Indirect Adaptive Regulator Design Based on TSK Fuzzy Models
نویسندگان
چکیده
منابع مشابه
Identifying Rule-Based TSK Fuzzy Models
ABSTRACT: This article presents a rule-based fuzzy model for the identification of nonlinear MISO (multiple input, single output) systems. The presented method of fuzzy modeling consists of two parts: (1) structure modeling, i.e., the determination of the number of rules and input variables involved respectively, and (2) parameter optimization, i.e., the optimization of the location and form of...
متن کاملLearning Accurate TSK Models Based on Local Fuzzy Prototyping
This work presents the use of local fuzzy prototypes as a first approximation to obtain accurate local semantics-based TakagiSugeno-Kang rules. A two-stage evolutionary algorithm considering the interaction between input and output variables has been developed. Firstly, it performs a local identification of prototypes, and then, a post-processing stage is considered to refine them. The proposal...
متن کاملAdaptive estimation for fuzzy TSK model-based predictive control
A long-range predictive control algorithm for nonlinear processes operating over a wide range is proposed and is based on the Takagi–Sugeno–Kang (TSK) piece-wise linear fuzzy modelling approach. The performance of the fuzzy modelling approach integrated with the proposed control algorithm to form an adaptive control scheme is examined using a series of experiments on a liquid level system and o...
متن کاملAdapted Neuro-Fuzzy Inference System on indirect approach TSK fuzzy rule base for stock market analysis
Nowadays because of the complicated nature of making decision in stock market and making real-time strategy for buying and selling stock via portfolio selection and maintenance, many research papers has involved stock price prediction issue. Low accuracy resulted by models may increase trade cost such as commission cost in more sequenced buy and sell signals because of insignificant alarms and ...
متن کاملStable Indirect Adaptive Fuzzy Control Based on Takagi-sugeno Model
This paper presents an indirect adaptive fuzzy control scheme for nonlinear uncertain stable plants with unmeasurable states. A discrete-time T-S fuzzy model is employed as a dynamic model of an unknown plant. Based on this model, a feedback linearization controller is designed and applied to both the model and the plant. Parameters of the model are updated on-line to allow for partially unknow...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Fuzzy Logic and Intelligent Systems
سال: 2006
ISSN: 1598-2645
DOI: 10.5391/ijfis.2006.6.1.052