Identification and adaptive multi‐dimensional Taylor network control of single‐input single‐output non‐linear uncertain time‐varying systems with noise disturbances

Adaptive tracking control for a class of stochastic non‐linear systems with input saturation constraint using multi‐dimensional Taylor network

“…Among them, MTN‐based control approach shows great appliance foreground in the control problems of non‐linear systems, and many interesting results have been reported. For example, this method has been applied to single‐input single‐output (SISO) non‐linear system [22, 24], SISO time‐varying systems [25], MIMO non‐linear discrete systems [26], SISO stochastic non‐linear systems [27–29] and MIMO stochastic non‐linear systems [30, 31]. However, despite these advancements, few results on adaptive control of stochastic non‐linear systems with input constraints have been reported to date.…”

Predictor‐based adaptive feedback control for a class of systems with time delay and its application to an aircraft skin inspection robot

“…In [18], the authors use the radial basis function (RBF) NNs as an approximator to cope with the design difficulties caused by the non-lower-triangular structure. In [19], a multi-dimensional Taylor network is utilised to eliminate the control interference and measurement noise.…”

“…• Note that the previously existing in [18,19,21] all solved the problem of adaptive NNs control design without time delays. The difference is that, in this paper, a predictor is designed to overcome the known input time delay.…”

Multidimensional Taylor network adaptive control for MIMO time‐varying uncertain nonlinear systems with noises

“…The idea of multidimensional Taylor network (MTN) optimal control was then proposed by Yan in 2010 . This model is commonly applied for model prediction, system identification, disaster prediction, motor control, and nonlinear control . However, Yan and Kang provided only a basic idea of the MTN controller (MTNC).…”

“…13,14 This model is commonly applied for model prediction, 15 system identification, 16,17 disaster prediction, 18 motor control, 19 and nonlinear control. [20][21][22][23][24][25] However, Yan and Kang 20 provided only a basic idea of the MTN controller (MTNC). Many problems, such as the overall consideration of the uncertainty, time-varying characteristics, and measurement noise, have not been investigated.…”