Title :
Intelligent hybrid Active Force Control in identification of a nonlinear MIMO system
Author :
Mohamed, T.L.T. ; Ishak, K.M.A.K. ; Ramli, Ham ; Meon, M.S.
Author_Institution :
Fac. of Mech. Eng., Univ. Teknol. MARA, Shah Alam, Malaysia
Abstract :
This paper presents Active Force Control (AFC) based scheme embedded with neural network and fuzzy logic in scheming the twin rotor multi-input multi-output (MIMO) system (TRMS). This architecture is proposed due to limitations of classic PID lead to difficulty in compensate the disturbances and internal changes appertain by angular momentum and reaction turning between two axes. The proposed architecture is employed in both pitch and yaw control scheme to optimize the responses. The results shown a very significant achievement as the proposed candidate give reasonably good performance and capable of compensating the internal and external disturbances. The integration of Neural Network and fuzzy logic is proven to be a potential hybrid as it provides an advanced optimization in accelerates the performance of TRMS.
Keywords :
MIMO communication; force control; fuzzy control; neurocontrollers; nonlinear control systems; optimisation; telecommunication control; three-term control; AFC; PID control; TRMS; angular momentum; disturbance compensation; fuzzy logic control; intelligent hybrid active force control; neural network; nonlinear MIMO identification system; optimization; pitch control scheme; reaction turning; twin rotor multiinput multioutput; yaw control scheme; Active Force Control; Multi-Input Multi-Output system; Twin Rotor; fuzzy logic; neural network;
Conference_Titel :
Research and Development (SCOReD), 2012 IEEE Student Conference on
Conference_Location :
Pulau Pinang
Print_ISBN :
978-1-4673-5158-4
DOI :
10.1109/SCOReD.2012.6518622