@Article{2018.100000037,
AUTHOR = {Hong-Sen Yan, Jiao-Jun Zhang, Qi-Ming Sun},
TITLE = {MTN Optimal Control of SISO Nonlinear Time-varying Discrete-time Systems for Tracking by Output Feedback*},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {25},
YEAR = {2019},
NUMBER = {3},
PAGES = {487--507},
URL = {http://www.techscience.com/iasc/v25n3/39674},
ISSN = {2326-005X},
ABSTRACT = {MTN optimal control scheme of SISO nonlinear time-varying discrete-time
systems based on multi-dimensional Taylor network (MTN) is proposed to
achieve the real-time output tracking control for a given reference signal.
Firstly, an ideal output signal is selected and Pontryagin minimum principle
adopted to obtain the numerical solution of the optimal control law for the
system relative to the ideal output signal, with the corresponding optimal
output termed as desired output signal. Then, MTN optimal controller (MTNC) is
generated automatically to fit the optimal control law, and the conjugate
gradient (CG) method is employed to train the weight parameters of MTNC
offline to acquire the initial weight parameters of MTNC for online training that
guarantees the stability of closed-loop system. Finally, a four-term back
propagation (BP) algorithm with a second order momentum term and error
term is proposed to adjust the weight parameters of MTNC adaptively to
implement the output tracking control of the systems in real time; the
convergence conditions for the four-term BP algorithm are determined and
proved. Simulation results show that the proposed MTN optimal control scheme
is valid; the systemâ€™s actual output response is capable of tracking the given
reference signal in real time.},
DOI = {10.31209/2018.100000037}
}