A single study has addressed actuator failure reconstruction for the One-sided Lipschitz (OSL) family of nonlinear systems. The predicted fault vector in that work does not provide any insight into the underlying prob...
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ISBN:
(纸本)9781665482622
A single study has addressed actuator failure reconstruction for the One-sided Lipschitz (OSL) family of nonlinear systems. The predicted fault vector in that work does not provide any insight into the underlying problematic physical characteristics of the system, which is a significant shortcoming. In this work, we offer a way for estimating the incorrect physical parameters of actuators using an adaptive observer strategy. To demonstrate the utility of the suggested method, a numerical example and simulation research are provided.
This paper deals with the Maximum Power Point Tracking (MPPT) for photovoltaic energy system. It includes photovoltaic array panel, DC/DC converter, and load. The operating point for photovoltaic energy system depends...
This paper deals with the Maximum Power Point Tracking (MPPT) for photovoltaic energy system. It includes photovoltaic array panel, DC/DC converter, and load. The operating point for photovoltaic energy system depends on climatic parameters and load. For each temperature and irradiation pair, there exists only one optimal operating point which corresponds to the maximum power transmitted to the load. The photovoltaic energy system is described by nonlinear equations. It is transformed into an augmented system which is described with a Takagi-Sugeno (T-S) fuzzy model. The proposed MPPT algorithm which permits transfering the maximum power from the panel to the load is based on Parallel Distributed Compensation method (PDC). The control parameters have been computed based on Linear Matrix Inequalities tools (LMI). The Lyapunov approach has been used to prove the stability of the system. Some reliable simulation results are provided to check the efficiency of the proposed algorithm.
Usually In the speed sensorless of the induction motor, the machine parameters (especially rotor resistance Rr) have a strong influence on the speed estimation. This paper presents simultaneous estimation of speed and...
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ISBN:
(纸本)9781467301435
Usually In the speed sensorless of the induction motor, the machine parameters (especially rotor resistance Rr) have a strong influence on the speed estimation. This paper presents simultaneous estimation of speed and rotor resistance in sensorless ISFOC induction Motor drive based on a Model Reference System (MRAS). The MRAS has been formed to estimate the rotor speed and the rotor resistance which are tuned to obtain high-performance ISFOC induction motor drive. The error between the reference and adjustable models, developed in stationary stator reference frame, is used to drive a suitable adaptation mechanism that generates the estimate wr and Rr from measured terminal voltages and currents. The proposed algorithm has been tested by numerical simulation, showing the capability of driving active load and stability is preserved. Experimental results for the simultaneous estimation are presented in order to validate the effectiveness of the proposed scheme. The control algorithm has been implemented using a digital signal processor based on dSPACE DS1104.
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