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Bottom up synthesis based on fuzzy schedules

Tai A. Ly, Jack T. Mowchenko
1991 Proceedings of the 28th conference on ACM/IEEE design automation conference - DAC '91  
In this paper, we present a new bottom up synthesis formulation designed for full allocation of data path operations and data values prior to scheduling.  ...  This work is novel because it treats unscheduled operations as having uncertain schedules, then applies fuzzy set theory to quantify these uncertainties during allocation.  ...  Discussions In this section, we compare fuzzy allocation with probability based bottom-up synthesis [lo] and with design partitioning [71.  ... 
doi:10.1145/127601.127749 dblp:conf/dac/LyM91 fatcat:b7atyj24ovdxvp6zagnmgk7rm4

Fuzzy gain scheduling: controller and observer design based on lyapunov method and convex optimization

P. Korba, R. Babuska, H.B. Verbruggen, P.M. Frank
2003 IEEE transactions on fuzzy systems  
The synthesis is based on linear matrix inequalities and convex optimization techniques.  ...  This paper addresses model-based fuzzy control. A constructive and automated method for the design of a gain-scheduling controller is presented.  ...  Extended Fuzzy Scheduler Based on the fuzzy scheduler described in Section II-B, which is for also known as PDC [11] , [13] , an EFS can be derived.  ... 
doi:10.1109/tfuzz.2003.812680 fatcat:eo3nxstu5jdaxgb6napvkt5oh4

Fuzzy wide-range control of fossil power plants for life extension and robust performance

P. Kallappa, Asok Ray
2000 Automatica  
This paper presents a fuzzy-logic-based methodology of life extending control (LEC) for robust wide-range operation of fossil power plants including load-following, scheduled shutdown, and hot startup.  ...  The fuzzy algorithm facilitates bumpless controller switching for gain scheduling under wide-range operation and control.  ...  The LEC system synthesis is carried out based on the dynamic models of: the power plant under control and structural damage in critical components.  ... 
doi:10.1016/s0005-1098(99)00103-x fatcat:k344ej33nrfxbb7vm3amw7vyne

Robust stability analysis and fuzzy-scheduling control for nonlinear systems subject to actuator saturation

Yong-Yan Cao, Zongli Lin
2003 IEEE transactions on fuzzy systems  
Based on this set invariance condition, the problem of estimating the domain of attraction of a TS fuzzy system under a constant state feedback law is formulated and solved as a linear matrix inequality  ...  A fuzzy scheduling control design method is also introduced to further enlarge the domain of attraction. An inverted pendulum is used to show the effectiveness of the proposed fuzzy controller.  ...  problem of balancing and swing-up of an inverted pendulum on a cart.  ... 
doi:10.1109/tfuzz.2002.806317 fatcat:cpqqcgbz5rharli3ovx2oruy44

Parameterized linear matrix inequality techniques in fuzzy control system design

H.D. Tuan, P. Apkarian, T. Narikiyo, Y. Yamamoto
2001 IEEE transactions on fuzzy systems  
The advantages of the proposed methods over earlier ones are then discussed and illustrated through numerical examples and simulations.  ...  Index Terms-Fuzzy systems, parameterized linear matrix inequality (PLMI).  ...  To sum up, we state the following theorem.  ... 
doi:10.1109/91.919253 fatcat:azbk5vrh35boza42gwziwcvale

Adaptive Fuzzy Hardware Scheduler for Real Time Operating System

D. G. Harkut, et.al.
2016 International Journal of Computing and Digital Systems  
This paper proposes the novel FIS based adaptive hardware task scheduler for multiprocessor systems that minimizes the processor time for scheduling activity which uses fuzzy logic to model the uncertainty  ...  This Fuzzy logic based adaptive hardware scheduler breakthroughs the limit of the number of total task and thus improves efficiency of the entire real-time system.  ...  Global Fuzzy scheduler -Long term scheduler. (FIS 1) 2. Local Adaptive scheduler -Short term scheduler.  ... 
doi:10.12785/ijcds/050606 fatcat:2vlhjuiqgnbrrdo42gqsk3gw34

2007 Index IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans Vol. 37

2007 IEEE transactions on systems, man and cybernetics. Part A. Systems and humans  
Yu, F., +, TSMCA Sept. 2007 746-757 Bottom-Up Construction of Minimum-Cost AND/ OR Trees for Sequential Fault Diagnosis. Kundakcioglu, O. E., +, TSMCA Sept. 2007 621-629 Fuzzy Ants and Clustering.  ...  ., +, TSMCA March 2007 226-236 Bottom-Up Construction of Minimum-Cost AND/ OR Trees for Sequential Fault Diagnosis. Kundakcioglu, O.  ... 
doi:10.1109/tsmca.2007.910186 fatcat:xhncxznowvbldf3pbmdfjdrnhq

Stable Fault Tolerant Controller Design for Takagi–Sugeno Fuzzy Model-Based Control Systems via Linear Matrix Inequalities: Three Conical Tank Case Study

Himanshukumar R. Patel, Vipul A. Shah
2019 Energies  
After that, based on this linear model, we employ parallel distributed compensation for designing linear controllers for each linear model.  ...  However, the controller synthesis for nonlinear systems described by the T–S fuzzy model is a complicated task, which can be reduced to convex problems linking with linear matrix inequalities (LMIs).  ...  regions and then weighted scheduler is designed to adjust the Controller parameter based on the operating regions.  ... 
doi:10.3390/en12112221 fatcat:i255ryxvijabffd7ravzg52yvi

