Pub Date : 2007-07-23DOI: 10.1109/FUZZY.2007.4295357
Tiejun Zhang, G. Feng, J. Lu
In this paper, a fuzzy affine model, which is more capable of representing strongly nonlinear dynamics, is used for predictive controller design. Based on piecewise quadratic Lyapunov functions, the proposed fuzzy affine model predictive control approach can ensure both the closed-loop system stability and the satisfactory transient control performance even under input and state constraints. With the help of partitioned degenerate ellipsoids and S-procedure, the large terminal invariant set of a fuzzy affine system can be achieved offline by solving a convex semi-definite programming problem subject to some linear matrix inequalities, rather than the non-convex bilinear matrix inequalities as in conventional fuzzy affine model based control. Then with the associated terminal cost, the resulting online open-loop predictive control approach can be formulated as a standard quadratic programming problem, which is readily solvable. Simulation results have demonstrated the performance of the proposed approach.
{"title":"Stable Model Predictive Control of Fuzzy Affine Systems with Input and State Constraints","authors":"Tiejun Zhang, G. Feng, J. Lu","doi":"10.1109/FUZZY.2007.4295357","DOIUrl":"https://doi.org/10.1109/FUZZY.2007.4295357","url":null,"abstract":"In this paper, a fuzzy affine model, which is more capable of representing strongly nonlinear dynamics, is used for predictive controller design. Based on piecewise quadratic Lyapunov functions, the proposed fuzzy affine model predictive control approach can ensure both the closed-loop system stability and the satisfactory transient control performance even under input and state constraints. With the help of partitioned degenerate ellipsoids and S-procedure, the large terminal invariant set of a fuzzy affine system can be achieved offline by solving a convex semi-definite programming problem subject to some linear matrix inequalities, rather than the non-convex bilinear matrix inequalities as in conventional fuzzy affine model based control. Then with the associated terminal cost, the resulting online open-loop predictive control approach can be formulated as a standard quadratic programming problem, which is readily solvable. Simulation results have demonstrated the performance of the proposed approach.","PeriodicalId":236515,"journal":{"name":"2007 IEEE International Fuzzy Systems Conference","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114987968","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}
Pub Date : 2007-07-23DOI: 10.1109/FUZZY.2007.4295404
Qingyong Li, Zhiping Shi, Siwei Luo
In order to improve the performance of content-based image retrieval (CBIR) systems, the 'semantic gap' between the low-level visual features and the high-level semantic features attracts more and more research interest. We propose an approach to describe and to extract the fuzzy color semantics. According to human color perception model, we utilize the linguistic variable to describe the image color semantics, so it becomes possible to depict the image in linguistic expression such as mostly red. Furthermore, we apply the feedforward neural network to model the vagueness of human color perception and to extract the fuzzy semantic feature vector. Our experiments show that the color semantic features have good accordance with the human perception, and also have good retrieval performance. In some extent, our approach shows the potential to reduce the semantic gap in CBIR.
{"title":"Image Retrieval Based on Fuzzy Color Semantics","authors":"Qingyong Li, Zhiping Shi, Siwei Luo","doi":"10.1109/FUZZY.2007.4295404","DOIUrl":"https://doi.org/10.1109/FUZZY.2007.4295404","url":null,"abstract":"In order to improve the performance of content-based image retrieval (CBIR) systems, the 'semantic gap' between the low-level visual features and the high-level semantic features attracts more and more research interest. We propose an approach to describe and to extract the fuzzy color semantics. According to human color perception model, we utilize the linguistic variable to describe the image color semantics, so it becomes possible to depict the image in linguistic expression such as mostly red. Furthermore, we apply the feedforward neural network to model the vagueness of human color perception and to extract the fuzzy semantic feature vector. Our experiments show that the color semantic features have good accordance with the human perception, and also have good retrieval performance. In some extent, our approach shows the potential to reduce the semantic gap in CBIR.","PeriodicalId":236515,"journal":{"name":"2007 IEEE International Fuzzy Systems Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114668833","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}
Pub Date : 2007-07-23DOI: 10.1109/FUZZY.2007.4295355
Sarah Greenfield, R. John
The inferencing stage of a type-2 fuzzy inferencing system is driven by join and meet operations. As conventionally implemented these algorithms are computationally complex. This article introduces optimised implementations for these operations. These alternative procedures pre-suppose that the grid method of discretisation is adopted. Time comparisons between the alternative and conventional implementations have been undertaken, for join and meet operations coded firstly in isolation, and secondly, within a full prototype type-2 fuzzy inferencing system. The experimental results show that the optimisation affords marked time reduction, particularly under finer discretisation.
