H ∞ Control Design Using Dynamic Neural Networks

Abstract

In this paper, a new approach is investigated for adaptive dynamic neural network-based H ∞ control, which is designed for a class of non-linear systems with unknown uncertainties. Currently, non-linear systems with unknown uncertainties are commonly used to efficiently and accurately express the real practical control process. Therefore, it is of critical importance but a great challenge and still at its early age to design a stable and robust controller for such a process. In the proposed research, dynamic neural networks were constructed to precisely approximate the non-linear system with unknown uncertainties first, a non-linear state feedback H ∞ control law was designed next, then an adaptive weighting adjustment mechanism for dynamic neural networks was developed to achieve H ∞ regulation performance, and last a recurrent neural network was employed as a neuro-solver to efficiently and numerically solve the standard LMI problem so as to obtain the appropriate control gains. Finally, case studies further verify the feasibility and efficiency of the proposed research.

Exact Takagi-Sugeno descriptor models of recurrent high-order neural networks for control applications

“…In this work, a properly trained RHONN intended to identify the model of such nonlinear plant is transformed into a nonlinear generalization of the descriptor form in Luenberger (1977) Fig. 2), based on which a possibly nonlinear output of interest y(t) = C(x)x(t) will be controlled via H ∞ -optimal control with respect to the bias term g(x) (Shen and Shen 2008)…”

Espectroscopia óptica em super-redes de GaAs com dopagem delta de Si

“…Também Shen et a/ 16 reportaram tempos de decaimento de 1.4 ms para amostras SIN-GaAs. A diferença nos tempos pode ser devida à interação com estados de superfície lentos, presentes em amostras oxidadas 71 Além disso, nos trabalhos mencionados a obtenção do tempo de decaimento é indireta, e a faixa de medida não permitia medir tempos maiores que 2 ms. obtidas usando os tempos de resposta determinados por PR resolvida no tempo ( eq. 5.…”