• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.473-483
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• 2015

This paper reports the single-input-single-output cascade control by using 1-axis attitude control test-bench for quad-rotor UAV. The test-bench was designed as a see-saw shape using 2 motors and propellers, and to enable changing the center of gravity with the center of gyration using ballast. The experiment was carried out by constructing a PID-PID controller having a cascade structure with the test-bench. The SIMC based PID gain tuning process, which makes PID gain tuning easy, was grafted to cascade control. To graft SIMC method, the system parameter estimation result was conducted with second order time delay model by using Matlab-Simulink. Gain tuning was conducted by simulating with estimated system parameter. In this paper, the conventional application of SIMC was conducted and improved application was proposed for improving stability at tuning process.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.06b
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• pp.325-330
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• 2006

Integrating processes are frequently encountered in process industries. Generally they are most commonly associated with level control problems. In this paper, tuning formulae of PID controllers for set-point tracking and load disturbance rejection are presented on integrating processes with time delay. In particular, the controller parameters are determined such that performance criteria(IAE, ISE and ITSE) are minimized. Optimal PID parameter sets are obtained by means of a real-coded genetic algorithm(RCGA) and then tuning rules are addressed using obtained PID parameter sets and another RCGA. The performances of the proposed tuning rules are tested on two processes.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1137-1139
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• 2002

In this paper, recurrent artificial neural network (RNN) based self tuning speed controller is proposed for the high performance drives of induction motor. RNN provides a nonlinear modeling of motor drive system and could give the information of the load variation, system noise and parameter variation of induction motor to the controller through the on-line estimated weights of corresponding RNN. Thus, proposed self tuning controller can change gains of the controller according to system conditions. The gain is composed with the weights of RNN. For the on-line estimation of the weights of RNN, extended kalman filter (EKF) algorithm is used. Self tuning controller that is adequate for the speed control of induction motor is designed. The availability of the proposed controller is verified through the MATLAB simulation with the comparison of conventional PI controller.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.5
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• pp.37-42
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• 2004

This paper presents an optimal and robust tuning method of decentralized PI controller for the TITO second order systems to be formulated as LQR. The procedure is developed by establishing relationships between the closed-loop state equation including the decentralized PI tuning parameter and the . closed-loop state equation of LQR and by selecting the weighting factors Q and R of the cost function in order to satisfy the design specifications In frequency domain which the stability robustness and satisfied the performance guaranteed.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.490-498
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• 2016

Proportional Integral Derivative (PID) controller tuning is an area of interest for researchers in many areas of science and engineering. This paper presents a new algorithm for PID controller tuning based on a combination of bacteria foraging and particle swarm optimization. BFO algorithm has recently emerged as a very powerful technique for real parameter optimization. To overcome delay in an optimization, combine the features of BFOA and PSO for tuning the PID controller. This new algorithm is proposed to combine both the algorithms to get better optimization values. The real time prototype model of paper machine is designed and controlled by using PIC microcontroller embedded with the programming in C language.

• Journal of Ocean Engineering and Technology
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• v.3 no.2
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• pp.551-551
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• 1989

In general, a remotely operated vehicle(ROV) operates at deep sea. The control system of ROV is composed of two local loops; the first loop placed on the surface vessel monitors and manipulates the attitude of the ROV using joystick, and the second part on the ROV automatically controls thrusters and acquires positional data. This paper presents a position control simulation of a ROV using an adaptive controller and discusses the control effects of two different conditions. The design of an adaptive control system is obtained by the application of a self-tuning controller with the minimization of an appropriate cost function. The parameters of the control system are estimated by a recursive least square method(RLS). In the simulation, a Runge-Kutta method is used for the numerical integration and the generated outputs are obtained by adding measurement errors. Additionally, this paper discusses the mathematical modelling of a ROV and make a survey of control systems.

• Journal of Ocean Engineering and Technology
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• v.3 no.2
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• pp.51-58
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• 1989

In general, a remotely operated vehicle(ROV) operates at deep sea. The control system of ROV is composed of two local loops; the first loop placed on the surface vessel monitors and manipulates the attitude of the ROV using joystick, and the second part on the ROV automatically controls thrusters and acquires positional data. This paper presents a position control simulation of a ROV using an adaptive controller and discusses the control effects of two different conditions. The design of an adaptive control system is obtained by the application of a self-tuning controller with the minimization of an appropriate cost function. The parameters of the control system are estimated by a recursive least square method(RLS). In the simulation, a Runge-Kutta method is used for the numerical integration and the generated outputs are obtained by adding measurement errors. Additionally, this paper discusses the mathematical modelling of a ROV and make a survey of control systems.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.327-331
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• 1989

This paper concerned about a study on the direct pole placement PID self-tuning controller design for Robot manipulator control system. The method of a direct pole placement self-tuning PID control for a DC motor of robot manipulator tracks a reference velocity in spite of the parameters uncertainties in nonminimum phase system. In this scheme, the parameters of controller are estimated by the recursive least square(RLS) identification algorithm, the pole placement method and diophantine equation. A series of simulation in which minimum phase system and nonminimum phase system are subjected to a pattern of system parameter changes is presented to show some of the features of the proposed control algorithm. The proposed control algorithm which shown are effective for the practical application, and experiments of DC motor speed control for Robot manipulator by a microcomputer IRH-PC/AT are performed and the results are well suited.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.3
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• pp.40-50
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• 1996

By using the neural networks(NN) as system identifier, the on-line self tuning method for fuzzy controller(FC) is proposed. In theis method, the learning of NN is carried out during control operation of FC and the cinsequent parameters of FC is tuned on-line automatically by means of system output errors backpropagated through NN. The Sugeno fuzzy model with constants as consequent parameters is selected for simplifying computation. In procedures of parameter tuning, the gradient descent method is used and the gradient vectors for adjusting the weight of NN are transferred as controller output errors. To evaluate the performance, the proposed method is applied to the inverted pendulum system.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.238-242
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• 1991

This paper presents an approach to self-tuning PI control of dynamic plants, based on fuzzy logic application. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a fuzzy logic controller, one of the most difficult problem is the selection of linguistic control rules and parameters. To overcome this difficulty, self-tuning fuzzy PI controller (STFPIC) with a hierarchical structure in which the fuzzy PI controller is assigned as the lower level and the rule modification and parameter adjustment as the higher level. The rules and parameters are generated by the adjustment of membership function through performance index(PE). In this paper, the algorithm for of the controller performance is estimated by means of computer simulation.