• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.61-64
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS32OC50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator. In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters are determined by the pole-placement method. Performance of self-tuning adaptive controller is illustrated by the simulation and experiment for a SCARA robot.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.117-123
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• 2001

To improve control performance of a non-linear system, many other reserches have used the sliding model control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However, this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network. The perturbation estimator based on the fuzzy adaptive network generates the control input of compensating unmodeled dynamics terms and disturbance. And the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluation control performance of the proposed approach, tracking control simulation is carried is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.143-153
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• 1997

At the on-line control method FLC(Fuzzy Logic Controller) is stronger to the disturbance than a classical controller and its overshoot of the initialized value is excellent. The fuzzy controller can do a proper control, though it doesn't know the mathematical model of the system or the parameter value. But to make the control rule of the fuzzy controller through an expert's experiance has a changes of the control system, the control rule is fixed, it can't adjust to the environment changes of the control system, the controller output value has a minute error and it can't convergence correctly to the desired value[1][2]. There are many ways to eliminate the minute error[3][4][5], but in this paper suggests EP-FNNIC(Fuzzy Neurla Network Intelligence Controller) intelligence controller which combines FLC with NN(Neural Network) and EP(Evolution Programming). The output characteristics of EP-FNNIC controller will be compared and analyzed with FLC. It will be showed that this EP-FN IC controller converge correctly to the desirable value without any error. The convergence speed, overshoot, rising time, error of steady state of controller of these two kinds also will be compared.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.242-244
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• 1992

Conventionally in the industrial control, PlD controller has been used because of its robustness, and nonlinear characteristic of a system under control. Although the PlD controller produce suitable parameter of the each system and also variable of PlD controller should be changed according to environment, disturbance, load. In this paper, the convergence and learning accuracy of the back-propagation(BP) method in neural network are investigated by analyzing the reason for decelerating the convergence of BP method. and examining the rapid deceleration of the convergence when the learning is executed on the part of sigmoid activation function with the very small first derivative. The modified logistic activation function it proposed by defining the convergence factor based on the analysis and applied to the position and speed control of a DC-servo motor. This paper revealed for experimental, a neural network and a PD controller combined off-line system using developed the position and speed characteristics of a DC-servo motor.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.858-863
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• 1988

A micro-processor based control system for a brushless DC motor used in the motor-driven electromechanical total artificial heart was developed. Functionally, the control system is composed of two parts. The first part is the velocity and position controller to assure that the motor follows a predetermined optimal velocity profile with minimal energy consumption, and to guarantee the full stroke length. This part also utilize the passive adaptive control method to be robust against the load disturbance, system parameter variation, and uncertainty which is the environment of artificial heart system. The pump output control is the second part, and this part provides the required responses of the artificial heart to the time-varying physiologic demands. The basic requirements of these responses are preload sensitivity, afterload insensitivity, and the balanced ventricular outputs. The performance and reliability of this control system was evaluated through a series of mock circulation tests and animal implantation, and the results are very encouraging.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.482-489
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• 2015

CSTR (Continuous Stirred Tank Reactor) which plays a key role in the chemical plants exhibits highly nonlinear behavior as well as time-varying behavior during operation. The control of CSTRs in the whole operating range has been a challenging problem to control engineers. So, a variety of feedback control forms and their tuning methods have been implemented to guarantee the satisfactory performance. This paper presents a scheme of designing a nonlinear PID controller incorporating with a GA (Genetic Algorithm) for the temperature control of a CSTR. The gains of the NPID controller are composed of easily implementable nonlinear functions based on the error and/or the error rate and its parameters are tuned using a GA by minimizing the ITAE (Integral of Absolute Error). Simulation works for reference tracking and disturbance rejecting performances and robustness to parameter changes show the feasibility of the proposed method.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.2 no.3
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• pp.243-255
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• 1990

The objective of this study is to present an efficient measurement method of the effective thermal diffusivity for the fibrous insulation material. The non-linear parameter estimation (NPE) method is adapted for this analysis because of its accuracy and its results are compared with those by other direct methods such as CTP, CHP and STD method. A experimental system is constructed with bell-jar vaccum chamber, diffusion pump, tube type furnace, control unit and data acquisition system included with A/D converter and IBM XT/AT personal computer. The typical results obtained from this study are as follows; 1) NPE method can be recommended as an useful and accurate method to measure the effective thermal diffusivity of insuation material because it is shown that the measurement error compared with those by other direct methods is reduced for standard material, NBS-1450b. 2) NPE method can minimize the effects of ill-measured temperature due to external disturbance, because the final value is found by point to point estimating. 3) NPE method dose not depend on the kinds of heat flux, since the surfac temperature are used to estimate the thermal diffusivity. 4) With NPE method, compared with the steady state method, a measuring time and a sample size could be reduced.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.351-354
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• 2006

In underwater environment, the control of AUV is difficult, because of the existence of parameter uncertainties and disturbances as well as highly nonlinear and coupled system dynamics. The requirement for the simple and robust controller which works satisfactorily in those dynamical uncertainties, call for a design using the PD or sliding mode controller. The PD controller is very popular controller in the industrial field and the sliding mode controller has been used successfully for the AUV controller design. In this paper, the two controllers arc designed for ISiMI(Integrated Submergible Intelligent Mission Implementation) AUV and the performances are compared by numerical simulation under the modeling uncertainty and disturbances. The design process of PD and sliding mode controller for ISiMI AUV and simulation results are included to compare the performances of the two controllers.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.1
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• pp.15-20
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• 2002

An electro-hydraulic manipulator using hydraulic actuators has many nonlinear elements, and its parameter fluctuations are greater than those of an electrically driven manipulator. So it is relatively difficult to realize not only stable contact work but also accurate force control for the automatic assembly tasks using hydraulic manipulators. In this manuscript, we applied a compliance control, which is based on the position control by a disturbance observer for our manipulator system. A reference trajectory modification method is proposed in order to achieve accurate force control even though the stiffness and the position of the environment change. Experimental results show that highly robust force tracking by a 6-link electro-hydraulic manipulator could be achieved under various environment conditions. The proposed force control algorithm is applied to the approaching of bolt and the wrenching of nut tasks as one typical task in the maintenance work of live power electric line and is experimentally confirmed very effective for the task.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.402-410
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• 2013

In this paper, a novel and robust Power System Stabilizer (PSS) is proposed as an effective approach to improve stability in electric power systems. The dynamic performance of proposed PSS has been thoroughly compared with Conventional PSS (CPSS). Both the Real Coded Genetic Algorithm (RCGA) and Particle Swarm Optimization (PSO) techniques are applied to optimum tune the parameter of both the proposed PSS and CPSS in order to damp-out power system oscillations. Due to the high sufficiency of both the RCGA and PSO techniques to solve the very non-linear objective, they have been employed for solution of the optimization problem. In order to verify the dynamic performance of these devices, different conditions of disturbance are taken into account in Single Machine Infinite Bus (SMIB) power system. Moreover, to ensure the robustness of proposed PSS in damping the power system multi-mode oscillations, a Multi Machine (MM) power system under various disturbances are considered as a test system. The results of nonlinear simulation strongly suggest that the proposed PSS significantly enhances the power system dynamic stability in both of the SMIB and MM power system as compared to CPSS.