The exogenous inputs are assumed to be limited in both magnitude and rate of change.
The procedure proposed here associates an ANN with a Nonlinear AutoRegressive model with eXogenous inputs (NARX).
This paper presents a design method for matched systems that are subject to persistent exogenous inputs.
The SVR nonlinear autoregressive model with exogenous inputs (NARX) was developed and tested using experimental data collected during fourteen years.
Here, we review behavioral and neural evidence that feedback inputs are important for the formation of signals that could guide attentional selection based on exogenous inputs.
This paper presents a non-linear moving average model with exogenous inputs (NMAX) and a non-linear auto-regressive moving average model with exogenous inputs (NARMAX) respectively to model static and dynamic hysteresis inherent in piezoelectric actuators.
The problem of output regulation for MIMO systems with harmonic exogenous inputs and parameter uncertainties is addressed.
Another constraint is the need to remodel the plant equations to get appropriate exogenous inputs and outputs.
This paper considers a linear matrix inequality approach to the design of critical control systems for rate-limited exogenous inputs.
Autoregressive model with exogenous inputs (ARX) is a widely-used black-box type model underlying adaptive predictors and controllers.
We address the robust stabilization of nonlinear systems subject to exogenous inputs using event-triggered output feedback laws.
