Using Emperor and Particle Swarm Optimization Algorithm to Optimize Induction Motor Control System
نویسندگان
چکیده
In this paper, the simulation and optimization of induction motor through its controlling and modeling by convert d-q with Simulink of Matlab Software has been developed. By utilization of classic PI controller and also with phase controller has been optimized which membership function center of it has been optimized by new intelligent algorithms such as Emperor and Particle Swarm Optimization (PSO). The obtained results show that obtaining phase points by new intelligent controllers such as Emperor and PSO ones have better results than classic PID and fuzzy controllers. In fact the experimental results show that the error of Emperor Algorithm is lower than PSO. Thus the emperor algorithm optimizes membership function centers of phase controllers better than PSO one.
منابع مشابه
Optimal Rotor Fault Detection in Induction Motor Using Particle-Swarm Optimization Optimized Neural Network
This study examined and presents an effective method for detection of failure of conductor bars in the winding of rotor of induction motor in low load conditions using neural networks of radial-base functions. The proposed method used Hilbert method to obtain the stator current signal push. The frequency and signal amplitude of the push stator were used as the input of the neural network and th...
متن کاملOptimal design of squirrel cage induction motor using multi-objective Salp Swarm Algorithm
The design of three-phase induction motors is a challenge in electrical engineering. Therefore, new design techniques are continuously provided. Since the design of the induction motors is carried out for different purposes, it is difficult to find a method that can addresses all the targets. Nowadays, the normal methods used to solve multi-objective problems are the optimization strategies. In...
متن کاملSensorless Speed Based on MRAS with Tuning of IP Speed Controller in FOC of Induction Motor Drive Using PSO
In this paper, a field oriented control (FOC) induction motor drive is presented. In order to eliminate the speed sensor, an adaptation algorithm for tuning the rotor speed is proposed. Based on the Model Reference Adaptive System (MRAS) scheme, the rotor speed is tuned to obtain an exact FOC induction motor drive. The reference and adjustable models, developed in stationary stator reference fr...
متن کاملFrequency Control of Isolated Hybrid Power Network Using Genetic Algorithm and Particle Swarm Optimization
This paper, presents a suitable control system to manage energy in distributed power generation system with a Battery Energy Storage Station and fuel cell. First, proper Dynamic Shape Modeling is prepared. Second, control system is proposed which is based on Classic Controller. This model is educated with Genetic Algorithm and particle swarm optimization. The proposed strategy is compared with ...
متن کاملLoad Frequency Control in Power Systems Using Improved Particle Swarm Optimization Algorithm
The purpose of load frequency control is to reduce transient oscillation frequencies than its nominal valueand achieve zero steady-state error for it.A common technique used in real applications is to use theproportional integral controller (PI). But this controller has a longer settling time and a lot of Extramutation in output response of system so it required that the parameters be adjusted ...
متن کامل