• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.4
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• pp.701-708
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• 2017

This paper proposes an optimum design method using Teaching-Learning-based optimization for the fuzzy PID controller of Magnetic levitation rail-guided vehicle. Since an attraction-type levitation system is intrinsically unstable, it is difficult to completely satisfy the desired performance through the conventional control methods. In the paper, a fuzzy PID controller with fixed parameters is applied and then the optimum parameters of fuzzy PID controller are selected by Teaching-Learning optimization. For the fitness function of Teaching-Learning optimization, the performance index of PID controller is used. To verify the performances of the proposed method, we use a Maglev model and compare the proposed method with the performance of PID controller. The simulation results show that the proposed method is more effective than conventional PID controller.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.7
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• pp.283-288
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• 1985

This paper is concerned with the analysis of microprocessor-based PID control for the current source inverter-induction motor derive system. A linearized dynamic model of the motor is derived and is converted into the discrete-time model. With the equation, the overall system including the feedback loops is formulated into a single discrete-time state equation. The stability regions are determined at various values of controller gains. The transient responses of the motor speed are simulated by digital computer and are verified by laboratory experiments.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2333-2335
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• 2000

The main motivation of this research is to develop an intelligent control strategy for Activated Sludge Process(ASP). ASP is a complex and nonlinear dynamic system because of the characteristic of a wastewater, the change of an influent flow rate, weather conditions, and etc. The mathematical model of ASP also includes uncertainties which are ignored or not considered by process engineer or controller designer. The ASP is generally controlled by a PID controller that consists of fixed proportional, integral, and derivative gain values. The PID gains can be adjusted by the expert in the ASP. The ASP model based on Matlab$^{(R)}$5.3/Simulink$^{(R)}$3.0 is developed in this paper. Various control methods are applied to the ASP model and the control results are disscussed. Three control methods are designed and tested: conventional PID controller, fuzzy logic control approach to modify setpoints, and fuzzy-PID control method.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.10
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• pp.65-77
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• 2004

In this paper, we propose an adaptive mechanism based on immune algorithm and neural network identifier technique. It is also applied fur an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To solve this problem, we use the neural network identifier (NNI) technique fur modeling the plant and humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using an immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. Finally, the simulation and experimental result fur the control of steering and speed of AGV system illustrate the validity of the proposed control scheme. These results for the proposed method also show that it has better performance than other conventional controller design methods.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_1
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• pp.753-758
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• 2024

Trajectory tracking of the AMR robot is one research for the AMR robot navigation. For the control system of the Autonomous mobile robot(AMR) being in non-honolomic system and the complex relations among the control parameters, it is d ifficult to solve the problem based on traditional mathematics model. In this paper, we presents a simple and effective way of implementing an adaptive tracking controller based on the PID for AMR robot trajectory tracking. The method uses a non-linear model of AMR robot kinematics and thus allows an accurate prediction of the future trajectories. The proposed controller has a parallel structure that consists of PID controller with a fixed gain. The control law is constructed on the basis of Lyapunov stability theory. Computer simulation for a differentially driven non-holonomic AMR robot is carried out in the velocity and orientation tracking control of the non-holonomic AMR. The simulation results of wheel type AMR robot platform show that the proposed controller is more robust than the conventional back-stepping controller to show the effectiveness of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.188-193
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• 1992

The PID controllers which is widely used in the process industry are poorly damped when the dynamic process contains significant dead time or when there are random disturbances acting on the plant. GPC is known to be more superior than conventional self-tuning algorithm in overcoming above problem and prior choice of model order. In this paper, we propose the method which determine the parameter of PID controller from minimization of GPC criterion. The controller has emplicit scheme which is comprised of parameter estimation and PID control design. Simulation results show the performance of the proposed self-tuning PID controller.

• Journal of Power System Engineering
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• v.15 no.2
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• pp.69-77
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• 2011

In this paper, an optimal PID sliding mode controller is proposed for the position control of electro-hydrostatic actuator(ERA) systems with system uncertainties and saturation in the motor. An ERA prototype is developed and system modeling and parameter identification are executed. Then, optimal PID and optimal anti-windup PID controller are designed based on identified system model by using optimization toolbox in MA TLAB/Simulink and the performance of the two control systems are compared by experiment. It was found that the optimal anti-windup PID control system has better performance than the optimal anti-windup PID control system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1012-1015
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• 2003

Recently technologies have created new principle and theory but the PID control system remains its popularity as the PID controller contains simple structure, including maintenance and parameter adjustment being so simple. The adjust parameter of PID to achieve best response of process which be using time and may be error if user are not expert. Nowadays this problem was solved by develop PID controller which can analysis and auto tune parameter are appropriate with process which used principle of Ziegler ? Nichols but it are expensive and designed for each task. Thus, this paper proposes auto tune PID based on FPGA by use principle of Dahlin which maximum overshoot not over 5 percentages and do not fine tuning again. It have performance in control process are neighboring controller in industrial and simple to use. Especially, It can use various process and low price. The auto tune digital PID processor embedded on chip FPGA XC2S50-5tq-144. The digital PID processor was designed by fundamental PID equation which architectures including multiplier, adder, subtracter and some other logic gate. It was verified by control model of temperature control system.

• Design & Manufacturing
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• v.17 no.3
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• pp.41-47
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• 2023

This paper presents the development of a controller that can control the temperature of an heating system based on a thermoelectric module. Temperature controller using Peltier has various external factors such as external temperature, characteristics of an aluminum plate, installation location of temperature sensors, and combination method between the aluminum plate and heating element. Therefore, it is difficult to apply the simulation and simulation results of heating system using Peltier at control algorithm. In general, almost temperature controller is using PID algorithm that finds control gain value heuristically. In this paper, it is proposed mathematical model that explain correlate between the temperature of the heating system and input voltage. And then, optimal parameter of estimated thermal model of the aluminum plate are searched by using genetic algorithm. In addition, based on this estimated model, the optimal PID control gain are inferred using a genetic algorithm. All of the sequence are simulated and verified with proposed real system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.786-791
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• 2005

This paper is concerned with the examination and evaluation concerning a tuning method of multivariable PID controllers based on partial model matching on frequency domain proposed by authors from practical view point. In this case, PID controller parameters are determined by minimizing the loss function defined by the difference between frequency response of ideal model transfer function and actual frequency response on several frequency points. The purpose of the paper is to examine and evaluate the performance of the method through actual experiments of MIMO liquid level experimental process control equipment.