• Journal of Power Electronics
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• v.7 no.1
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• pp.21-27
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• 2007

This paper investigates a PID fuzzy controller for output voltage regulation of a current-doubler-rectified asymmetric half-bridge (CDRAHB) DC/DC converter. The controller is a PD-type fuzzy controller in parallel with a linear integral controller. The PD type fuzzy controller is for providing the varying gain at the different operating conditions to regulate the output voltage. The linear integral controller is for removing the steady-state error of the output voltage. In order to show the outstanding dynamic characteristics of the proposed controller, PSIM simulation studies are carried out and compared to the results for which the conventional loop gain design method is used.

• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.231-242
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• 2023

A novel combinatorial type-2 adaptive neuro-fuzzy inference system (T2-ANFIS) and robust proportional integral derivative (PID) control framework for intelligent vibration mitigation of uncertain structural system is introduced. The fuzzy logic controllers (FLCs), are designed independently of the mathematical model of the system. The type-1 FLCs, have a limited ability to reduce the effect of uncertainty, due to their fuzzy sets with a crisp degree of membership. In real applications, the consequent part of the fuzzy rules is uncertain. The type-2 FLCs, are robust to the fuzzy rules and the process parameters due to the fuzzy degree of membership functions and footprint of uncertainty (FOU). The adaptivity of the proposed method is provided with the optimum tuning of the parameters using the neural network training algorithms. In our approach, the PID control force is obtained using the generalized type-2 neuro-fuzzy in such a way that the stability and robustness of the controller are guaranteed. The robust performance and stability of the presented framework are demonstrated in a numerical study for an eleven-story seismically-excited building structure combined with an active tuned mass damper (ATMD). The results indicate that the introduced type-2 neuro-fuzzy PID control scheme is effective to attenuate plant states in the presence of the structured and unstructured uncertainties, compared to the conventional, type-1 FLC, type-2 FLC, and type-1 neuro-fuzzy PID controllers.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.101.4-101
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• 2002

I. Introduction ▶The PID(Proportional-Integral-Derivative) controller is widely used in the industry it can be implemented easily for a typical second order plant. ▶The parameters of PID controller should be adapted complicatedly if a plant is various or the load is present. ▶For solving the problem, many control techniques have been developed. ▶A major method is a hybrid Fuzzy-PID controller. But, in case of using this method, we can not obtain characteristic of rapidly response and not achieved compensation on disturbance. ▶Therefore, we will use compensator fuzzy controller a front Hybrid type fuzzy-PID controller...

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2010.10a
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• pp.42-43
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• 2010

In this paper, automatic control system for the Manta UUV are constructed for the diving and steering maneuver. PID controller and Fuzzy controller are adopted in this system. Based on the 6DOF dynamic equation, simulation program has been developed using the Matlab. Using this program, depth control system and heading control system with tidal current are evaluated.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.681-686
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• 1991

In this paper, a novel self-organizing fuzzy plus PID control algorithm is proposed and analyzed by extensive computer simulations and experiments with an inverted pendulum. Specifically, the proposed self-organizing fuzzy controller consists of a typical fuzzy reasoning part and self organizing part in which both on-line and off-line algorithms are employed to modify the 'then' part of the fuzzy rules and to decide how much fuzzy rules are to be modified after evaluating the control performance, respecfively. And the fuzzy controller is replaced by a PID controller in a prespecified region near by the set point for good settling actions.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.279-284
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• 2014

This paper proposes a optimum design method for the Fuzzy PID controller of magnetic levitation-based Rail-Guided Vehicle(RGV). Since an attraction type levitation system is intrinsically unstable, it is difficult to completely satisfy the desired performance through the methods designed by conventional controllers. In the paper, the Fuzzy PID controller with fixed parameters are applied and then the optimum parameters of fuzzy PID controller are selected by genetic algorithm. For the fitness function of genetic algorithm, the performance index of PID controller is used. To verify the performance of the proposed method, we used Matlab/simulink model of Maglev and compared the proposed method with the performance of PID controller. The simulation results show that the proposed method is more effective than conventional PID controller.

• Journal of Navigation and Port Research
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• v.35 no.5
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• pp.359-363
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• 2011

In this paper, automatic control system for the Manta UUV are constructed for the diving and steering maneuver. PID controller and Fuzzy controller are adopted in this system. Based on the 6DOF dynamic equation, simulation program has been developed using the Matlab. Using this program, depth control system and heading control system with tidal current are evaluated.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.650-652
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• 2000

Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance. FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and increase efficiency, a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy Pi and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and them. The resultant rule base is Macvicar-Whelan type. The frequency response information is used in tuning of membership functions. Also a tuning strategy for the scaling factors is Proposed based on the relationship between PID gain and them. Simulation results show better performance and the effectiveness of the proposed method.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.3 no.2
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• pp.5-10
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• 2004

In this paper, the hybrid-type current controller for inverter TIG systems was implemented and it was shown that the low-current pulse wave forms with high dynamic performance could be obtained. It is not sri easy to obtain the optimum gain tuning of PID controllers in digital PWM control methods. Hybrid control methods which uses automatic tuning techniques after adding fuzzy control methods to traditional PID controllers are chosen to improve the dynamic performance of PID controller's. To demonstrate the practical significance and dynamic performance improvement of the results, some simulation and experimental results are presented.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.451-459
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• 2018

This work presents an approach for modeling of electric vehicle considering the vehicle dynamics, drive train, rotational wheel and load dynamics. The system is composed of IPMSM (Interior Permanent Magnet Synchronous Motor) coupled with the wheels through a drive train. Generally, IPMSM is controlled by ordinary PID controllers. Performance of the ordinary PID controller is not satisfactory owing to the difficulties of optimal gain selections. To overcome this problem, a new type of fuzzy logic gain tuner for PID controllers of IPMSM is required. Therefore, in this paper fuzzy logic based gain tuning method for PID controller is proposed and compared with some previous control techniques for the better performance of electric vehicle with an optimal balance of acceleration, speed, travelling range, improved controller quality and response. The model was developed in MATLAB/Simulink, simulations were carried out and results were observed. The simulation results have proved that the proposed control system works well to remove the transient oscillations and assure better system response in all conditions.