Sentence examples for systems to approximate from inspiring English sources

We use a sequence of periodically forced systems to approximate the considered system, and find their periodic solutions.

Using fuzzy logic systems to approximate unknown nonlinear functions, a fuzzy state observer is designed for estimating the unmeasured states.

With the time-delay functions unavailable, we employ adaptive RBF neural network systems to approximate unknown functions.

To study the existence of homoclinic solutions to Equation (4), we still use a sequence of periodic forced systems to approximate Equation (4), and find their periodic solutions.

Main idea of the control scheme is employing the fuzzy systems to approximate the unknown nonlinear functions and adopting the PI control to eliminate the input chattering.

With the help of fuzzy logic systems to approximate the unknown nonlinear functions, and a fuzzy state observer is designed to estimate the unmeasured states.

We propose a fuzzy stochastic partial differential system to approximate the NSPDSs based on fuzzy interpolation approach.

By employing T-S fuzzy system to approximate nonlinear uncertainties of the control system, the proposed scheme is developed by combining "dynamic surface control" (DSC) and "minimal learning parameter" (MLP) techniques.

The proposed approach uses a fuzzy system to approximate the unknown substrate consumption rate in designing the adaptive controller, and then an observer is designed to estimate the concentration in substrate at the outlet bioreactor.

The proposed approach employs a fuzzy system to approximate the unknown nonlinear functions in designing the adaptive controller and an observer is designed to generate an error signal for the adaptive law.

System (3.1) is a classic nonlinear model and the nonlinear model is more troublesome dealing with many problems, so we use the linear system to approximate the nonlinear system according to the characteristics of T-S fuzzy control, so that the problem of the nonlinear system is transformed into the problem of a linear system.