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Process data exhibits both nonlinear and dynamic characteristics. A multivariable nonlinear dynamic modeling method is proposed by combining dynamic partial least squares (DPLS) algorithm and Hammerstein model. This method applies Hammerstein model to the DPLS inner regression. The outer PLS algorithm with ARX inputs is used to model the dynamics of the process, and it is also used to reduce the dimensionality...
We consider the averaging method for stability of rapidly switching nonlinear and linear systems with disturbances. First, we show that the input-to-state stability (ISS) analysis results for continuous-time systems in apply directly to nonlinear rapidly switched systems that we consider. We show that the notions of strong and weak averages that were proposed in play an important role in the context...
The paper studies semi-global practical input-to-state stability (SGP-ISS) of a parameterized family of discrete-time systems that may arise when an approximate discrete-time model of a sampled-data system with disturbances is used for controller design. It is shown under appropriate conditions that if the solutions of the time varying family of discrete-time systems with disturbances converge uniformly...
In this paper, the results of stabilizing a large scale nonlinear systems with uncertain dynamic interactions and unmodelled dynamics depending on both subsystem inputs and outputs in [9] and [10] are extended to highly nonlinear systems. Certain modifications on standard adaptive backstepping controllers are proposed to compensate for the effects of interactions from other subsystems in designing...
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