<span>Distributed generation (DG) is an essential attributor in smart grid to fulfill the uncontrollable increase in the demand for energy. Artificial intelligent optimization techniques are widely used within automation systems for guarantee the optimal operation and utilization of DG allocation on the day-ahead power scheduling. In this paper, the genetic algorithm technique used for obtaining the optimal utilization of the automated operation of distributed generation for power losses and total cost minimization as well as user comfort maximization considering all operating constraints technique. Distributed generation represented by fuel cells to supply part of the daily demand in the power system. The target is to apply decision-making strategy of smart operation for economical and reliable operation of power system. Concentrated fuel cell units considered representing the available DG at the load centers. The methodology applied to the 11-bus test system. The simulation results have demonstrated that the GA capability for full automation of DGs in a smart manner within the power system for economic and safe operation</span>
The development of a fu zzy-logic controller for a class of industrial hydraulic man ipulator is described. The main element of the controller is a PItype fuzzy control technique which utilizes a simp le set of membership functions and rules to meet the basic control requirements of such robots. Using the triangle shaped membership function, the position of the servocylinder was successfully controlled. When the system parameter is altered, the control algorith m is shown to be robust and more faster co mpared to the traditional PID controller. The robustness and tracking ability of the controller were demonstrated through simulations.
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