Multivariable liquid level control is essential in process industries to ensure quality of the product and safety of the equipment. However, the significant problems of the control system include excessive time consumption and percentage overshoot, which result from ineffective performance of the tuning methods of the PID controllers used for the system. In this paper, fuzzy logic was used to t...

A brain emotional cerebellar model articulation controller (BECMAC) is developed, which is a mathematical model that approximates the judgmental and emotional activity of a brain. A fuzzy inference system is incorporated into the BECMAC, to give the novel fuzzy brain emotional cerebellar model articulation controller (FBECMAC) that is also proposed in this paper. The developed FBECMAC has the b...

The paper proposes the realization of a Fuzzy Logic Temperature Controller. In this paper an analysis of Fuzzy Logic Controller is made and a temperature controller using MATLAB is developed. Here we used Fuzzy Logic Toolbox which is very useful software for development and testing of Fuzzy Logic system. It can be very quickly implemented and its visual impact is very encouraging. In this contr...

In order to tackle high dimensional, complex problems, learning models have go deeper. this article, a novel multilayer ensemble model with first-order evolving fuzzy systems as its building blocks is introduced. The proposed approach can effectively learn from streaming data on sample-by-sample basis and self-organizes multilayered system structure meta-parameters in feedforward, noniterative ...

Fuzzy inference systems and neural networks are complementary technologies in the design of adaptive intelligent systems. Artificial Neural Network (ANN) learns from scratch by adjusting the interconnections between layers. Fuzzy Inference System (FIS) is a popular computing framework based on the concept of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. A neuro-fuzzy system is sim...

Two-string fuzzy inference consists of two separate inference mechanisms: One conventional fuzzy inference system that processes recommending rules, as well as a mechanism for processing negative rules, which prevent the system from outputting their associated values when their premise is fulfilled. Two-string inference has valuable applications in pattern recognition and control tasks. We pres...

Neuro-fuzzy computing, which provides efficient information processing capability by devising methodologies and algorithms for modeling uncertainty and imprecise information, forms at this juncture, a key component of soft computing. An integrated neuro-fuzzy system is simply a fuzzy inference system trained by a neural networklearning algorithm. The learning mechanism fine-tunes the underlying...

-In this paper, we analyze the impact of extinction ratio (Ron/off) of Mach-Zehnder (MZ) amplitude modulator using Fuzzy logic generator. The system performance has been analyzed by varying the value of extinction ratio (Ron/off) from 0 to 10 dB. It is found that the system gives optimum performance at extinction ratio value 9.965 dB. Further, the fuzzy model of the system is developed using AN...