{"title":"A fuzzy cell-mapping feedback control algorithm for the satellite attitude manoeuvring control","authors":"J. Yen, Shiou-Wen Tarng","doi":"10.1109/AFSS.1996.583713","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583713","url":null,"abstract":"A fuzzy cell-mapping control algorithm, formerly proposed for motor control, is extended to the application of satellite attitude manoeuvring/stabilizing control. The cell-mapping method treats the complex satellite attitude dynamics, and the fuzzy interpretation helps achieve a suitable control effort. The result is a smooth transition for manoeuvring to stabilization without overshoot while maintaining an optimal control performance.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122549755","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}
{"title":"Stabilization of nonholonomic mobile robots by a GA-based fuzzy sliding mode control","authors":"Wei-Ming Lee, Han-Pang Huang","doi":"10.1109/AFSS.1996.583639","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583639","url":null,"abstract":"In this study, fuzzy logic control principle and sliding mode control theory are combined to stabilize a mobile robot under nonholonomic kinematic constraints. In order to improve the tracking performance, the scaling factors of FLC are searched by genetic algorithms (GAs). The simulation results show that all three control approaches, SMC (sliding mode control), FSMC (fuzzy-SMC) and GA-FSMC (GA-based FSMC) can stabilize the mobile robot to the origin with /spl phi/=0. However the GA-FSMC provides a systematic way to search the scaling factors, and thus improves the transient performance of the system response and reduces the path length for navigation.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125439208","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}
{"title":"Generalized probabilistic rough set models","authors":"Y.Y. Yao, S. Wong","doi":"10.1109/AFSS.1996.583582","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583582","url":null,"abstract":"This paper presents a probabilistic version of generalized rough set models. It generalizes the standard algebraic and probabilistic rough set models in two aspects. An arbitrary binary relation is used instead of an equivalence relation. A probability function on the universe is used instead of computing probabilities from the cardinality of sets. Fundamental issues related to probabilistic rough set models are examined.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"63 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120851433","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}
{"title":"Tuning rough controllers by genetic algorithms","authors":"T. Chiu, T. Y. Lin","doi":"10.1109/AFSS.1996.583624","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583624","url":null,"abstract":"A design process of intelligent control systems, called rough logic government, consists of a sequence of transformations of mathematical models of control systems. It is a modification of the design process of fuzzy controllers using rough sets, rough logic, and evolutionary computing. Rough logic government starts with a symbolic model, called rough linguistic model, and concludes with tedious experiments. The final mathematical structure is called rough verification and validation model. In this paper, genetic algorithm is used to partially automate the final step, and experiments from various angles are conducted and analyzed.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125903718","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}
{"title":"Fuzzy decisions in possibility programming problems","authors":"Ping Guo, H. Tanaka","doi":"10.1109/AFSS.1996.583604","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583604","url":null,"abstract":"In this paper, possibility programming problems are formulated to obtain fuzzy decisions that reflect vagueness in decision problems. According to the different decision cases, there are two options: one is linear programming (LP), the other is quadratic programming (QP). In general, it is feasible that QP will obtain a greater number of different solutions than LP will.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126079827","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}
{"title":"Fuzzy reasoning and fuzzy logic","authors":"Guna Wang","doi":"10.1109/AFSS.1996.583672","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583672","url":null,"abstract":"Fuzzy reasoning and fuzzy logic are two related but different research fields such that both are fruitful but have not yet been well linked. The aim of the paper is to: (i) prove that it is impossible to keep all theorems in classical propositional calculus to be tautologies in fuzzy propositional calculus; (ii) establish a so called quasi-formal deduction system and prove the corresponding soundness theorem; and (iii) revise, clear and set a logic foundation for the concepts of fuzzy modus ponens and fuzzy modus tollens.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"325 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132588577","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}
{"title":"Neural networks modeling of temperature field distribution in hyperthermia","authors":"Yung-Yaw Chen, Chi-Hung Chen, Win-Li Lin","doi":"10.1109/AFSS.1996.583716","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583716","url":null,"abstract":"Hyperthermia is known to be a method of killing tumor cells by heating. An ultrasound transducer is often used as the heating device. In order to kill the tumor cells and not injure the normal tissue, the temperature distribution generated by the ultrasound must be predetermined. For a multi-element ultrasound transducer, the phase and the amplitude of the input signal for each element can be tuned to generate a suitable temperature distribution to meet the needs of individual treatments. However, direct computation is often time-consuming, while there are also difficulties in computing the ultrasound transducer parameters with a given temperature distribution. In this paper, artificial neural networks are used to learn the relationship between the ultrasound transducer parameters and the temperature distribution, both in the forward and in the inverse direction.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130878611","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}
{"title":"Configuring an improved backpropagation network for forecasting study of interest rate in traditional money market and derivative commodity market","authors":"Yea-Win Wu","doi":"10.1109/AFSS.1996.583689","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583689","url":null,"abstract":"By good management of the interacting characteristics of micro and meso structures for optimizing performance of feedforward networks, the application of a neural network to pattern recognition of monetary tools, bond rating, stock price forecasting and loan examination has successfully been done. The study focuses on the prediction of future trends of the 90 to 180 day commercial paper interest rate. The outcome shows several encouraging messages: (1) While the result of applying the multiregressional model on this kind of problem is awkward, the improved backpropagation networks, especially the one integrating Nguyen-Widrow Method and Adaptive Learning Rate Method have good performance without involving the serious problems of multicollinearity and autocorrelation. (2) With small tolerance error, the network forecasting reliability is satisfactory no matter whether random or moving simulation sampling is adopted. (3) For avoiding the impact of random wave, we take the average daily interest rate t-2,t-1,t+1,t+2 as the target output. In so doing the network presents a good learning effect with the accuracy of forecast beyond 98%. (4) The performance of the improved backpropagation network like momentum is not always better than a pure backpropagation network. We learned from the study that the fluctuating trend of interest rate may be influenced by different combinations of economic and monetary independent variables in different time periods, so rashly gathering a big sample without reviewing the attributes of the data may prevent the authentic forecasting effect of the network.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132058465","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}
{"title":"Adaptive aggregation of modular control","authors":"H. C. Tseng, T. Lin, C. W. Chi","doi":"10.1109/AFSS.1996.583682","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583682","url":null,"abstract":"Modular methodologies are popular in various control designs. We propose a performance-based adaptive aggregation for modular controllers. Conventional modular control techniques, like decentralized control, singular perturbation and hierarchical decomposition, use non-adaptive aggregation and are only applicable to a restricted class of nonlinear systems. It is demonstrated in this paper that adaptive aggregation extends the validity and the performance of a modular design to a wider class of nonlinear systems. Rule-based aggregation, induced by fuzzy logic and rough sets, is proposed for ease of design and utilization of a priori knowledge. The emphasis in this paper is on model-independent design.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132191961","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}
{"title":"Inexact strategy and planning-the implementation of route planning in Taipei city","authors":"Hung-Chang Lee, Chen-Chung Lee","doi":"10.1109/AFSS.1996.583619","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583619","url":null,"abstract":"Focuses on inexact strategies and planning. As an example and implementation, we integrate geographic information system (GIS) and fuzzy decision support system (DSS) technology to explore route planning in Taipei city, Taiwan. The first objective is to build a useful route-planning GIS in Taipei. We have proposed functions such as spatial querying and landmark location. In the second objective, we incorporate inexact information into spatial information, such as distances and traffic jams, and propose an inexact strategy to help with making decisions in these route-planning systems.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134181482","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}