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This study aims to design an adaptive output recurrent cerebellar model articulation controller (AORCMAC), which is embedded into the direct torque control (DTC) system of an induction motor as the speed controller. Similar to the conventional cerebellar model articulation controller (CMAC), the designed AORCMAC also has the advantages of rapid learning, simple architecture, online training, and nonlinear...
This paper presents an adaptive sliding self-organizing fuzzy controller (ASSOFC) designed using fuzzy theory and a self-organizing algorithm. Composed of a conventional fuzzy controller (FC) and self-organizing algorithm, the ASSOFC adopts the sliding surface signal as an input, uses the algorithm to adjust the central position of the output consequent membership function of the FC, and, by fuzzy...
This study proposed an adaptive recurrent cerebellar model articulation controller (ARCMAC) which consisted of a recurrent Gaussian cerebellar model articulation controller (RCMAC) and a compensation controller. The ARCMAC was used as the speed controller for a switched reluctance motor (SRM), and the contained compensation controller was used to offset the error between the RCMAC and a theoretically...
In this study, the sliding mode controller (SMC) and the Takagi-Sugeno-Kang (TSK) fuzzy system were employed to design the proposed sliding mode controller with adaptive fuzzy compensation (AFSC). This design can improve the speed control performance of switched reluctance motor drive systems. Lyapunov function was derived to ensure the stability of the controller in the motor drive systems. To verify...
This study proposed a fuzzy excitation controller to reduce noise and torque ripples for switched reluctance motors. The design of the controller is simple and can generate appropriate turn-on and turn-off angles according to the speed of torque error in order to improve the torque response. At the motor speed of 300 rpm with one Nm load, the experimental results showed that the implantation of a...
Based on the Takagi-Sugeno-Kang (TSK) fuzzy controller and adaptive control theory, this study presents the design of an adaptive TSK fuzzy controller (ATSKFC). With an online learning function, this controller is an improvement on the traditional PI controller, whose parameters are fixed. An improved model for a compensating controller is also proposed to address the problems caused by the fixed...
In this paper, an adaptive TSK-fuzzy rotor resistance observer (ATFRO) is proposed and embedded into the induction motor vector control system. The proposed observer consists of adaptive rotor resistance observer, TSK-fuzzy control (TSKFC), and projection algorithm (PA). The estimated rotor resistance value enters into the adaptive pseudo-reduced-order flux observer (APRO) to decrease sensitivity...
Force regulation is a challenging task of forceps used for robot-assisted surgical manipulation. To avoid excessive force applied on soft tissues, sophisticated sensors with computerized precise control are often required. Without using additional electronic elements, this paper presents a passive mechanism to maintain a constant contact force between forceps jaw tips and tissues given a pre-specified...
Torque pulsations exist in ring permanent torque motors, which seriously degrade the drive performance of system at low speeds. In view of the periodic nature of torque ripple, adopt fuzzy iterative learning control (F-ILC) controller to minimize the torque ripple. It records the torque error and the compensating reference current of last cycle to update the compensating reference current of this...
The design and implementation of an adaptive neural network based proportional-integral controller (NNPIC) were carried out on the direct torque control (DTC) system. The proposed controller consists of neural network and projection algorithm, in order to tune its parameters adaptively online under environmental variations. The experimental results proved that the performance of the proposed controller...
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