DocumentCode :
605401
Title :
PID control scheme for twin rotor MIMO system using a real valued genetic algorithm with a predetermined search range
Author :
Prasad, Durga G. ; Manoharan, P.S. ; Ramalakshmi, A.P.S.
Author_Institution :
Dept. of Electr. & Electron. Eng., Thiagarajar Coll. of Eng., Madurai, India
fYear :
2013
fDate :
6-8 Feb. 2013
Firstpage :
443
Lastpage :
448
Abstract :
This paper discusses the proportional-integral-derivative control scheme for a twin rotor multiple input multiple output system (TRMS), which is a nonlinear system with two degrees of freedom and cross couplings. The objectives of the work are to stabilize the TRMS, to attain a particular position and to make it to track a trajectory. Four PID controllers are used for achieving the objectives. The parameters of the PID controllers are tuned using the real valued genetic algorithm (RGA). The initial search range of the RGA is obtained using a control design optimization (CDO) technique. The control scheme is initially implemented for the decoupled system viz., horizontal and vertical 1-degree of freedom (1-DOF) systems, using 1 PID controller for each system, and it is followed by the implementation of the control scheme for the 2-degree of freedom (2-DOF) System.
Keywords :
MIMO systems; genetic algorithms; machine control; nonlinear control systems; rotors; three-term control; 1-DOF systems; 2-DOF System; CDO technique; PID control scheme; RGA; control design optimization technique; cross couplings; degrees of freedom; horizontal 1-degree of freedom systems; initial search range; nonlinear system; predetermined search range; proportional-integral-derivative control scheme; real valued genetic algorithm; twin rotor MIMO system; twin rotor multiple input multiple output system; vertical 1-degree of freedom systems; Biological cells; Force; Genetic algorithms; Rotors; Sociology; Statistics; Transmission line measurements; Twin rotor multiple input multiple output system (TRMS); proportionalintegral derivative (PID) control scheme; real valued genetic algorithm (RGA);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power, Energy and Control (ICPEC), 2013 International Conference on
Conference_Location :
Sri Rangalatchum Dindigul
Print_ISBN :
978-1-4673-6027-2
Type :
conf
DOI :
10.1109/ICPEC.2013.6527697
Filename :
6527697
Link To Document :
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