The paper proposes a development method for PI-fuzzy controllers of Mamdani-type and of Takagi-Sugeno-type meant for two classes of second-order systems. The controllers are developed by starting from basic PI controllers tuned in terms of the Extended Symmetrical Optimum method, followed by applying the modal equivalences principle resulting in useful development steps. The developed fuzzy con...

We present a novel simplest fuzzy PID controller using a modified Takagi – Sugeno (TS) rule base. Mathematical model of the controller is derived and analyzed. The unique features of the controller are: (i) the consequent part of the rule base is closely related to the rule base of Mamdani type controller, and (ii) the proportional, integral and derivative gains vary as the output of the system...

The paper deals with both theoretical and application aspects concerning Iterative Feedback Tuning (IFT) algorithms in the design of a class of fuzzy control systems employing Mamdani-type PI-fuzzy controllers. The presentation is focused on twodegree-of-freedom fuzzy control system structures resulting in one design method. The stability analysis approach based on Popov’s hyperstability theory...

Linguistic fuzzy modeling that is usually implemented using Mamdani type of fuzzy systems suffers from the lack accuracy and high computational costs. The paper shows that product-sum inference is an immediate remedy to both problems and that in this case it is sufficient to consider symmetrical output membership functions. For the identification of the latter, a numerically efficient method is...

A new fuzzy based method to compute the initial parameter values for the optimization design phase of electronic circuits is presented. A Mamdani type fuzzy system models the relations expressing the dependencies between circuit parameters and circuit functions. This fuzzy system is able to compute the values of design parameters for every set of design requirements. This way, the optimization ...

41 ABSTRACT This paper presents the comparison of tracking control performance of fuzzy PI Controller with fuzzy PID and conventional PID controllers. Fuzzy PI controller and Fuzzy PID controller composes of Mamdani type fuzzy controllers and parameters are adjusted to meet the desired control system performances both in transient state and steady state. Computer simulations are done for contro...

Normally a decision support system is build to solve problem where multicriteria decisions are involved. The knowledge base is the vital part of the decision support containing the information or data that is used in decision-making process. This is the field where engineers and scientists have applied several intelligent techniques and heuristics to obtain optimal decisions from imprecise info...

The aim of the research is to control the quality of the pulp and the functional condition of the refiners using statistical process control (SPC) and fuzzy modelling techniques. The on-line measurements and the SPC parameters are combined with the Mamdani type fuzzy models. The models and the “indexes” are used for the optimisation and the fault diagnosis purposes in the industrial scale pulp ...

In This paper, the authors propose a Sensorless Direct Torque and Flux Control (DTFC) of Induction Motor (IM) using two approach intelligent techniques: Mamdani Fuzzy Logic (FL) controller is used for controlling the rotor speed and Artificial Neural Network (ANN) applied in switching select stator voltage. We estimated the rotor speed by using the Model Reference Adaptive Systems (MRAS). The c...

Genetic algorithms and evolution strategies are combined in order to build a multi-stage hybrid evolutionary algorithm for learning constrained approximate Mamdani-type knowledge bases from examples. The genetic algorithm niche concept is used in two of the three stages composing the learning process with the purpose of improving the accuracy of the designed fuzzy rule-based systems. The propos...