A On-line Rule Tuning Grey Prediction Fuzzy Control System Design
نویسندگان
چکیده
An on-line rule tuning grey prediction fuzzy control system is present in this paper, which contains the advantage of the grey prediction, fuzzy theory and the on-line tuning algorithm. The on-line rule tuning grey prediction fuzzy control system structure is constructed so that the rise time and the overshoot of the controlled system can be maintained simultaneously. Keyword: Grey predictor, Fu zzy control system, On-line rule tuning.
منابع مشابه
Proposing a Novel Cost Sensitive Imbalanced Classification Method based on Hybrid of New Fuzzy Cost Assigning Approaches, Fuzzy Clustering and Evolutionary Algorithms
In this paper, a new hybrid methodology is introduced to design a cost-sensitive fuzzy rule-based classification system. A novel cost metric is proposed based on the combination of three different concepts: Entropy, Gini index and DKM criterion. In order to calculate the effective cost of patterns, a hybrid of fuzzy c-means clustering and particle swarm optimization algorithm is utilized. This ...
متن کاملNeuro-fuzzy Based Control Loop Tuner
An alternative approach for intelligent tuning of a control loop will be presented in this paper. The objective is to design an algorithm which will tune the controller employing a neuro-fuzzy based algorithm. Structure and design method based on this approach will be explored, which include an adaptive network employed as building block, the backpropagation gradient method and least square est...
متن کاملDynamic Evolving Neuro-Fuzzy Inference System (DENFIS): On-line learning and Application for Time-Series Prediction
This paper introduces a new type of fuzzy inference systems, denoted as DENFIS (dynamic evolving neural-fuzzy system), for adaptive on-line learning, and its application for dynamic time series prediction. DENFIS evolve through incremental, hybrid (supervised/unsupervised), learning and accommodate new input data, including new features, new classes, etc. through local element tuning. New fuzzy...
متن کاملA Fuzzy Expert System for Predicting the Performance of Switched Reluctance Motor
In this paper a fuzzy expert system for predicting the performance of a switched reluctance motor has been developed. The design vector consists of design parameters, and output performance variables are efficiency and torque ripple. An accurate analysis program based on Improved Magnetic Equivalent Circuit (IMEC) method has been used to generate the input-output data. These input-output data i...
متن کاملDesign of Self-Tuning Fuzzy Logic Controller
During the past several years fuzzy control has emerged as one of the most active and fruitful areas of research in the field of control engineering especially, in the realm of industrial processes. Fuzzy control, based on fuzzy logic is a logical system which incorporates human thinking rather than traditional analytical methods. Therefore, this paper aims to explore the utility of this contro...
متن کامل