• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.350-350
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• 2000

Since the heat exchange system, such as the boiler of power plant, gas turbine, and radiator require a high rate heat efficiency and the efficiency of these systems is depended on the control methods. However, it is important f3r operator to understand control system of these systems. In order to properly apply control equipment to these process control systems, such as boiler, any other heat process, or process control system it is necessary to understand the basic aspects and operation principle of the process that relate control, interrelationships of the process characteristics, and the dynamics that are involved. Generally, PID controllers are used in these systems but it is difficult for engineer to understand the complex dynamics and the tuning method because of the coupling action and disturbance in the system loop. In this paper, we design an effective experimental system fur automatic control education and analyze its characteristics through experimental system and industrial plant control software to study how they can team automatic control system by experiments.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.51-57
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• 2020

A propeller-based seesaw system is a system that can represent one of axis of four propeller drones and its stabilization has been replaced by intelligent control system instead of often used control methods such as PID and state space. Today, robots are increasingly use machine learning methods to adapt to their environment and learn to perform the right actions. In this article, we propose a Q-learning-based approach to control the stability of a seesaw system with a propeller. From the experimental results that it is possible to fully learn the balance control of a seesaw system by correctly defining the state of the system, the actions to be performed, and the reward functions. Our proposed method solves the seesaw stabilization.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.8
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• pp.1104-1110
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• 2012

The inverted pendulum system is a common, interesting control problem that involves many basic elements of control theory. In the early, controls of stabilization for the inverted pendulum system were used classical methods like PD, PID controller. In recently, however, control methods based on modern and intelligent control theory are widely applied. The fuzzy logic controller which is often used in nonlinear control is a little too hard to design due to increasing fuzzy rules rapidly if the given system like inverted pendulum has many state variables. Also, in case the state variables are divided into two parts, two fuzzy controllers are needed in the control system. In this paper, the authors propose FCSC(Fuzzy Controller based on State variables Combination) that reorganized into two new signals depending on the physical meaning of the four state variables of the inverted pendulum system. The proposed method is applied to the inverted pendulum system and simulations are accomplished to illustrate the control performance.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1983-1989
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• 2005

Industrial robots are powerful, extremely accurate multi-jointed systems, but they are heavy and highly rigid because of their mechanical structure and motorization. Therefore, sharing the robot working space with its environment is problematic. A novel pneumatic artificial muscle actuator (PAM actuator) has been regarded during the recent decades as an interesting alternative to hydraulic and electric actuators. Its main advantages are high strength and high power/weight ratio, low cost, compactness, ease of maintenance, cleanliness, readily available and cheap power source, inherent safety and mobility assistance to humans performing tasks. The PAM is undoubtedly the most promising artificial muscle for the actuation of new types of industrial robots such as Rubber Actuator and PAM manipulators. However, some limitations still exist, such as the air compressibility and the lack of damping ability of the actuator bring the dynamic delay of the pressure response and cause the oscillatory motion. In addition, the nonlinearities in the PAM manipulator still limit the controllability. Therefore, it is not easy to realize motion with high accuracy and high speed and with respect to various external inertia loads in order to realize a human-friendly therapy robot To overcome these problems a novel controller, which harmonizes a phase plane switching control method with conventional PID controller and the adaptabilities of neural network, is newly proposed. In order to realize satisfactory control performance a variable damper - Magneto-Rheological Brake (MRB) is equipped to the joint of the manipulator. Superb mixture of conventional PID controller and a phase plane switching control using neural network brings us a novel controller. This proposed controller is appropriate for a kind of plants with nonlinearity uncertainties and disturbances. The experiments were carried out in practical PAM manipulator and the effectiveness of the proposed control algorithm was demonstrated through experiments, which had proved that the stability of the manipulator can be improved greatly in a high gain control by using MRB with phase plane switching control using neural network and without regard for the changes of external inertia loads.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.738-743
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• 2007

