This paper focuses on the synthesis of adaptive fuzzy fault tolerant controller which combines a sliding mode controller and a Proportional Integral controller (PI). The free parameters of the adaptive fuzzy controlle...
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This paper focuses on the synthesis of adaptive fuzzy fault tolerant controller which combines a sliding mode controller and a Proportional Integral controller (PI). The free parameters of the adaptive fuzzy controller as well as the PI controller are tuned on-line based on Lyapunov approach. The overall adaptive fuzzy sliding mode scheme guarantees the global stability of the resulting closed-loop system as well as the convergence of the reference tracking error vector. The proposed method is applied to a robot manipulator of two degrees of freedom system and achieves satisfactory simulation results.
This paper deals with the parameter estimation and the self-tuning regulation of a solar system, which is composed of a solar cell followed by a boost converter. The considered system is described by an input-output s...
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This paper deals with the parameter estimation and the self-tuning regulation of a solar system, which is composed of a solar cell followed by a boost converter. The considered system is described by an input-output stochastic mathematical model at discrete-time, with unknown but constant or slowly time-varying parameters. This parameter estimation is conducted based on the method of prediction error and least squares techniques. The posed regulation problem consists in the development of a self-tuning regulator on the basis of the generalized minimum-variance approach. Thus, a generalized minimum-variance self-tuning regulator is developed. A numerical simulation of the self-tuning regulation of the considered stochastic system is treated.
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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