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The reduced model can be used as basis for control design for process stabilization.
This paper presents a low complexity model aimed as the basis for control design.
However, the minimal order approach to prestabilisation is not always a good basis for control design.
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Backstepping technique combined with nonlinearly parameterized fuzzy approximators is employed to derive the controller, which removes the restriction that fuzzy basis functions must be well-known for control design.
A simple dynamic nonlinear model for the vehicle, valid for quasi-stationary flight conditions, is derived as a basis for the control design.
Feedback linearization is used as a basis for the control design.
The basis for the control design is a first-principles mathematical model of the air supply circuit and the combustion of flammable products.
Frequency response function (FRF) identification is often used as a basis for control systems design and as a starting point for subsequent parametric system identification.
In view of its accuracy, simplicity and fast computation speed, the developed nodal core model can serve as the basis for control system design and simulation of the AP1000 reactor.
The scheme is motivated by the well-known Crank-Nicolson discretization that was originally developed for second-order systems and it is used in this paper to develop a discrete in time and space model of a deformable mirror as a basis for control law design.
In the future, the mathematical model will be used as a basis for controller design and the physiological model for experimental control performance evaluation.
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