An Adaptive H(o) Controller Design for Bank-To-Turn Missiles Using Ridge Gaussian Neural Networks  

Oleh:

Lin, Chuan-Kai ; Wang, Sheng-De

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 15 no. 6 (Nov. 2004), page 1507-1516.
Topik: gaussian; adaptive; H(o); controller design; bank; ridge; gaussian neural networks

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.11 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

A new autopilot design for bank - to - turn (BTT) missiles is presented. In the design of autopilot, a ridge Gaussian neural network with local learning capability and fewer tuning parameters than Gaussian neural networks is proposed to model the controlled nonlinear systems. We prove that the proposed ridge Gaussian neural network, which can be a universal approximator, equals the expansions of rotated and scaled Gaussian functions. Although ridge Gaussian neural networks can approximate the non linear and complex systems accurately, the small approximation errors may affect the tracking performance significantly. Therefore, by employing the H 8 control theory, it is easy to attenuate the effects of the approximation errors of the ridge Gaussian neural networks to a prescribed level. Computer simulation results confirm the effectiveness of the proposed ridge Gaussian neural networks - based autopilot with H 8 stabilization.

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