This paper presents the similarity of a class of adaptive fuzzy controllers and a time dependent single rule controller of TakagiSugeno (TS) model. The class of adaptive fuzzy controllers is one of iterative multilayer structure of single input fuzzy controllers (SIFC). On the other hand, in a time dependent single rule controller of TS model, only one rule can be fired at a time. The result mo...

A group of multi-input-single-output fuzzy logic controllers are designed for a nuclear power plant to control turbine power, reactor pressure, and reactor water level based on input-output data from plant simulations with conventional PI controllers. Simulations show that fuzzy logic control may result in faster reference signal tracking and final value holding. Milder control actions of fuzzy...

Recently, there is great deal of interest in the use of fuzzy expert systems in control applications. Controllers based on fuzzy logic belong to the class of static or memoryless nonlinear controllers and provide better control than is possible using linear control. The major strength of fuzzy controllers lies in the way a nonlinear output mapping of a number of inputs can be specified easily u...

In this paper, analytical structures of TITO (two-input two-output) Mamdani fuzzy PI/PD controllers are investigated with respect to conventional PI/PD control and variable gain control. Components of the fuzzy controllers include two input fuzzy sets for each input variable, five singleton output fuzzy sets for each output variable, 16 fuzzy rules, product AND fuzzy logic operator, the Mamdani...

This paper discusses the design of neural network and fuzzy logic controllers using genetic algorithms, for real-time control of flows in sewerage networks. The soft controllers operate in a critical control range, with a simple set-point strategy governing "easy" cases. The genetic algorithm designs controllers and set-points by repeated application of a simulator. A comparison between neural ...

In this paper, a fuzzy controllers type Takagi_Sugeno is optimized by method of Particle Swarm Optimization (PSO). This algorithm automatically adjust the membership function of fuzzy controllers to control a trajectory of nonholonomic mobile robot that involves path trajectory using two optimized fuzzy controllers one for speed control and the other for azimuth control. The mobile robot is mod...

This paper presents a design approach intended for the modeling and synthesis of discrete-event modules of hybrid controllers by combining a model of computation and a soft computing synthesis approach. The model of computation is based on coloured Petri nets (CPNs) and the soft computing method uses fuzzy logic. The design approach converts Petri net models into their equivalent fuzzy sets for...

In the paper, using some MATLAB fuzzy logic toolbox Demos, in which the fuzzy controllers are compared with the classical PID ones, it is shown that the well tuned classical PID are significantly better than those fuzzy presented in the Demos. It is shown, that using fuzzy approach, it is very difficult to shape the input-output nonlinearity, describing the so called fuzzy block of the fuzzy co...

This paper presents an approach that allows to evolve fuzzy controllers that can be expressed as fuzzy rules in human-readable form and interpreted. For comparison, the evolution is also performed on simple neural controllers. The control task considered here is a balancing problem, where a construct made of articulated elastic elements is equipped with sensors and actuators. The goal of the co...