• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.188-199
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• 2014

Although the fuzzy logic controller is superior to the proportional integral derivative (PID) controller in motor control, the gain tuning of the fuzzy logic controller is more complicated than that of the PID controller. Using mathematical analysis of the proportional derivative (PD) and fuzzy logic controller, this study proposed a design method of a fuzzy logic controller that has the same characteristics as the PD controller in the beginning. Then a design method of a fuzzy logic controller was proposed that has superior performance to the PD controller. This fuzzy logic controller was designed by changing the envelope of the input of the of the fuzzy logic controller to nonlinear, because the fuzzy logic controller has more degree of freedom to select the control gain than the PD controller. By designing the fuzzy logic controller using the proposed method, it simplified the design of fuzzy logic controller, and it simplified the comparison of these two controllers.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.10
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• pp.888-894
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• 2005

In this paper, experimental studies of balancing a pendulum mounted on a wheeled drive mobile robot and its position control are presented. Main PID controllers are compensated by a neural network. Neural network learning algorithm is embedded on a DSP board and neural network controls the angle of the pendulum and the position of the mobile robot along with PID controllers. Uncertainties in system dynamics are compensated by a neural network in on-line fashion. Experimental results show that the performance of balancing of the pendulum and position tracking of the mobile robot is good.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.154-161
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• 2012

This article presents experimental studies of fuzzy logic application to control a two-wheel mobile robot(TWMR) system. The TWMR system is composed of two systems, an inverted pendulum system and a mobile robot system. Although linear controllers can stabilize the TWMR, fuzzy controllers are expected to have robustness to uncertainties so that the resulting performances are expected to be better. Nominal fuzzy rules are used to control balance and position of TWMR. Fuzzy logic is embedded on a DSP chip to control the TWMR. Balancing performances of the PID controller and the fuzzy controller under disturbances are compared through extensive experimental studies.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.85.6-85
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• 2001

This paper describes a 3-DOF attitude control of a small model helicopter in hover through explicit decoupling and adaptive control scheme. A model helicopter mounted on gimbal-stand is considered as a system that has 3 independent SISO systems representing motions about roll, pitch and yaw axis and these subsystems are identified from the test flight data. In this consideration, the contribution of others to yaw channel is neglected since it is relatively small. Two PID controllers based on Ziegler-Nichols method are designed for roll pitch channels independently. Also, adaptive fuzzy tuner is designed and applied to those PID controllers to cope with coupling effects between each channel and system uncertainties due to variation of engine RPM. The experimental results show that the attitude control ...

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.537-542
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• 2014

This paper proposes a control system to keep the balance of a unicycle robot. The robot consists of the disk and wheel, for balancing and driving respectively, and the tile angle is measured and used for balancing by the IMU sensor. A PID controller is designed based on a non-model based algorithm to prove that it is possible to control the unicycle robot without any approximated linear system model such as the sliding mode control algorithm. The PID controller has the advantage that it is simple to design the controller and it does not require an unnecessary complex formula. In this paper, assuming that the pitch and roll axis are dynamically decoupled, each of the two controllers are designed separately. A reaction wheel pendulum method is used for the control of the roll axis, that is, for balancing and an inverted pendulum concept is used for the control of the pitch axis. To confirm the performance of the proposed controllers using MATLAB Simulink, the dynamic equations of the robot are derived.

• Smart Structures and Systems
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• v.1 no.1
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• pp.13-27
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• 2005

Simultaneous precision positioning and vibration suppression of a reciprocating flexible manipulator is investigated in this paper. The flexible manipulator is driven by a multifunctional active strut with fuzzy logic controllers. The multifunctional active strut is a combination of a motor assembly and a piezoelectric stack actuator to simultaneously provide precision positioning and wide frequency bandwidth vibration suppression capabilities. First, the multifunctional active strut and the flexible manipulator are introduced, and their dynamic models are derived. A control strategy is then proposed, which includes a position controller and a vibration controller to achieve simultaneous precision positioning and vibration suppression of the flexible manipulator. Next, fuzzy logic control approach is presented to design a fuzzy logic position controller and a fuzzy logic vibration controller. Finally, experiments are conducted for the fuzzy logic controllers and the experimental results are compared with those from a PID control scheme consisting of a PID position controller and a PID vibration control. The comparison indicates that the fuzzy logic controller can easily handle the non-linearity in the strut and provide higher position accuracy and better vibration reduction with less control power consumption.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.303-311
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• 2012

In this study, we introduce a dynamic process model as well as the design methodology of optimized fuzzy controller for its efficient application to vacuum production system to produce a semiconductor, solar module and display and so on. In a vacuum control field, PID control method is widely used from the viewpoint of simple structure and preferred performance. But, PID control method is very sensitive to the change of environment of control system as well as the change of control parameters. Therefore, it's difficult to get a preferred performance results from target system which has a complicated structure and lots of nonlinear factors. To solve such problem, we propose the design methodology of an optimized fuzzy PID controller through a following series of steps. First a dynamic characteristic of the target system is analyzed through a series of experiments. Second the process model is built up and its characteristic is compared with real process. Third, the optimized fuzzy PID controller is designed using genetic algorithms. Finally, the fuzzy controller is applied to target system and then its performance is compared with that of other conventional controllers(PID, PI, and Fuzzy PI controller). The performance of the proposed fuzzy controller is evaluated in terms of auto-tuned control parameters and output responses considered by ITAE index, overshoot, rise time and steady state time.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.948-955
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• 2008

The conventional PID controller has been widely employed in industry. However, the PID controller with one degree of freedom(DOF) can not optimize both set-point tracking response and disturbance rejection response at the same time. In order to solve this problem, a few types of 2DOF PID controllers have been suggested. In this paper, a tuning formula for a 2DOF PID controller is presented. The optimal parameter sets of the 2DOF PID controller are determined based on the first-order plus time delay process and a real-coded genetic algorithm(RCGA) such that the ITAE performance criterion is minimized. The tuning rule is then addressed using calculated parameter sets and another RCGA. A set of simulation works are carried out on three processes with time delay to verify the effectiveness of the proposed rule.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.701-704
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• 2005

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They are difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.123-133
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• 2023

Active queue management (AQM) is a leading congestion control system, which can keep smaller queuing delay, less packet loss with better network utilization and throughput by intentionally dropping the packets at the intermediate hubs in TCP/IP (transmission control protocol/Internet protocol) networks. To accelerate the responsiveness of AQM framework, proportional-integral-differential (PID) controllers are utilized. In spite of its simplicity, it can effectively take care of a range of complex problems; however it is a lot complicated to track down optimal PID parameters with conventional procedures. A few new strategies have been grown as of late to adjust the PID controller parameters. Therefore, in this paper, we have developed a Squirrel search based PID controller to dynamically find its controller gain parameters for AQM. The controller gain parameters are decided based on minimizing the integrated-absolute error (IAE) in order to ensure less packet loss, high link utilization and a stable queue length in favor of TCP networks.