Fuzzy Logic Based Hardware Accelerator with Partially Reconfigurable Defuzzification Stage for Image Edge Detection

Aous H. Kurdi, Janos L. Grantner, Ikhlas M. Abdel-Qader
2017 International Journal of Reconfigurable Computing  
In this paper, the design and the implementation of a pipelined hardware accelerator based on a fuzzy logic approach for an edge detection system are presented.  ...  Its peak performance is up to 58 high definition frames per second.  ...  Dynamic Partially Reconfigurable Design At the time of writing this paper, the Vivado Design Suite supports only nonproject Tcl-based design flow for partial reconfiguration designs on FPGAs using bottom-up  ... 
doi:10.1155/2017/1325493 fatcat:rsuyuigs7jfejpga7c6dgokg3a

LMI-Fuzzy Control Design for Non-Minimum-Phase DC-DC Converters: An Application for Output Regulation

Carlos Andrés Torres-Pinzón, Leonel Paredes-Madrid, Freddy Flores-Bahamonde, Harrynson Ramirez-Murillo
2021 Applied Sciences  
This work presents the design of a fuzzy control synthesis based on a T-S fuzzy model for non-minimum phase dc-dc converters, such as boost and buck-boost.  ...  Finally, the fuzzy controller design based on LMIs is solved for the defined specification in close loop through MATLAB toolbox LMI.  ...  Build up the rule-base R i of the T-S fuzzy model.  ... 
doi:10.3390/app11052286 fatcat:pas3ssokdnfepd4slhv55r5fhm

A Review on AI Control of Reactive Distillation for Various Applications [chapter]

Vandana Sakhre
2020 Wastewater Treatment [Working Title]  
In this chapter, previous studies on reactive distillation process control including control using conventional as well as soft sensor control, membrane assisted reactive distillation design and simulation  ...  The chapter is focused on dynamics and control of Reactive distillation, its control using Conventional Techniques, Model Predictive Control MPC), Reactive Distillation using Soft Sensors/Soft Controllers  ...  Model gain scheduling was included in one of the control strategies for reactive distillation.  ... 
doi:10.5772/intechopen.94023 fatcat:4rj3qkdlz5defma563f2qopjaq

Simulation Model of Wind Turbine Power Control System with Fuzzy Regulation by Mamdani and Larsen Algorithms

Ghada Adel Aziz
2017 ˜Al-œKhawarizmi engineering journal  
The aim of this work is to create a power control system for wind turbines based on fuzzy logic.  ...  effective on these wind turbines control.  ...  The Fuzzy Inference Larsen Algorithm The rule base of the rules is based on many inputs and many output variables.  ... 
doi:10.22153/kej.2017.01.003 fatcat:35vgjgsfgveypgecdtov76iqkm

Integration of code optimization and hardware exploration for a VLIW architecture by using fuzzy control system

Xiaoyan Jia, Gerhard Fettweis
2011 2011 IEEE International SOC Conference  
Up to 42.4% register read and 67.9% register write operations are cut down on average.  ...  To improve the system efficiency of STA, in this paper we propose a novel approach to integrate compiler techniques with architecture exploration: A fuzzy control system is implemented to help the compiler  ...  By reading this machine description, the STA code generator generates the assembly based on the compiled ARM code.  ... 
doi:10.1109/socc.2011.6085072 dblp:conf/socc/JiaF11 fatcat:67b6ngvedfhznmjh7wb7uu5uwi

Hierarchical genetic optimization of a fuzzy logic system for energy flows management in microgrids

Enrico De Santis, Antonello Rizzi, Alireza Sadeghian
2017 Applied Soft Computing  
Results are compared with a simpler approach based on a classic fuzzy-GA scheme, where both FIS parameters and rule weights are tuned, while the number of fuzzy rules is fixed in advance.  ...  In particular, this study focuses on the application of a Hierarchical Genetic Algorithm (HGA) for tuning the Rule Base (RB) of a Fuzzy Inference System (FIS), trying to discover a minimal fuzzy rules  ...  In particular given the load demand, the wind power generation and day-ahead electricity prices, the algorithm is able to set up a MG generation schedule and to synthesize a suitable fuzzy expert system  ... 
doi:10.1016/j.asoc.2017.05.059 fatcat:qtqwhuoirjhyppnhjc3pyehpge

MODEL REFERENCE FUZZY CONTROL SYSTEM OF BRAIN TEMPERATURE FOR HYPOTHERMIA TREATMENT

H. Wakamatsu, T. Wakatsuki, T. Utsuki
2005 IFAC Proceedings Volumes  
The model reference fuzzy control of the brain temperature based on water-cooling blankets is verified for the clinical application to brain hypothermia treatment through the various kinds of simulation  ...  The brain temperature is successfully realized to follow up the desired temperature course automatically.  ...  The third illustration is for the consequent and the bottom table is the fuzzy rule for the subsystemare fuzzificated based on the membership functions of the antecedents given by Fig Fig.4-(b-2) for  ... 
doi:10.3182/20050703-6-cz-1902.02156 fatcat:kkxk5xd6afbfvdw5gokexn2on4
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