DocumentCode
2327472
Title
Augmented feedforward and feedback control of a twin rotor system using real-coded MOGA
Author
Toha, S.F. ; Tokhi, M.O.
Author_Institution
Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, Sheffield, UK
fYear
2010
fDate
18-23 July 2010
Firstpage
1
Lastpage
7
Abstract
Vibration suppression is crucial for applications in engineering particularly for aircraft systems. A hybrid control approach comprising a feedforward intelligent command shaping technique inverse-model based PID feedback control is presented in this paper. The proposed augmented control scheme is used to control both the flexible motion and rigid body dynamics of a twin rotor multi-input multi-optput system (TRMS). The advantage of using command shaping is to reduce system vibration. However, it can cause delay in system. Furthermore, performance requirements based on tracking error, rise time, settling time, percentage overshoot and steady state error are often found to be conflicting with one another in most flexible systems. Therefore real-coded multi objective genetic algorithm is employed in this work to compromise the problems and determine a set of solutions for the amplitudes and corresponding time locations of impulses on an extra sensitive (EI), four-impulse sequence command shaper as well as gain parameters for the PID controller. The effectiveness of the proposed technique is assessed both in the time domain and the frequency domain. Moreover, a comparative assessment of the performance of the technique with the system response and unshaped finite step input is presented.
Keywords
MIMO systems; aircraft control; feedback; feedforward; genetic algorithms; motion control; rotors; three-term control; vehicle dynamics; vibration control; PID control; aircraft systems; feedback control; feedforward control; feedforward intelligent command shaping technique inverse model; flexible motion dynamics; multiinput multioutput system; real-coded multiobjective genetic algorithm; rigid body dynamics; sequence command shaper; twin rotor system; vibration suppression; Biological cells; Feedforward neural networks; Optimization; Rotors; Steady-state; Transmission line measurements; Vibrations; Vibration suppression; multi objective genetic algorithm; twin rotor system;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location
Barcelona
Print_ISBN
978-1-4244-6909-3
Type
conf
DOI
10.1109/CEC.2010.5586130
Filename
5586130
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