Title :
Implementation techniques for the matrix Riccati differential equation solution for energetic optimization of the AC drives
Author :
Gaiceanu, Marian
Author_Institution :
Dept. of Electr. Eng., "Dunarea de Jos" Univ., Galati, Romania
Abstract :
This paper presents the energetic optimization of induction motor (IM) drives. The implementation methods of the optimal solution are described. The optimal solution may be applied to the three phase squirrel cage IM that is supplied either by using a current source inverter, or voltage source inverter. Thus, the entire existent power range is covered. By using the nonrecursive method, the optimal solution is calculated for each sampling period at the current time, not backward in time as in the recursive case. The use of a zero order hold provides the numerical solution. By using the artificial intelligence (neuronal networks, fuzzy and neuro-fuzzy logic), the author has developed and implemented optimal control systems with a three phase IM. The optimal control provides dynamic regimes with minimal input energy and performs the minimization of the copper losses from the IM at the same output power with the classical control. The experimental results illustrate the optimal control features
Keywords :
Riccati equations; differential equations; fuzzy neural nets; induction motor drives; matrix algebra; neurocontrollers; optimal control; optimisation; rotors; differential equation; fuzzy neural network; induction motor drives; matrix Riccati equation; optimal control; optimization; rotor; squirrel cage motors; Artificial intelligence; Biological neural networks; Fuzzy control; Fuzzy logic; Induction motors; Inverters; Optimal control; Riccati equations; Sampling methods; Voltage;
Conference_Titel :
Control Applications, 2001. (CCA '01). Proceedings of the 2001 IEEE International Conference on
Conference_Location :
Mexico City
Print_ISBN :
0-7803-6733-2
DOI :
10.1109/CCA.2001.973929