Robust Quasi-LPV Control Based on Neural State Space Models  

Oleh:

Bendtsen, J. D. ; Trangbaek, K.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 13 no. 2 (2002), page 355-368.
Topik: robust; robust - quasi; LPV control; neural state; space models

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.6 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

We derive a synthesis result for robust linear parameter varying (LPV) output feedback controllers for nonlinear systems modeled by neural state - space models. This result is achieved by writing the neural state - space model on a linear fractional transformation (LFT) form in a non conservative way, separating the system description into a linear part and a nonlinear part. Linear parameter - varying control synthesis methods are then applied to design a non linear control law for this system. Since the model is assumed to have been identified from input - output measurement data only, it must be expected that there is some uncertainty on the identified nonlinearities. The control law is therefore made robust to noise perturbations. After formulating the controller synthesis as a set of linear matrix inequalities (LMI s) with added constraints, some implementation issues are addressed and a simulation example is presented.

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