• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.690-692
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• 1999

In this thesis, We implement the controller system only using the neural network to identify the plant characteristics with keeping the PID controller structure. The neural network has learned by the adaptive learning rates that has suggested by Chao-Chee Ku and the DBP algorithm. We proposed the on-line tuning algorithm about the unknown plant using the adaptive tuning technique. As a result of executing the parameters has tuned from the initial value to more suitable ones and the output of the Plant has improved and also it is appeared that the convergence is guaranteed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.988-991
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• 2003

In this paper, we try to develop the controller which uses the block diagrams of SIMTool and internal functions CEMTool for planning the global driving controller for high efficiency AGV. We acquire the control efficiency by controlling the motor used each part of AGV driving controller. The block diagram structures provided with SIMTool is easily designed by the controller, and the monitoring and analysis of the results is researched by simulation. We expect to control AGV. robot and various plant using Ziegler-Nichols auto-tuning method and external I/O board

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.384-388
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• 1999

This paper presents auto-tuning to compensate the integrator windup of the current and the speed PID controller of DC motor, which suppress the overshoot of transient response without delay of rising time. The simulation results using Matlab show the validity of auto-tuning methods.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.795-797
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• 1995

In this paper, we present a simple auto-tuning PID controller using genetic algorithms. The basic idea of the scheme is to parameterize a Ziegler-Nichols-like tuning formula by a single parameter ${\alpha}$, then to use GA to select optimal tuning parameter. Also, simple rule mechanisms make the controller adapt against large variations in parametric and dynamics uncertainties in the plant. These scheme lead to improved performance of the transient and steady state behavior of the closed loop system, including processes with long delay-time and nonminimum phase systems.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.9
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• pp.1463-1468
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• 2003

This paper presented the real-time self-tuning learning control based on evolutionary computation, which proves its superiority in finding of the optimal solution at the off-line learning method. The individuals of the populations are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations is proposed. It is possible to control the control object slightly varied as time changes. As the state value of the control object is generated, evolutionary strategy is applied each sampling time because the learning process of an estimation, selection, mutation is done in real-time. These algorithms can be applied; the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes.

• Journal of IKEEE
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• v.28 no.2
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• pp.136-144
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• 2024

In this paper, we propose a PID controller for altitude control of quadrotor system with experimental analysis. The Routh-Hurwitz test is applied to analyze the system to which our proposed controller is applied. We also summarize experimental data in which the gain values of kP, kI, and kD are changed using MATLAB and Simulink based on mathematical modeling of the quadrotor system. Based on the summarized experimental data, we analyze the effect of changes in each gain values (k_P, k_I, k_D) of PID controller on altitude control of quadrotor, and present an algorithm for tuning the PID controller gain values. The PID controller with the proposed algorithm is applied to AR.Drone system, subsequently and result are verifised through experiments.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.4
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• pp.187-194
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• 2002

Recently, the application of the linear machine far industrial field is remarkable increased, especially for the gantry machine, machine tool system and CNC. In these application fields, high dynamics position control performance Is essentially required in both the steady and the transient state. This pacer presents simple but powerful position control loop based on traditional PID controller. The presented position control algorithm, named 'Unified PID Position Controller'has great features for the linear machine drives such as no over-shoot phenomena and simple gain tuning strategy. Through the experimental results with commercial linear motors, it is shown that the proposed algorithm has excellent dynamics suitable fur linear motions.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.5
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• pp.721-728
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• 2009

PID control is widely used to control stable processes, however, PID control for unstable processes is less common. In this paper, systematic tuning methods are derived to tune the PID controller for unstable FOPTD(Forst Order Plus Time Delay) processes. The proposed PID controllers for set-point tracking and disturbance rejection problem are tuned based on minimizing the performance indexes (IAE, ISE, ITAE) using a real-coded genetic algorithm. Simulation example is given to illustrate the set-point tracking and disturbance rejection performance of the proposed method.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2655-2657
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• 2000

this paper suggests a genetic algorithms combining simulated annealing for PID factor tunning. This paper made Off-Line control parameter tuning of the DC servo motor for the speed, In this paper new method to design PID controller through proposed genetic algorithm. Two experiments compared both the PID controller using genetic algorithms and PID controller using proposed genetic algorithm for a DC-servo motor. The result of two experiments was safty higher PID controller using proposed genetic algorithm than PID controller using genetic algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.3
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• pp.161-172
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• 2007

This article suggests an inverse kinematics analysis of a two degree of freedom spatial parallel motion simulator and design methodology of the robust PID controller. The parallel motion simulator consists of a fixed base and a moving frame connected by two serial chains, with each serial chain containing one revolute joint and two passive spherical joint. First, an inverse kinematics problems are solved in order to find the joint variable necessary to bring the end effector to track the desired trajectory. Second, an inverse optimal PID controller is proposed to track trajectories in the face of uncertainty. And the $H_{\infty}$ optimality and robust stability of the closed-loop system is acquired through the PID controller. Finally numerical results show the effectiveness of the PID controller that is designed by square/linear tuning laws.