Robust Adaptive Control of Nonaffine Nonlinear Plants With Small Input Signal Changes  

Oleh:

Keel, L. H. ; Sathananthan, S. ; Adetona, O.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 15 no. 2 (Mar. 2004), page 408-416.
Topik: robust; robust adaptive; control; non affine; non linear; small input signal changes

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.10 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

Lihat Detail Induk

Isi artikel

Assuming small input signal magnitudes, ARMA models can approximate the NARMA model of non affine plants. Recently, NARMA - L1 and NARMA - L2 approximate models were introduced to relax such input magnitude restrictions. However, some applications require larger input signals than allowed by ARMA, NARMA - L1 and NARMA - L2 models. Under certain assumptions, we recently developed an affine approximate model that eliminates the small input magnitude restriction and replaces it with a requirement of small input changes. Such a model complements existing models. Using this model, we present an adaptive controller for discrete non affine plants with unknown system equations, accessible input - output signals, but inaccessible states. Our approximate model is realized by a neural network that learns the unknown input - output map online. A deadzone is used to make the weight update algorithm robust against modeling errors. A control law is developed for asymptotic tracking of slowly varying reference trajectories.

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