{"title":"Optimised Generalised Type-2 Join and Meet Operations","authors":"Sarah Greenfield, R. John","doi":"10.1109/FUZZY.2007.4295355","DOIUrl":"https://doi.org/10.1109/FUZZY.2007.4295355","url":null,"abstract":"The inferencing stage of a type-2 fuzzy inferencing system is driven by join and meet operations. As conventionally implemented these algorithms are computationally complex. This article introduces optimised implementations for these operations. These alternative procedures pre-suppose that the grid method of discretisation is adopted. Time comparisons between the alternative and conventional implementations have been undertaken, for join and meet operations coded firstly in isolation, and secondly, within a full prototype type-2 fuzzy inferencing system. The experimental results show that the optimisation affords marked time reduction, particularly under finer discretisation.","PeriodicalId":236515,"journal":{"name":"2007 IEEE International Fuzzy Systems Conference","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114684135","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}
Pub Date : 2007-07-23DOI: 10.1109/FUZZY.2007.4295367
V. Barra, V. Delouille, J. Hochedez
Accurate means of quantifying the respective contributions of different structures to the solar irradiance is now a key issue in Solar Physics, with implications to Sun-Earth relationships and space weather study. In this paper, we propose a three-step fusion scheme, that allows to aggregate (17.1 nm, 19.5 nm) data stemming from the solar EIT instrument onboard the SoHO mission, and that is flexible enough to allow the integration of other type of information. The method is based on both a spatially constrained possibilistic clustering algorithm and a context dependent fusion operator. It aggregates the complementary and redundant information coming from the input sources. The results obtained on a 9-year dataset are consistent with those found in the solar physics literature. Unlike previous algorithms used in solar physics, our method has the ability to add further heterogeneous sources and sensors (e.g. human knowledge, images in other bandpasses, ratio of images) to the process, in order to postpone the decision step (here the segmentation of structures of interest) until sufficient information is available.
{"title":"Segmentation of Extreme Ultraviolet Solar Images using a Multispectral Data Fusion Process","authors":"V. Barra, V. Delouille, J. Hochedez","doi":"10.1109/FUZZY.2007.4295367","DOIUrl":"https://doi.org/10.1109/FUZZY.2007.4295367","url":null,"abstract":"Accurate means of quantifying the respective contributions of different structures to the solar irradiance is now a key issue in Solar Physics, with implications to Sun-Earth relationships and space weather study. In this paper, we propose a three-step fusion scheme, that allows to aggregate (17.1 nm, 19.5 nm) data stemming from the solar EIT instrument onboard the SoHO mission, and that is flexible enough to allow the integration of other type of information. The method is based on both a spatially constrained possibilistic clustering algorithm and a context dependent fusion operator. It aggregates the complementary and redundant information coming from the input sources. The results obtained on a 9-year dataset are consistent with those found in the solar physics literature. Unlike previous algorithms used in solar physics, our method has the ability to add further heterogeneous sources and sensors (e.g. human knowledge, images in other bandpasses, ratio of images) to the process, in order to postpone the decision step (here the segmentation of structures of interest) until sufficient information is available.","PeriodicalId":236515,"journal":{"name":"2007 IEEE International Fuzzy Systems Conference","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115171296","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}
Pub Date : 2007-07-23DOI: 10.1109/FUZZY.2007.4295674
E. Gelenbe
We study gene regulatory networks that include the effect of multiple binary interactions, when various genes can activate or inhibit other genes, as well as of ternary interactions where two genes jointly affect the level of activity of a third gene. We also prove that Boolean identities for the activation state of a gene in terms of the activation level of another set of genes, can be represented, so that the overall probability of activation of any gene in the network can be computed in the presence of logical dependencies, and excitatory-inhibitory interactions between genes.
