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In this paper, a systematic output-sliding control design methodology for nonlinear multivariable systems is presented.
A broadly-applicable, control-relevant system identification methodology for nonlinear restricted complexity models (RCMs) is presented.
This paper proposes a passive fuzzy controller design methodology for nonlinear system with multiplicative noises.
The proposed architecture exploits a distributed Fault Detection and Isolation (FDI) methodology for nonlinear LSS in a PnP framework.
This paper presents a continuous-time distributed fault detection and isolation methodology for nonlinear uncertain possibly large-scale dynamical systems.
A robust PID controller design methodology for nonlinear processes is proposed based on the just-in-time learning (JITL) technique.
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The application of the very efficient adjoint sensitivity analysis methodology (ASAM) for nonlinear systems is also illustrated by computing exactly the first-order sensitivities of selected facility responses to all model parameters.
The results could potentially provide an intriguing design methodology for developing nonlinear MEMS devices for broadband random energy harvesting.
The identification methodology for a nonlinear system with discrete state space variables based on combining fuzzy clustering and principal component analysis is proposed.
Thus, it is essential to propose a methodology for analyzing nonlinear dynamic properties of the pipeline with combined parametric and vortex excitations.
In the present paper a semi-analytical methodology for a nonlinear stress strain analysis of buried steel pipelines at active fault crossings is presented and verified.
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