The Experts below are selected from a list of 96843 Experts worldwide ranked by ideXlab platform
Melinpatricia - One of the best experts on this subject based on the ideXlab platform.
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Embedding a high speed interval type-2 fuzzy controller for a Real Plant into an FPGA
Applied Soft Computing, 2012Co-Authors: Sepúlvedaroberto, Montieloscar, Castillooscar, MelinpatriciaAbstract:The main goal of this paper is to show that interval type-2 fuzzy inference systems (IT2 FIS) can be used in applications that require high speed processing. This is an important issue since the us...
Patricia Melin - One of the best experts on this subject based on the ideXlab platform.
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Embedding a high speed interval type-2 fuzzy controller for a Real Plant into an FPGA
Applied Soft Computing, 2012Co-Authors: Roberto Sepúlveda, Oscar Montiel, Oscar Castillo, Patricia MelinAbstract:The main goal of this paper is to show that interval type-2 fuzzy inference systems (IT2 FIS) can be used in applications that require high speed processing. This is an important issue since the use of IT2 FIS still being controversial for several reasons, one of the most important is related to the resulting shocking increase in computational complexity that type reducers, like the Karnik-Mendel (KM) iterative method, can cause even for small systems. Hence, comparing our results against a typical implementation of a IT2 FIS using a high level language implemented into a computer, we show that using a hardware implementation the the whole IT2 FIS (fuzzification, inference engine, type reducer and defuzzification) last only four clock cycles; a speed up of nearly 225,000 and 450,000 can be obtained for the Spartan 3 and Virtex 5 Field Programmable Gate Arrays (FPGAs), respectively. This proposal is suitable to be implemented in pipeline, so the complete IT2 process can be obtained in just one clock cycle with the consequently gain in speed of 900,000 and 2,400,000 for the aforementioned FPGAs. This paper also shows that the iterative KM method can be efficient if it is adequately implemented using the appropriate combination of hardware and software. Comparative experiments of control surfaces, and time response in the control of a Real Plant using the IT2 FIS implemented into a computer against the IT2 FIS into an FPGA are shown.
Jialin Liu - One of the best experts on this subject based on the ideXlab platform.
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Modeling a Large-Scale Nonlinear System Using Adaptive Takagi−Sugeno Fuzzy Model on PCA Subspace
Industrial & Engineering Chemistry Research, 2007Co-Authors: Jialin LiuAbstract:A data-driven Takagi−Sugeno fuzzy model is developed for modeling a Real Plant situation with the dependent inputs and the nonlinear and time-varying input−output relation. The collinearity of inpu...
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JCIS - Adaptive Fuzzy Modeling For A Large-Scale Nonlinear System
Proceedings of the 9th Joint Conference on Information Sciences (JCIS), 2006Co-Authors: Jialin LiuAbstract:A data-driven Takagi-Sugeno (TS) fuzzy model is developed for modeling a Real Plant with the dependent inputs, the nonlinear and the time-varying input-output relation. The collinearity of inputs can be eliminated through the principal component analysis (PCA). The TS model split the operating region into a collection of IF-THEN rules. For each rule, the premise is generated from clustering the compressed input data and the consequence is represented as a linear model. A post-update algorithm for model parameters is also proposed to accommodate the timevarying nature. Effectiveness of the proposed model is demonstrated using Real Plant data from a polyethylene process.
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On-line soft sensor for polyethylene process with multiple production grades
Control Engineering Practice, 2005Co-Authors: Jialin LiuAbstract:Abstract Since online measurement of the melt index (MI) of polyethylene is difficult, a virtual sensor model is desirable. However, a polyethylene process usually produces products with multiple grades. The relation between process and quality variables is highly nonlinear. Besides, a virtual sensor model in Real Plant process with many inputs has to deal with collinearity and time-varying issues. A new recursive algorithm, which models a multivariable, time-varying and nonlinear system, is presented. Principal component analysis (PCA) is used to eliminate the collinearity. Fuzzy c-means (FCM) and fuzzy Takagi–Sugeno (FTS) modeling are used to decompose the nonlinear system into several linear subsystems. Effectiveness of the model is demonstrated using Real Plant data from a polyethylene process.
Sepúlvedaroberto - One of the best experts on this subject based on the ideXlab platform.
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Embedding a high speed interval type-2 fuzzy controller for a Real Plant into an FPGA
Applied Soft Computing, 2012Co-Authors: Sepúlvedaroberto, Montieloscar, Castillooscar, MelinpatriciaAbstract:The main goal of this paper is to show that interval type-2 fuzzy inference systems (IT2 FIS) can be used in applications that require high speed processing. This is an important issue since the us...
Roberto Sepúlveda - One of the best experts on this subject based on the ideXlab platform.
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Embedding a high speed interval type-2 fuzzy controller for a Real Plant into an FPGA
Applied Soft Computing, 2012Co-Authors: Roberto Sepúlveda, Oscar Montiel, Oscar Castillo, Patricia MelinAbstract:The main goal of this paper is to show that interval type-2 fuzzy inference systems (IT2 FIS) can be used in applications that require high speed processing. This is an important issue since the use of IT2 FIS still being controversial for several reasons, one of the most important is related to the resulting shocking increase in computational complexity that type reducers, like the Karnik-Mendel (KM) iterative method, can cause even for small systems. Hence, comparing our results against a typical implementation of a IT2 FIS using a high level language implemented into a computer, we show that using a hardware implementation the the whole IT2 FIS (fuzzification, inference engine, type reducer and defuzzification) last only four clock cycles; a speed up of nearly 225,000 and 450,000 can be obtained for the Spartan 3 and Virtex 5 Field Programmable Gate Arrays (FPGAs), respectively. This proposal is suitable to be implemented in pipeline, so the complete IT2 process can be obtained in just one clock cycle with the consequently gain in speed of 900,000 and 2,400,000 for the aforementioned FPGAs. This paper also shows that the iterative KM method can be efficient if it is adequately implemented using the appropriate combination of hardware and software. Comparative experiments of control surfaces, and time response in the control of a Real Plant using the IT2 FIS implemented into a computer against the IT2 FIS into an FPGA are shown.