{"title":"Analytical Solution of Gene Regulatory Networks","authors":"E. Gelenbe","doi":"10.1109/FUZZY.2007.4295674","DOIUrl":"https://doi.org/10.1109/FUZZY.2007.4295674","url":null,"abstract":"We study gene regulatory networks that include the effect of multiple binary interactions, when various genes can activate or inhibit other genes, as well as of ternary interactions where two genes jointly affect the level of activity of a third gene. We also prove that Boolean identities for the activation state of a gene in terms of the activation level of another set of genes, can be represented, so that the overall probability of activation of any gene in the network can be computed in the presence of logical dependencies, and excitatory-inhibitory interactions between genes.","PeriodicalId":236515,"journal":{"name":"2007 IEEE International Fuzzy Systems Conference","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116142496","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}
Pub Date : 2007-07-23DOI: 10.1109/FUZZY.2007.4295504
Yian-Kui Liu, X. Dai
Based on mean chance theory, this paper presents a new class of two-stage fuzzy random minimum risk problem (FRMRP), and discusses its deterministic equivalent programming problem. Because the FRMRPs include fuzzy random variable parameters with infinite supports, they are inherently infinite-dimensional optimization problems that can rarely be solved directly. Therefore, an approximation approach to the original two-stage FRMRPs is proposed, which results in finite-dimensional approximating two-stage FRMRPs. After that, the paper deals with the convergence of the objective value of the approximating two-stage FRMRP to that of the original two-stage FRMRP.
{"title":"Minimum-Risk Criteria in Two-Stage Fuzzy Random Programming","authors":"Yian-Kui Liu, X. Dai","doi":"10.1109/FUZZY.2007.4295504","DOIUrl":"https://doi.org/10.1109/FUZZY.2007.4295504","url":null,"abstract":"Based on mean chance theory, this paper presents a new class of two-stage fuzzy random minimum risk problem (FRMRP), and discusses its deterministic equivalent programming problem. Because the FRMRPs include fuzzy random variable parameters with infinite supports, they are inherently infinite-dimensional optimization problems that can rarely be solved directly. Therefore, an approximation approach to the original two-stage FRMRPs is proposed, which results in finite-dimensional approximating two-stage FRMRPs. After that, the paper deals with the convergence of the objective value of the approximating two-stage FRMRP to that of the original two-stage FRMRP.","PeriodicalId":236515,"journal":{"name":"2007 IEEE International Fuzzy Systems Conference","volume":"263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115282353","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}
Pub Date : 2007-07-23DOI: 10.1109/FUZZY.2007.4295641
M. Falda
This paper describes a framework for temporal reasoning that allows managing a restricted form of disjunctive temporal constraints without making the modelled problems intractable as in the case of general DTPs. This is obtained by assigning classes to the constraints and by allowing only one constraint per class, in order to build a collection of independent STPs that can share sub-problems and therefore allows increasing algorithm efficiency. The model proposed is directly applied to fuzzy constraint satisfaction problems and can be solved using an extended fuzzy path-consistency algorithm, also presented in the paper. A simple application to medical diagnosis shows its expressive power over previous tractable temporal reasoning models.
{"title":"Fuzzy Disjunctive Temporal Problems with Classes","authors":"M. Falda","doi":"10.1109/FUZZY.2007.4295641","DOIUrl":"https://doi.org/10.1109/FUZZY.2007.4295641","url":null,"abstract":"This paper describes a framework for temporal reasoning that allows managing a restricted form of disjunctive temporal constraints without making the modelled problems intractable as in the case of general DTPs. This is obtained by assigning classes to the constraints and by allowing only one constraint per class, in order to build a collection of independent STPs that can share sub-problems and therefore allows increasing algorithm efficiency. The model proposed is directly applied to fuzzy constraint satisfaction problems and can be solved using an extended fuzzy path-consistency algorithm, also presented in the paper. A simple application to medical diagnosis shows its expressive power over previous tractable temporal reasoning models.","PeriodicalId":236515,"journal":{"name":"2007 IEEE International Fuzzy Systems Conference","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121679808","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}
Pub Date : 2007-07-23DOI: 10.1109/FUZZY.2007.4295479
P. Stewart, D. Gladwin, M. Parr, J. Stewart
An investigation is made in this paper of the possibility of enhancing the performance of controllers of unstable systems while retaining safety critical function. In this case, a general dynamics F16 fighter is considered in simulation. A fuzzy logic controller is designed and its membership functions tuned by multiobjective genetic algorithms in order to design an augmented flight controller with enhanced manouverability which still retains safety critical operation. The controller is assessed in terms of pilot effort and thus reduction of pilot fatigue. The controller is incorporated into a six degree of freedom real-time flight simulator, and flight tested by a qualified pilot instructor.
