• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.1
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• pp.1-8
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• 2008

A two-wheel balancing vehicle, which helps people moving freely and fast, and is applied from inverted pendulum system, has been widely researched and developed, and some products are came into a market in actuality. Until now, the two-wheel balancing vehicles developed have chosen the general PID control method. In this paper, we propose a new control method to improve a control capacity for a two-wheeled balancing vehicle for human transportation. The proposed method is the fuzzy PD+I control that is one of the improved PID control, and it contains a 2input-1output fuzzy system. This fuzzy system processes signals from proportional and derivative controller, and the fuzzy output signal generates the final output by summing up integral signal. The non-linearity of the fuzzy system makes an optimal output control signal by changing weight of the proportional signal and the derivative signal in process of time. We have simulated the fuzzy PD+I control system and experimented by implementing the two-wheel balancing mobile robot to verify the advantages of the proposed fuzzy PD+I control method in comparison with general PID control. As the results of simulation and experimentation, the proposed fuzzy PD+I control method has better control performance than general PID in this system and improves it.

• 연구논문집
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• s.23
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• pp.73-80
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• 1993

This study presents an intelligent PID control method based on the fuzzy logic and this method is applied to the active magnetic bearing system. By using an appropriate fuzzy matrix, some changes of values of the three coefficients of the controller are determined during system operation and these lead to the improvement of the transient and steady state behavior of the closed loop system. The presented method is actually a combination of the principles of PID control and fuzzy logic. Since the fuzzy logic using linguistic variables in place of numeric variables has many points of likeness to the human logic, the improvement in performance is notable especially in case of large nonlinearity and uncertainty such as the controller start and the excessive mass unbalance. A set of simulation and experimental results illustrate and considerable improvement in the control performance including small overshoot and small transient currents in magnet coils, while maintaining the overal static and dynamic characteristics near the equilibrium position.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2161-2163
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• 2002

The PID type controller has been widely used in industrial application doc to its simply control structure, ease of design and inexpensive cost. However control performance of the PID type controller suffers greatly from high uncertainty and nonlinearity of the system, large disturbances and so on. This paper presents a hybrid fuzzy logic proportional plus conventional integral derivative controller (Fuzzy P+ID). In comparison with a conventional PID controller, only one additional parameter has to be adjusted to tune the Fuzzy P+ID controller. In this case, the stability of a system remains unchanged after the PID controller is replaced by the Fuzzy P+ID controller without modifying the original controller parameters. Finally, the proposed hybrid Fuazy P+ID controller is applied to BLDC motor drive. Simulation results demonstrated that the control performance of the proposed controlled is better than that of the conventional controller.

• Journal of Convergence Society for SMB
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• v.4 no.1
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• pp.31-39
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• 2014

PID auto-tuning controller was designed via fuzzy logic. Typical values such as error and error derivative feedback were changed as heuristic expressions, and they determine PID gain through fuzzy logic and defuzzification process. Fuzzy procedure and PID controller design were considered separately, and they are combined and analyzed. Obtained auto-tuning PID controller by Fuzzy Logic showed the ability for less than 3rd order plant control. We also applied to reference tracking problem with the designed auto-tuning scheme.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.352-354
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• 2004

In this paper, a parallel fuzzy controller for one degree of freedom magnetic levitation is designed and its performance is compared with the performance of a PID controller. Input, output scaling factor of fuzzy controller and gain of PID controller were tuned using the GA algorithm. The designed controllers are validated by numerical simulations. So it's shown that parallel fuzzy controller can give the better performance for the plant than PID controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.26-34
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• 2015

In this paper, a fuzzy compensated PID control system is proposed for formation control of mobile robots. The control system consists of a kinematic controller based on the leader-follower approach and a dynamic controller to handle dynamics effects of mobile robots. To maintain the desired formation of mobile robots, the dynamic controller is equipped with a PID controller; however, the PID controller has poor performance in nonlinear and changing environments. In order to improve these problem, we applied the additional fuzzy compensator. Finally, the proposed control system has been evaluated through computer simulation to demonstrate the improved results.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.184-187
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• 1996

In this paper, an algorithm for tuning gains of a PID controller is proposed. The proposed algorithm is composed of two stages. The first is a stage for Lyapunov function-based initial stabilization of an overall system and rough tuning gains of the PID controller. The other is that for fine tuning gains of the PID controller. All tunings are performed by using the well-known fuzzy logic-based tuner. The computer simulations are performed to show the validity of the proposed algorithm and results are presented.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.257-262
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• 1994

This paper describes an autotuning fuzzy PID controller for a position control of DC serve motor. Because ZNM(Ziegler-Nichols Method) with relay feedback has the difficulty in re-tuning the PID parameters and adaptive method has complex algorithm, a new method to overcome those problems is required. The proposed scheme determines the initial PID gains by using ZNM with relay feedback, and then re-tunes the optimal PID parameters by using fuzzy expert system whenever control conditions are changed. To show the validity of the proposed method, a position control of DC servo motor is illustrated by computer simulation and is experimented by a designed controller.

• Ocean Systems Engineering
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• v.3 no.3
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• pp.237-255
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• 2013

In many applications, Remotely Operated Vehicles (ROVs) are required to be capable of course keeping, depth keeping, and height keeping. The ROV must be able to resist time-variant external forces and moments or frequent manipulate changes in some specified circumstances, which require the control system meets high precision, fast response, and good robustness. This study introduces a Fuzzy-Incomplete Derivative Ahead-PID (FIDA-PID) control system for a 500-meter ROV with four degrees of freedom (DOFs) to achieve course, depth, and height keeping. In the FIDA-PID control system, a Fuzzy Gain Scheduling Controller (FGSC) is designed on the basis of the incomplete derivative ahead PID control system to make the controller suitable for various situations. The parameters in the fuzzy scheme are optimized via many cycles of trial-and-error in a 10-meter-deep water tank. Significant improvements have been observed through simulation and experimental results within 4-DOFs.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2545-2547
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• 2000

In this paper, a hybrid fuzzy controller using genetic algorithm based on parameter estimation mode to obtain optimal control parameter is presented. First, The control input for the system in the HFC is a convex combination of the FLC's output in transient state and PID's output in steady state by a fuzzy variable, namely, membership function of weighting coefficient. Second, genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller utilizing the conventional methods for finding PID parameters and estimation mode of scaling factor. The algorithms estimates automatically the optimal values of scaling factors, PID parameters and membership function parameters of fuzzy control rules according to the rate of change and limitation condition of control input. Computer simulations are conducted to evaluate the performance of proposed hybrid fuzzy controller. ITAE, overshoot and rising time are used as a performance index of controller.