• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1297-1302
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• 2014

This paper presents modern optimization methods for determining the optimal parameters of proportional-integral-derivative (PID) controller for coupled tank systems. The main objective is to obtain a fast and stable control system for coupled tank systems by tuning of the PID controller using the Particle Swarm Optimization algorithm. The result is compared in terms of system transient characteristics in time domain. The obtained results using the Particle Swarm Optimization algorithm are also compared to conventional PID tuning method like the Ziegler-Nichols tuning method, the Cohen-Coon method and IMC (Internal Model Control). The simulation results have been simulated by MATLAB and show that tuning the PID controller using the Particle Swarm Optimization (PSO) algorithm provides a fast and stable control system with low overshoot, fast rise time and settling time.

• 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.15 no.10
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• pp.974-981
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• 2009

In this paper, a method of auto-tuning of PID (Proportional-Integral-Derivative) and PIDA (Proportional-Integral-Derivative-Acceleration) controllers is proposed that can be applied to a time-delayed second order model. The proposed identification method is based on step responses, but it can be easily automated rising digital controller unlike the existing graphical identification methods. We provide a ways to yield parameter identifications which is independent to initial values of the plants. The tuning rule is based on the pole-placement strategy and is formulated so that it can be implemented using a digital controller with ease.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.111-116
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• 2004

In this paper, parameters of a given DC motor system are estimated using the model adjustment technique and the real coded genetic algorithm(RCGA) technique. A number of tuning methods, based on experience and experiment, such as Ziegler-Nichols, Cohen-Coon, IMC, L-ITAE Method have been proposed to obtain parameters for the PID controller. This paper proposes estimating parameters of PID controller using RCGA. The performance of the proposed algorithm is demonstrated through simulations and experiences.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.333-336
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• 1992

In this paper, We propose a PID-type of self-tuning algorithm which is based on the parameter estimation and the minimization of the cost function. We use the CARIMA model for parameter estimation and determine the discrete PID controller parameters by minimizing the cost function which considers the quadratic deviations of the predicted output over the set-point as well as the control efforts. Also, The algorithm is extended by incorporating constraints of the control signal. Simulations are performed to illustrate the efficiency of the proposed method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2000.04a
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• pp.56-63
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• 2000

Abstract - In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. 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 adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. 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 immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.

• 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.

• Smart Structures and Systems
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• v.14 no.4
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• pp.643-658
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• 2014

This paper presents the design, modelling and, simulation and experimental results of a shape memory alloy (SMA) actuator based critical motion control application. Dynamic performance of SMA and its ability in replacing servo motor is studied for which the famous open loop unstable balancing ball and beam system direct driven by antagonistic SMA is designed and developed. Simulation uses the mathematical model of ball and beam structure derived from the first principles and model estimated for the SMA actuator by system identification. A PID based cascade control system consisting of two loops is designed and control of ball trajectory for various target positions with settling time as control parameter is verified experimentally. The results demonstrate the performance of SMA for a complicated i.e., under actuated, highly nonlinear unstable system, and thereby it's dynamic behaviour. Control strategies bring out the effectiveness of the actuator and its possible application to much more complex applications such as in aerospace control and robotics.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.579-584
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• 1998

This paper presents an efficient algorithm which determines the parameters of discrete PID controller. The proposed algorithm is an algebraic method to obtain controller parameters using ROM(Reduced Order Model), which can not only make design procedure simple but also reduce the computational burden required for controller implementation. Also, by solving a set of linear equations based on least squares method, the proposed method can make the controller design procedure systematic. Simple examples are given to demonstrate the effectiveness of our method when compared with widely-used conventional method.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.321-325
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• 1988

The objective of this study is to develop a microcomputer-based adaptive controller for an electro hydraulic velocity control system subjected to the variation of system parameters. The step response performance of the system with the adaptive controller is investigated for the variation of the external load torque, the moment of inertia and the reference inputs, and compared with that obtained by PID controller whose gains are constant. The experimental results show that this proposed model reference adaptive controller is robust to the variation of system parameters and yield much better control performance compared with the conventionel PID controller.