{"title":"A Multiobjective G.A./Fuzzy Logic augmented flight controller for an F16 aircraft","authors":"P. Stewart, D. Gladwin, M. Parr, J. Stewart","doi":"10.1109/FUZZY.2007.4295479","DOIUrl":"https://doi.org/10.1109/FUZZY.2007.4295479","url":null,"abstract":"An investigation is made in this paper of the possibility of enhancing the performance of controllers of unstable systems while retaining safety critical function. In this case, a general dynamics F16 fighter is considered in simulation. A fuzzy logic controller is designed and its membership functions tuned by multiobjective genetic algorithms in order to design an augmented flight controller with enhanced manouverability which still retains safety critical operation. The controller is assessed in terms of pilot effort and thus reduction of pilot fatigue. The controller is incorporated into a six degree of freedom real-time flight simulator, and flight tested by a qualified pilot instructor.","PeriodicalId":236515,"journal":{"name":"2007 IEEE International Fuzzy Systems Conference","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123452713","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}
Pub Date : 2007-07-23DOI: 10.1109/FUZZY.2007.4295333
Dongrui Wu, J. Mendel
Fuzzy logic is frequently used in computing with words (CWW). When input words to a CWW engine are modeled by interval type-2 fuzzy sets (IT2 FSs), the CWW engine's output can also be an IT2 FS, A tilde, which needs to be mapped to a linguistic label so that it can be understood. Because each linguistic label is represented by an IT2 FS Bi, there is a need to compare the similarity of A tilde and B tildei to find the B tildei most similar to A tilde. In this paper, a vector similarity measure (VSM) is proposed for IT2 FSs, whose two elements measure the similarity in shape and proximity, respectively. A comparative study shows that the VSM gives more reasonable results than all other existing similarity measures for IT2 FSs.
{"title":"A Vector Similarity Measure for Interval Type-2 Fuzzy Sets","authors":"Dongrui Wu, J. Mendel","doi":"10.1109/FUZZY.2007.4295333","DOIUrl":"https://doi.org/10.1109/FUZZY.2007.4295333","url":null,"abstract":"Fuzzy logic is frequently used in computing with words (CWW). When input words to a CWW engine are modeled by interval type-2 fuzzy sets (IT2 FSs), the CWW engine's output can also be an IT2 FS, A tilde, which needs to be mapped to a linguistic label so that it can be understood. Because each linguistic label is represented by an IT2 FS Bi, there is a need to compare the similarity of A tilde and B tildei to find the B tildei most similar to A tilde. In this paper, a vector similarity measure (VSM) is proposed for IT2 FSs, whose two elements measure the similarity in shape and proximity, respectively. A comparative study shows that the VSM gives more reasonable results than all other existing similarity measures for IT2 FSs.","PeriodicalId":236515,"journal":{"name":"2007 IEEE International Fuzzy Systems Conference","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124074368","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}
Pub Date : 2007-07-23DOI: 10.1109/FUZZY.2007.4295604
J. Montes, R.M. Llorca, L. Fernandez
A novel approach for the development of linguistically interpretable fuzzy models from data is proposed. Based on this approach a methodology for inverse and indirect adaptive fuzzy control is presented. The proposed methodology includes clustering techniques to determine rules, the minimum squares method to adjust consequents and, for a sharp tuning, the descendant gradient to adjust the modal values of sets that confirm the antecedent. The antecedent partition uses triangular sets with 0.5 interpolations. The most promissory aspect in our proposal consists in achieving a great precision without sacrificing the fuzzy system interpretability. The real-world applicability of the proposed approach is demonstrated by application to a classic benchmark in system modeling and identification (Box-Jenkins gas furnace) and to a temperature control of a food process.
{"title":"Interpretable Fuzzy Models from Data and Adaptive Fuzzy Control: A New Approach","authors":"J. Montes, R.M. Llorca, L. Fernandez","doi":"10.1109/FUZZY.2007.4295604","DOIUrl":"https://doi.org/10.1109/FUZZY.2007.4295604","url":null,"abstract":"A novel approach for the development of linguistically interpretable fuzzy models from data is proposed. Based on this approach a methodology for inverse and indirect adaptive fuzzy control is presented. The proposed methodology includes clustering techniques to determine rules, the minimum squares method to adjust consequents and, for a sharp tuning, the descendant gradient to adjust the modal values of sets that confirm the antecedent. The antecedent partition uses triangular sets with 0.5 interpolations. The most promissory aspect in our proposal consists in achieving a great precision without sacrificing the fuzzy system interpretability. The real-world applicability of the proposed approach is demonstrated by application to a classic benchmark in system modeling and identification (Box-Jenkins gas furnace) and to a temperature control of a food process.","PeriodicalId":236515,"journal":{"name":"2007 IEEE International Fuzzy Systems Conference","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124076214","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}
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