• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.138-138
• /
• 2000

In this paper, a methodology for designing a controller based on inverse dynamics for speed control of DC motors is presented. The proposed controller consists of a prefilter, the inverse dynamic model of a system and a fuzzy logic controller. The prefilter prevents high frequency effects from the inverse dynamic model. The model of the system is characterized by a nonlinear equation with coulomb friction. The fuzzy logic controller regulates the error between the set-point and the system output which may be caused by disturbances and it simultaneously traces the change o( the reference input. The parameters of the model are estimated by a genetic a]gorithm. An experimental work on a DC motor system is carried out to illustrate the performance of the proposed controller

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.173-174
• /
• 2007

In this paper, a new speed sensorless control based on an instantaneous reactive power and a fuzzy PI compensator are proposed for the interior permanent magnet synchronous motor (IPMSM) drives. The conventional fixed gain PI and PID controllers are very sensitive to step change of command speed, parameter variations and load disturbance. Also, to the estimated speeds are compensated by using an instantaneous reactive power in synchronously rotating reference frame. In a fuzzy compensator, the system control parameters are adjusted by a fuzzy rule based system, which is a logical model of the human behavior for process control. The effectiveness of algorithm is confirmed by the experiments.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.6
• /
• pp.1439-1450
• /
• 2013

This paper investigates a robust neuro-fuzzy control (NFC) method which can accurately follow the speed reference of an interior permanent magnet synchronous motor (IPMSM) in the existence of nonlinearities and system uncertainties. A neuro-fuzzy control term is proposed to estimate these nonlinear and uncertain factors, therefore, this difficulty is completely solved. To make the global stability analysis simple and systematic, the time derivative of the quadratic Lyapunov function is selected as the cost function to be minimized. Moreover, the design procedure of the online self-tuning algorithm is comparatively simplified to reduce a computational burden of the NFC. Next, a rotor angular acceleration is obtained through the disturbance observer. The proposed observer-based NFC strategy can achieve better control performance (i.e., less steady-state error, less sensitivity) than the feedback linearization control method even when there exist some uncertainties in the electrical and mechanical parameters. Finally, the validity of the proposed neuro-fuzzy speed controller is confirmed through simulation and experimental studies on a prototype IPMSM drive system with a TMS320F28335 DSP.

• Proceedings of the KIEE Conference
• /
• 2002.07d
• /
• pp.2255-2257
• /
• 2002

In this paper, Fuzzy-Observer is designed to control the speed of DC Servo Motor. Fuzzy-Observer estimates the speed of DC Servo Motor with the measurement of the amature current. The constant speed and variable speed experiments are excuted to evaluate the performance of Fuzzy-Observer.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.8 no.1
• /
• pp.46-52
• /
• 1994

In this paper, we implemented the variable speed controller of an induction motor by the Fuzzy control algorithms, which recently is invoking the remarkable interest. As the fuzzy controller is designed on the base of expert's knowlede and experience, it is difficult to expect the perfect control performance of fuzzy controller. Therefore, the adjustment techniques for optimization of scale factors were presented to design the robust fuzzy controller comparing with conventional PI control the usefullness of proposed fuzzy controller was showed by the experimental results.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.5 no.2
• /
• pp.3-12
• /
• 1995

A controller utilizing fuzzy logic is developed to control the speed of a motor in a washing machine by choosing an appropriate phase. Due to the hardship imposed on obtaining a result from a relation established for inputs, present speed and present rate of speed, and ouput, a phase, of the system that can be tested against an experimental result, it is impossible to apply a genetic algorithm to fine-tune the fuzzy logic controller. To avoid this difficulty, a proper assumption that the parameters of an if-part of a primary fuzzy logic controller have a functional relationship with an error between computed values and experimental ones in made. Setting up of a fuzzy relationship between the parameters and the errors is then achieved through experimentally obtained data. Genetic Algorithm is then applied to this secondary fuzzy logic controller to verify the fuzzy logic. In the verification process, the primary fuzzy logic controller is used in obtaining experimental results. In this way the kind of difficulty in obtaining enough experimental values used to verify the fuzzy logic with genetic algorithm is gotten around. Selection of the parameters that would produce the least error when using the secondary fuzzy logic controller is done with applying genetic algorithm to the then-part of the controller. In doing so the optimal values for the parameters of the if-part of the primary fuzzy logic controller are assumed to be contained. The experimental result presented in the paper validates the assumption.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.3
• /
• pp.218-226
• /
• 2003

