Adaptive Neural Control of Uncertain MIMO Nonlinear Systems  

Oleh:

Wang, Cong ; Ge, S. S.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 15 no. 3 (May 2004), page 674-692.
Topik: neural network; adaptive; neural control; MIMO non linear systems

Ketersediaan

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

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Isi artikel

In this paper, adaptive neural control schemes are proposed for two classes of uncertain multi - input / multi - output (MIMO) non linear systems in block - triangular forms. The MIMO systems consist of interconnected subsystems, with couplings in the forms of unknown nonlinearities and / or parametric uncertainties in the input matrices, as well as in the system interconnections without any bounding restrictions. Using the block - triangular structure properties, the stability analyses of the closed - loop MIMO systems are shown in a nested iterative manner for all the states. By exploiting the special properties of the affine terms of the two classes of MIMO systems, the developed neural control schemes avoid the controller singularity problem completely without using projection algorithms. Semiglobal uniform ultimate boundedness (SGUUB) of all the signals in the closed - loop of MIMO non linear systems is achieved. The outputs of the systems are proven to converge to a small neighborhood of the desired trajectories. The control performance of the closed - loop system is guaranteed by suitably choosing the design parameters. The proposed schemes offer systematic design procedures for the control of the two classes of uncertain MIMO non linear systems. Simulation results are presented to show the effectiveness of the approach.

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