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      저자 : Hamed Tirandaz (검색결과 2 건)
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      • KCI등재

        Estimation of load torque in induction motors via dynamic sliding mode control and new nonlinear state observer

        Ali Karami-Mollaee,Hamed Tirandaz 대한기계학회 2018 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.32 No.5

        This study conducts load torque estimation in an induction motor (IM) with uncertainty using a dynamic sliding mode controller (DSMC) that suppresses chattering using an integrator or a low-pass filter placed before the control signal of the system. Hence, the dimension of the augmented system in DSMC is larger than the dimension of the original system, thus leading to an increase in the number of system states. These new state variables should be determined to control such a system. To address this problem, a new nonlinear state observer (NSO) is suggested and utilized in this study. The proposed method is independent of the uncertainty bound of the system, but the system output must be accessible. These subjects are important in practical implementations. Lyapunov theory is applied to validate the stability of the proposed DSMC and NSO methods. Then, the boundedness of the closed-loop signals is concluded from the stability of the proposed techniques. The validity of the proposed approach is evaluated using an IM model. By using DSMC and NSO, we can simultaneously control the IM and estimate its load torque. In particular, the external bounded load torque signal is compensated by the input control signal of the motor. Simulation results illustrate the advantages of the proposed approach.

      • KCI등재

        Adaptive Fuzzy Fault Tolerant Control Using Dynamic Sliding Mode

        Ali Karami-Mollaee,Hamed Tirandaz 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.1

        In this paper, an actuator fault tolerant control (FTC) has been designed using dynamic sliding mode control (DSMC) for single input nonlinear systems which are affected from uncertainty. In DSMC the switching of input control signal is removed due to the integrator which is placed before the input control signal of the plant hence, its result is reducing of chattering. However, in DSMC the augmented system (the system plus the integrator) is one dimension bigger than the actual system and then, the plant model should be completely known. To overcome on this problem, an adaptive fuzzy observer (AFO) has been proposed. Finally, we show the combination result of DSMC and AFO is the compensation of the fault by input control signal of the plant, while the performance and robustness of the closed loop system are reserved. The main property of the proposed approach is its simplicity and we only use system output for FTC and moreover, the fault diagnosis (detection, isolation and reconstruction) is done at the same time. The upper bound of the uncertainty is not used in DSMC and AFO, which is important in practical implementation. Simulation results show the advantages of the proposed approach.

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