Due to the friction characteristics of pump, cylinder packing and passenger car, in the elevation system actuated with hydraulic inverter, there exist dead zones. which cannot be controlled by a PID controller. To overcome the drawbacks, in this paper, we propose a new hybrid fuzzy-sliding mode control scheme, which controls the controller output between a sliding mode control output and a PID control output by fuzzy control method. The proposed hybrid control scheme achieves an improved control performance by using both controllers. We first propose a design method of the hybrid controller far a hydraulic system controlled by inverters, then propose a design method of a hybrid fuzzy-sliding mode centre] scheme. The effectiveness of the proposed control scheme is shown by simulation results, in which the proposed hybrid control method yields better control performance then the PID controlled scheme, not only in the zero-crossing speed region but also in the overall control region including steady-state region.

• Proceedings of the KIPE Conference
• /
• 1998.07a
• /
• pp.230-233
• /
• 1998

The conventional PI controller are fragile in parameter variation and load-variation. Therefore, in this paper, a speed control algorithm based on the Fuzzy PI controller is proposed for the high performance speed control of a voltage-source inverter to drive 3-phase induction motors. The computer simulation results show that the proposed controller are more excellent control characteristics than conventional PI controller in transient-state and steady-state response.

• Proceedings of the KIEE Conference
• /
• 1998.07b
• /
• pp.541-543
• /
• 1998

Generally, PI control is simple and easy to implement and gains of PI control are determined by specifying a dynamics of the servo driver system. However, the gain-tuning is so difficult that it is relied on an expert's effort. This paper presents a gain auto-tuning method for PI controllers based on a fuzzy inference mechanism. First, the proposed fuzzy inference system identifies a system moment of inertia and adjusts control gains by using the difference in speed responses between a real plant and a reference model. Second, this paper proposes an improved fuzzy PI controller. To reduce the speed overshoot, we adapt a control method that selects a proper PI gains with respect to the load inertia variation. To prove the validity of the proposed gain tuning algorithm and the feasibility of the servo drive, a high performance servo drive will be implemented by DSP(TMS320C31) and intelligent power module (IPM). The proposed controller is applied to the speed control of the 300W AC servo motor. Some simulations and experimental results show that the proposed fuzzy PI controller is more robust than the conventional PI controller against the load inertia variation.

• Journal of Power Electronics
• /
• v.15 no.3
• /
• pp.730-740
• /
• 2015

This paper presents model reference adaptive system speed estimators based on Type-1 and Type-2 fuzzy logic controllers for the speed sensorless direct torque and flux control of an induction motor drive (IMD) using space vector pulse width modulation. A Type-1 fuzzy logic controller (T1FLC) based adaptation mechanism scheme is initially presented to achieve high performance sensorless drive in both transient as well as in steady-state conditions. However, the Type-1 fuzzy sets are certain and cannot work effectively when a higher degree of uncertainties occurs in the system, which can be caused by sudden changes in speed or different load disturbances and, process noise. Therefore, a new Type-2 FLC (T2FLC) - based adaptation mechanism scheme is proposed to better handle the higher degree of uncertainties, improve the performance, and is also robust to different load torque and sudden changes in speed conditions. The detailed performance of different adaptation mechanism schemes are performed in a MATLAB/Simulink environment with a speed sensor and sensorless modes of operation when an IMD is operates under different operating conditions, such as no-load, load, and sudden changes in speed. To validate the different control approaches, the system is also implemented on a real-time system, and adequate results are reported for its validation.