Title :
Tuning of RLS-active vibration controller using genetic algorithm
Author :
Salleh, S. Md ; Tokhi, M.O.
Author_Institution :
Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, Sheffield, UK
Abstract :
This paper presents a recursive least-squares (RLS)-model based active vibration control (AVC) system with genetic algorithm (GA) self tuning. Tuning parameters include initial regression vectors, gain of RLS-model and gain of controller. The system employs a single-input single-output (SISO) control configuration, and is realised within the Matlab/Simulink environment. In the paper, the parameters of RLS-AVC system are tuned so as to achieve effective vibration suppression. The approach is tested with pseudo random binary sequence (PRBS) disturbance signal acting on a plate to access the effectiveness of the approach in reducing the vibration of the plate.
Keywords :
adaptive control; genetic algorithms; least squares approximations; recursive estimation; regression analysis; self-adjusting systems; vibration control; Matlab-Simulink environment; genetic algorithm; initial regression vectors; pseudorandom binary sequence disturbance signal; recursive least-squares model based active vibration control system; self tuning; single-input single-output control configuration; vibration suppression; Automatic voltage control; Genetic algorithms; Mathematical model; Transfer functions; Tuning; Vibration control; Vibrations; GA tuned; RLS-active vibration control; flexible plate;
Conference_Titel :
Cybernetic Intelligent Systems (CIS), 2010 IEEE 9th International Conference on
Conference_Location :
Reading
Print_ISBN :
978-1-4244-9023-3
Electronic_ISBN :
978-1-4244-9024-0
DOI :
10.1109/UKRICIS.2010.5898115
