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The motivation for using this control strategy for training the RBFNN based controller is to take large modeling uncertainties into account, cover physical constraints on control action and minimize the effects of area load disturbances.
Optimal control strategies for constraints on control and state variables and for different parameters are presented.
We were able to detect design constraints on control systems that other methods fail to detect.
System uncertainties, practical constraints on control action and desired performance are included in the synthesis procedure.
Constraints on control inputs and system outputs are usually given in the non-symmetric form.
The constraints on control input and angular velocity are implemented by second-order command filter.
Similar(47)
Constraints on controls are imposed.
The presented methodology can handle very general formulations, including several objectives, arbitrary network topologies and non-linear kinetics, large numbers of control variables (enzymes or activation rates), and general path and point constraints on controls and states (metabolites concentrations).
System uncertainties according to load, practical constraint on control action and desired performance are included in the synthesis procedure.
It is assumed that the hydrodynamic parameters of the nonlinear vehicle model are imprecisely known, and in order to obtain a practical design, a hard constraint on control fin deflection is imposed.
It describes the control design criteria, taking also into consideration the constraints on the control and controlled variables, arising from the application of such control technique in a real scenario.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com