• Journal of Institute of Control, Robotics and Systems
• /
• v.2 no.4
• /
• pp.297-305
• /
• 1996

In this paper a novel robust adaptive fuzzy controller for the nonlinear system with state-dependent uncertainty is proposed. The conventional adaptive fuzzy controller determines the function of state variable bounding the state-dependent uncertain term in the system dynamics on the local state space by off-line calculation. Whereas the proposed method determines that function by the fuzzy inference so that it guarantees the stability of the closed loop system globally on the whole state space. In addition, the method is applicable to the multi-input system. We applied the proposed method to the Burn Control of the Tokamak fusion reactor whose dynamics contains the state-dependent uncertainty and proved the effectiveness of the scheme by using the simulation results.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.260-264
• /
• 1998

In this paper, we implemented the neuro-computer called MY-NEUPOWER in our research to carry out the artificial neural networks (ANN) calculating. An application software was developed based on a neural network using back-propagation (BP) algorithm under the UNIX platform by the specified computer language named MYPARAL. This neural network model was used as an auxiliary controller in the temperature control of sinter cooler system in steel plant which is a nonlinear system. The neural controller was trained off-line using the real input-output data as training pairs. We also made the system description of adaptive neural controller on the same temperature control system. We will carry out the whole system simulation to verify the suitability of neural controller in improving the system features.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.53 no.2
• /
• pp.82-88
• /
• 2004

In this study, an intelligent solenoid valve controller has been developed for efficient maintaining of filters in a dust collecting system. This controller has automatic controllability of solenoid valves' ON/OFF time depending on the clogging status of filters, and then it can extend the filters' lifetimes, decrease the power consumption, and make effective operation of the system possible. This controllability has been executed by the fuzzy theory that utilizes the workers' experimental knowledges, the control expert's knowledges and the differential pressures between the inlets and outlets measured by the sensors. The system's operation is under the continuous surveillance by using a current transformer, which warns the operators and lets them take necessary actions in case of abnormal operation.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.15 no.6
• /
• pp.269-279
• /
• 2020

This paper presents the design and implementation of embedded systems and autonomous path generation for autonomous speed sprayer. Autonomous Orchard Systems can be divided into embedded controller and path generation module. Embedded controller receives analog sensor data, on/off switch data and control linear actuator, break, clutch and steering module. In path generation part, we get 3D cloud point using Velodyne VLP16 LIDAR sensor and process the point cloud to generate maps, do localization, generate driving path. Then, it finally generates velocity and rotation angle in real time, and sends the data to embedded controller. Embedded controller controls steering wheel based on the received data. The developed autonomous speed sprayer is verified in test-bed with apple tree-shaped artworks.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.5
• /
• pp.892-897
• /
• 2007

This paper presents the output filter design and the output characteristic analysis by cut-off frequency set up of the LCR filter on NPC multi-level inverter with trap-filter. The single-phase NPC three-level inverter operates at low switching frequency. The proposed LC trap filter is comprised of a conventional LCR output filter, by using LC trap filter the need for high damping resistor and low LC cut-off frequency is eliminated. Also. low damping resistor is increased the output filter system. The multilevel inverter system used NPC type inverter in proper system for high power application and controller is used DSP(TMS320C31). The effectiveness of proposed system confirmed the validity through SPICE simulation and experimental results.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1283-1288
• /
• 2003

This paper proposes an approach to attitude control artificial satellites with jet-engine. The jet-engine produces on-off thrust, which can be modelled as pulse-width-modulated (PWM) function. Therefore, the problem is converted to design a PWM controller and we develop an efficient technique for this purpose using digital redesign. The digital redesign is a converting technique a well-designed analog controller into the equivalent digital one maintaining the property of the original analog control system in the sense of state-matching. The redesigned digital controller is again converted into PWM controller using the equivalent area principle. We show a computer simulation of the attitude control of artificial satellites.

• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.897-899
• /
• 1999

This paper presents a scaling factor tuning method to improve the performance of fuzzy logic controller. Tuning rules and reasoning are utilized off-line to determine the scaling factors based on absolute value of the error and its difference. In this paper We proposed a new method to generate fuzzy logic controllers throught genetic algorithm. The developed approach is subsequently applied to the design of proportional plus integral type fuzzy controller for a dc-servo motor control system. The performance of this control system is demonstrated higher than a conventional fuzzy logic controller(FLC).

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.681-686
• /
• 1991

In this paper, a novel self-organizing fuzzy plus PID control algorithm is proposed and analyzed by extensive computer simulations and experiments with an inverted pendulum. Specifically, the proposed self-organizing fuzzy controller consists of a typical fuzzy reasoning part and self organizing part in which both on-line and off-line algorithms are employed to modify the 'then' part of the fuzzy rules and to decide how much fuzzy rules are to be modified after evaluating the control performance, respecfively. And the fuzzy controller is replaced by a PID controller in a prespecified region near by the set point for good settling actions.

• Proceedings of the KIEE Conference
• /
• 2002.07d
• /
• pp.2824-2826
• /
• 2002

Immune system is an evolutionary biological system to protect innumerable foreign materials such as virus, germ cell, and etcetera. Immune algorithm is the modeling of this systems response that has adaptation and reliability when disturbance occur. In this paper, immune algorithm is proposed to control four wheels steering AGV(Automated Guided Vehicle) in container yard. The adaptive immune system is applied to the PID controller. For design the PID controller using immune algorithm, we tune PID parameters by off-line manner, in order to avoid the damage from abrupt control force. Repeatedly, the PID parameters are adjusted to be accurate by on-line fine tuner of immune algorithm. And then the computer simulation result from the viewpoint of yaw rate and lateral displacement are analyzed and compared with result of conventional PID controller.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.3
• /
• pp.246-254
• /
• 2002

In this paper auto-tuning scheme of PID controller based on the reference model has been studied for a Process control system by immune algorithm. Up to this time, many sophisticated tuning algorithms have been tried in order to improve the PID controller performance under such difficult conditions. Also, a number of approaches have been proposed to implement mixed control structures that combine a PID controller with fuzzy logic. However, in the actual plant, they are manually tuned through a trial and error procedure, and the derivative action is switched off. Therefore, it is difficult to tune. Since the immune system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (Parallel Distributed Processing) network to complete patterns against the environmental situation. Simulation results reveal that reference model basd tuning by immune network suggested in this paper is an effective approach to search for optimal or near optimal process control.