@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 system’s actual output response is capable of tracking the given 
reference signal in real time.},
DOI = {10.31209/2018.100000037}
}