<p class="Author"><span>It is known that controlling the speed of a three phase Induction Motor (IM) under different operating conditions is an important task and this can be accomplished through the process of controlling the applied voltage on its stator circuit. Conventional Proportional- Integral- Differeantional (PID) controller takes long time in selecting the error signal gain values. In this paper a hybrid Fuzzy Logic Controller (FLC) with Genetic Algorithm (GA) is proposed to reduce the selected time for the optimized error signal gain values and as a result inhances the controller and system performance. The proposed controller FL with GA is designed, modeled and simulated using MATLAB/ software under different load torque motor operating condition. The simulation result shows that the closed loop system performance efficiency under the controller has a maximum value of 95.92%. In terms of efficiency and at reference speed signal of 146.53 rad/sec, this system performance shows an inhancement of 0.67%,0.49% and 0.05% with respect to the closed loop system efficiency performance of the PID, FL, and PID with GA controllers respectively. Also the simulation result of the well designed and efficient GA in speeding up the process of selecting the gain values, makes the system to have an efficiency improvement of 14.42% with respect to the open loop system performance.</span></p>
Due to the required different speeds and important role of direct current (DC) motors in laboratories, production factories and industrial application, speed controlling of these motors becomes an essential matter for proper operation with high efficiency and performance accuracy. This paper presents a new speed controlling technique that is based on particle swarm optimization (PSO) algorithm in the optimization process of the parameters for the fractional order proportional–integral–derivative (FOPID) controller. The FOPID is an advanced and modern controlling system in which the two more added parameters (the derivative μ and integral λ orders) are fractional rather than integer. Through the process of minimizing the fitness functions, the obtained results show that the designed controller system can excellently set the best controller parameters due to the fractions of these additional parameters. With respect to the PSO-PID controller, the simulation results for the proposed PSO-FOPID controller show performance improvements of 14%, 21%, 24.5%, 78%, and 19.3% in the values of the parameters Kp, Ki, Kd, Tr, and Ts respectively.
This paper investigates the applicability of star, tree and mesh topology schemes for large scale Wireless Sensor Network (WSN) complying with IEEE 802.15.4 standard. The main focus of this work is to evaluate the performance of such network through simulation which is carried out via the discrete event OPNET simulator (version 14.5). The performance metrics of interest include throughput, end to end delay and packet drop rates. Performance comparison and analyses of different topologies have been made, and it is concluded that the selection of topology scheme depends on the application context.
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