on the fuzzy set theory. He then offers a new \"hybrid\" algorithm that tries to minimize the negative moments. The main goals of the analysis are: selection of \"like\" text descriptions on the basis of the criteria of identity; independence from new items in some classifiers or database field lists; and an automatic search of corresponding text descriptions of database, database fields, or data.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128358897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Multi-objective circuit quality optimization using hierarchical/adaptive fuzzy set theory approach 基于层次/自适应模糊集理论的多目标电路质量优化
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324218
B. Rodrigues, M. Styblinski
{"title":"Multi-objective circuit quality optimization using hierarchical/adaptive fuzzy set theory approach","authors":"B. Rodrigues, M. Styblinski","doi":"10.1109/IFIS.1993.324218","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324218","url":null,"abstract":"A new methodology based on the use of fuzzy sets theory and intended to be applied to the design of products having a number of performance requirements is outlined. Initially motivated by the intention to generalize the Taguchi methodology for off-line quality control to an arbitrary number of outputs and statistical measures, it allows the designer to specify an ordering of the performances to be optimized during the optimization process. In such a way it fits into what has become lately known as design for quality. It relies heavily on the notions of dynamically altered membership functions and aggregation procedures. It also makes strong usage of history information to guide both the search procedure in the optimization space as well as to control the dynamically altered membership function and the way they are aggregated. An example is included describing an application of the methodology to a multi-output, multistatistics OPAMP, where the authors' approach was very successful in minimizing variability and maximizing yield, results that could not be obtained by other procedures. The methodology is applicable to the generic class of design situations where the product under study has to satisfy a number of dependent or independent criteria, which can but do not need to be of statistical nature.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128585118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Supervisory control of an energy management control system via fuzzy logic 基于模糊逻辑的能源管理控制系统监控
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324202
R. Belur, R. Langari
{"title":"Supervisory control of an energy management control system via fuzzy logic","authors":"R. Belur, R. Langari","doi":"10.1109/IFIS.1993.324202","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324202","url":null,"abstract":"In this paper an approach to supervisory control of multi-stage industrial control systems is presented. This approach is based on the notion of an internal reference model, and further makes use of a fuzzy multi-objective optimization strategy to compute the control action via an iterative approach. This framework has been shown to be effective in the operation of an energy management and control system (EMCS) used in climate control and may offer similar advantages in other situations as well.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128707470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
DC/DC converters fuzzy control DC/DC变换器模糊控制
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324222
A. Pagni, R. Poluzzi, G. Rizzotto, M. L. Lo Presti
{"title":"DC/DC converters fuzzy control","authors":"A. Pagni, R. Poluzzi, G. Rizzotto, M. L. Lo Presti","doi":"10.1109/IFIS.1993.324222","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324222","url":null,"abstract":"This paper aims to illustrate the use of a sophisticated methodology, based on system simulation techniques, to design a fuzzy controller for a DC/DC converter. The goal of the control is to stabilize the voltage output of the switching regulator against the load and parametric variations for a flyback topology. This system is characterized by being unstable in closed loop configuration. Robustness and high performances art requested to the control law especially for high power systems (more than 200 Watt). In order to obtain a good cost/performances ratio, the rules and the related membership functions have to be implemented via an analog dedicated solution capable to obtain an elevated number of FIPS (fuzzy inference per second).<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127770500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Neural net robot controller with guaranteed stability 具有保证稳定性的神经网络机器人控制器
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324205
F. Lewis, A. Yesildirek, K. Liu
{"title":"Neural net robot controller with guaranteed stability","authors":"F. Lewis, A. Yesildirek, K. Liu","doi":"10.1109/IFIS.1993.324205","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324205","url":null,"abstract":"A multilayer neural net (NN) controller for a general serial-link robot arm is developed. The structure of the NN controller is derived using a filtered error approach. No learning phase is needed. It is argued that standard backpropagation tuning, when used for real-time closed-loop control, can yield unbounded NN weights if: (1) the net cannot exactly reconstruct a certain required nonlinear control function; (2) there are bounded unknown disturbances in the robot dynamics; or (3) the robot arm has more than one link (i.e. nonlinear case). Novel online weight tuning algorithms given include correction terms to backpropagation, plus an added robustifying signal, and guarantee tracking as well as bounded weights.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125449662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
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