Saif Ghith Ehab (9 results)

Condition: New. pp. 240.

Taschenbuch. Condition: Neu. Induction Motor Speed Control Technique Using Intelligent Methods | Intelligent control methods such as FLC,ANN,ANFIS and Optimization control Techniques such as GA,SQP,PSO | Ehab Saif Ghith (u. a.) | Taschenbuch | 240 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659413056 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Book relates to the speed control of an induction motor introduced intelligent methods such as Fuzzy Logic Control (FLC), Artificial Neural Networks (ANN), Adaptive Neural Fuzzy Inference System (ANFIS) and Optimization Techniques such as Genetic Algorithm (GA), Sequential Quadratic Programming (SQP) and Particle Swarm Optimization Algorithms(PSO).The results showed that the PSO-PI controller can perform with an efficient way for searching for the optimal PI controller. Comparison study among fuzzy logic, neural network, Adaptive Neural Fuzzy Inference System , genetic algorithm, sequential quadratic programming and particle swarm optimization controllers are performed. These methods can improve the dynamic performance of the system in a better way.The PI-PSO controller is the best method based on integrated of time weight absolute error (ITAE)criteria which presented satisfactory performances and possesses good robustness (no overshoot, minimal rise time, steady state error almost to zero value). A comparison study has been done between selected methods and some other technique which showed that the proposed controller has setting time less than other methods by 40%. 240 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Saif Ghith Ehab*M.Sc. In Systems Engineering and Engineering Management, South Westphalia University of Applied Sciences,Germany,2013.*M.Sc. In System s Automation and Engineering Management,Helwan University, Egypt,2013.*Research to.

Condition: New. Print on Demand pp. 240 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Condition: New. PRINT ON DEMAND pp. 240.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Book relates to the speed control of an induction motor introduced intelligent methods such as Fuzzy Logic Control (FLC), Artificial Neural Networks (ANN), Adaptive Neural Fuzzy Inference System (ANFIS) and Optimization Techniques such as Genetic Algorithm (GA), Sequential Quadratic Programming (SQP) and Particle Swarm Optimization Algorithms(PSO).The results showed that the PSO-PI controller can perform with an efficient way for searching for the optimal PI controller. Comparison study among fuzzy logic, neural network, Adaptive Neural Fuzzy Inference System , genetic algorithm, sequential quadratic programming and particle swarm optimization controllers are performed. These methods can improve the dynamic performance of the system in a better way.The PI-PSO controller is the best method based on integrated of time weight absolute error (ITAE)criteria which presented satisfactory performances and possesses good robustness (no overshoot, minimal rise time, steady state error almost to zero value). A comparison study has been done between selected methods and some other technique which showed that the proposed controller has setting time less than other methods by 40%.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 240 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Book relates to the speed control of an induction motor introduced intelligent methods such as Fuzzy Logic Control (FLC), Artificial Neural Networks (ANN), Adaptive Neural Fuzzy Inference System (ANFIS) and Optimization Techniques such as Genetic Algorithm (GA), Sequential Quadratic Programming (SQP) and Particle Swarm Optimization Algorithms(PSO).The results showed that the PSO-PI controller can perform with an efficient way for searching for the optimal PI controller. Comparison study among fuzzy logic, neural network, Adaptive Neural Fuzzy Inference System , genetic algorithm, sequential quadratic programming and particle swarm optimization controllers are performed. These methods can improve the dynamic performance of the system in a better way.The PI-PSO controller is the best method based on integrated of time weight absolute error (ITAE)criteria which presented satisfactory performances and possesses good robustness (no overshoot, minimal rise time, steady state error almost to zero value). A comparison study has been done between selected methods and some other technique which showed that the proposed controller has setting time less than other methods by 40%.