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The controller sensorless feature is achieved using an adaptive observer providing the controller with online estimates of the mechanical variables.
Thus, assuming that only the frame positions (namely, (z_{1}) and (z_{2})) are measurable, it becomes necessary to recover all the unavailable variables and parameters using an adaptive observer.
In this paper, we propose to estimate a parameter which is shown to be characteristic of this component's health by using an Adaptive Observer or an Extended Kalman Filter.
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Consequently, in order to estimate both z and θ, we propose to use an adaptive observer whose estimation state error does vanish asymptotically.
The unavailable rotor flux is recovered by using an adaptive sliding rotor-flux observer provided with an adaptive mechanism of rotor resistance.
The effects of the fault and saturation are combined as a composite actuator fault, which is estimated together with the system state using an adaptive two-step sliding mode observer.
The approach is based on estimation of the pitch system states and fault indicator function using an adaptive step-by-step sliding mode observer, effectively handling the nonlinear fault distribution function with a simple design.
Spots were quantified using an adaptive method.
More specifically, the involved parameters and time-delay are jointly estimated using a suitable adaptive observer.
Starting from a simple synchronization method, a renormalization technique enables us to design an adaptive observer (slave) of the known Chua's circuit using simple and standard electronic components.
Using local recurrent neural network to approximate the unknown nonlinear functions, an adaptive observer is introduced for state estimation.
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