Helicopter Trimming and Tracking Control Using Direct Neural Dynamic Programming  

Oleh:

Si, Jennie ; Enns, R.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 14 no. 4 (Jul. 2003), page 929-939.
Topik: neural network; programming; helicopter trimming; tracking control; direct neural; dynamic programming

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.8 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

This paper advances a neural - network - based approximate dynamic programming control mechanism that can be applied to complex control problems such as helicopter flight control design. Based on direct neural dynamic programming (DNDP), an approximate dynamic programming methodology, the control system is tailored to learn to maneuver a helicopter. The paper consists of a comprehensive treatise of this DNDP - based tracking control framework and extensive simulation studies for an Apache helicopter. A trim network is developed and seamlessly integrated into the neural dynamic programming (NDP) controller as part of a baseline structure for controlling complex nonlinear systems such as a helicopter. Design robustness is addressed by performing simulations under various disturbance conditions. All designs are tested using FLYRT, a sophisticated industrial scale non linear validated model of the Apache helicopter. This is probably the first time that an approximate dynamic programming methodology has been systematically applied to, and evaluated on, a complex, continuous state, multiple - input multiple - output non linear system with uncertainty. Though illustrated for helicopters, the DNDP control system framework should be applicable to general purpose tracking control.

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