DocumentCode :
3094959
Title :
Adaptive Backstepping Based Online Loss Minimization Control of an IM Drive
Author :
Uddin, M. Nasir ; Nam, Sang Woo
Author_Institution :
Dept. of Electr. Eng., Lakehead Univ., Thunder Bay, ON
fYear :
2007
fDate :
24-28 June 2007
Firstpage :
1
Lastpage :
9
Abstract :
Among the numerous loss minimization algorithms (LMA), a loss-model-based approach offers a fast response without torque pulsations. However, it requires the accurate loss model and the knowledge of the motor parameters. Therefore, a technical difficulty in deriving the loss model-based controller (LMC) lies in the complexity of the full loss model and the on-line motor parameter adaptation. In an effort to overcome the drawbacks of LMC, this paper presents a new strategy for inverter-fed IM drives aiming for both high efficiency and high dynamic performance. A new LMC incorporating the effect of the leakage inductance and an adaptive backstepping based nonlinear controller (ABNC) are designed and combined with each other. Thus on-line parameter adaptation of LMC can be obtained with no extra effort. The proposed control scheme is implemented in real-time using digital signal processor board DS 1104 and simulation and experimental results demonstrate the effectiveness of the proposed scheme.
Keywords :
induction motor drives; invertors; losses; machine control; nonlinear control systems; DS 1104; adaptive backstepping; digital signal processor; induction motor drive; inverter fed IM drive; leakage inductance; loss minimization algorithms; loss model based controller; nonlinear controller; online loss minimization control; online parameter adaptation; Adaptive control; Backstepping; Inductance; Induction motors; Magnetic flux; Minimization methods; Programmable control; Rotors; Stators; Torque control; Adaptive Backstepping Design; Efficiency Optimization; Induction Motor; Iron Loss Resistance; Loss Minimization; Nonlinear Control; Vector Control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering Society General Meeting, 2007. IEEE
Conference_Location :
Tampa, FL
ISSN :
1932-5517
Print_ISBN :
1-4244-1296-X
Electronic_ISBN :
1932-5517
Type :
conf
DOI :
10.1109/PES.2007.385717
Filename :
4275483
Link To Document :
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