TY - GEN
T1 - Adaptive output feedback control of uncertain multi-input multi-output systems using single hidden layer neural networks
AU - Hovakimyan, Naira
AU - Calise, Anthony J.
PY - 2002
Y1 - 2002
N2 - We consider adaptive output feedback control of uncertain multi-input multi-output nonlinear systems, in which both the dynamics and the dimension of the regulated plant may be unknown, but knowledge of vector relative degree is required. Given smooth reference trajectories, the problem is to design controllers that force the system measurements to track them with bounded errors. We propose a linear observer for the output tracking error vector and a Single Hidden Layer (SHL) Neural Network (NN) to cancel the modelling errors. Ultimate boundedness of the error signals is shown through Lyapunov's direct method. Simulations of a fourth order two-input two-output nonlinear system illustrate the theoretical results.
AB - We consider adaptive output feedback control of uncertain multi-input multi-output nonlinear systems, in which both the dynamics and the dimension of the regulated plant may be unknown, but knowledge of vector relative degree is required. Given smooth reference trajectories, the problem is to design controllers that force the system measurements to track them with bounded errors. We propose a linear observer for the output tracking error vector and a Single Hidden Layer (SHL) Neural Network (NN) to cancel the modelling errors. Ultimate boundedness of the error signals is shown through Lyapunov's direct method. Simulations of a fourth order two-input two-output nonlinear system illustrate the theoretical results.
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U2 - 10.1109/ACC.2002.1023243
DO - 10.1109/ACC.2002.1023243
M3 - Conference contribution
AN - SCOPUS:0036061227
SN - 0780372980
T3 - Proceedings of the American Control Conference
SP - 1555
EP - 1560
BT - Proceedings of the American Control Conference
T2 - 2002 American Control Conference
Y2 - 8 May 2002 through 10 May 2002
ER -