Title :
Robust emerged artificial intelligence speed controller for PMSM drive
Author :
Rayd, Hamza ; Zahid, Noureddine ; Idrissi, Aziz EI Lanati EI ; Jedra, Mohamed
Author_Institution :
Dept. of Phys., Mohamed V Agdal Univ., Rabat, Morocco
Abstract :
Artificial intelligence based fusion (AIF) is a new soft optimization method that is based on the emerged science of soft computing (expert system, fuzzy logic, neural Network and genetic algorithm...) with optimal mathematical state equation (Extended Kalman filter...). In this paper we propose two optimized soft to constraint the new controller for PMSM. First, we propose a recurrent neural network controller trained with extended kalman filter results show that is better than backpropagation. Second, we employ GA to solve EKF covariance optimization problems. The approach that we use does not require any additional mathematical model of the dynamical system beyond those that are required for classical automation problems. The constrained hybrid artificial controller algorithm is compared with solutions based on a conventional controller, classical recurrent neural network controller (RNNC) and genetic algorithm (GAC) the simulated results demonstrate that constrained HAIC is more suitable for modern automation.
Keywords :
Kalman filters; angular velocity control; artificial intelligence; expert systems; fuzzy logic; genetic algorithms; machine control; nonlinear filters; permanent magnet motors; recurrent neural nets; synchronous motor drives; AIF; EKF covariance optimization problems; PMSM drive; artificial intelligence based fusion; classical automation problems; constrained hybrid artificial controller; expert system; extended Kalman filter; fuzzy logic; genetic algorithm; optimal mathematical state equation; permanent magnet synchronous motor drive; recurrent neural network controller; robust emerged artificial intelligence; soft computing; soft optimization; speed controller; Kalman filters; Magnetic flux; Magnetic separation; Rotors; Sociology; Statistics; Synchronous motors; Artificial intelligence; extended kalman filter; genetic algorithm; neural network; permanent magnet synchronous motor;
Conference_Titel :
Complex Systems (WCCS), 2014 Second World Conference on
Print_ISBN :
978-1-4799-4648-8
DOI :
10.1109/ICoCS.2014.7060952