In this paper, a muscle motion sensing system and an artificial arm control system are studied. The artificial arm is for the people who lost one's forearm. The muscle motion sensing system detect the intention of motion from the upper arm's muscle. In sensing system we use flex sensors which is electrical resistance type sensor. The sensor is attached on the biceps brachii muscle and coracobrachialis muscle of the upper arm. We propose an algorithm to classify the one's intention of motions from the sensor signal. Using this algorithm, we extract the 4 motions which are flexion and extension of the forearm, pronation and supination of the arm. To verify the validity of the proposed algorithms we made experiments with two d.o.f. artificial arm. To reduce the control errors of the artificial arm we also proposed a fuzzy PID control algorithm which based on the errors and error rate.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.516-523
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• 2001

This paper introduces a indirect rotor position and speed estimation algorithm for the SRM(switched reluctance motor) sensorless control based on the sliding mode observer and evolutionary programming The information of position and speed is generally provided by encoder or resolve. However, the position sensor not only adds complexity, cost and size to the whole drive system, but also causes limitation for industrial applications. In this paper, in order to eliminate the position sensor, indirect position sensing, indirect position sensing method using sliding mode observer is used for SRM drives. But if sliding mode observer parameters are selected to be large, the corresponding rapid changes of estimated position and velocity result in chattering phenomenon. Therefore in order to reduce the chattering, this observer parameters are optimized by evolutionary programming. And PID controller is also optimized to track precisely for the SRM using evolutionary programming.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.299-305
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• 2015

Global environmental concerns and the ever increasing need of energy, coupled with steady progress in renewable energy technologies, are opening up new opportunities for utilization of renewable energy resources. Distributed electricity generation is a suitable option for sustainable development thanks to the load management benefits and the opportunity to provide electricity to remote areas. Solar energy being easy to harness, non-polluting and never ending is one of the best renewable energy sources for electricity generation in present and future time. Due to the random and intermittent nature of solar source, PV plants require the adoption of an energy storage and management system to compensate fluctuations and to meet the energy demand during night hours. This paper presents an efficient, economic and technical model for the design of a MPPT based grid connected PV with battery storage and management system. This system satisfies the energy demand through the PV based battery energy storage system. The aim is to present PV-BES system design and management strategy to maximize the system performance and economic profitability. PV-BES (photovoltaic based battery energy storage) system is operated in different modes to verify the system feasibility. In case of excess energy (mode 1), Li-ion batteries are charged using CC-CV mechanism effectively controlled by fuzzy logic based PID control system whereas during the time of insufficient power from PV system (mode 2), batteries are used as backup to compensate the power shortage at load and likewise other modes for different scenarios. This operational mode change in PV-BES system is implemented by State flow chart technique based on SOC, DC bus voltages and solar Irradiance. Performance of the proposed PV-BES system is verified by some simulations study. Simulation results showed that proposed system can overcome the disturbance of external environmental changes, and controls the energy flow in efficient and economical way.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.109-115
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• 2010

A main technology of opening and closing a sluice gate is accurate synchronous and position control for the two cylinders when they are moving with the sluice gate together over 10[m]. Since the supply flow and supply pressure of cylinders are not constant and a nonlinear friction force of the piston in cylinders exists, a difference will be made between the displacement of two cylinders. This difference causes the sluice gate to deform and abrade, and even it may be out of order. In order to solve this problem we design two kinds of fuzzy PI controllers. The former is for a position control of two cylinders, the latter is for their synchronous control. We show some simulation results compare the performance of fuzzy PI controller to the conventional PID controller.

• 전자공학회논문지 IE
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• v.43 no.4
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• pp.28-36
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• 2006

In this paper, an algorithm to classify the 4 motions of arm and a control system to position control the prosthesis are studied. To classify the 4 motions, we use flex sensors which is electrical resistance type sensor that can measure warp of muscle. The flex sensors are attached to the biceps brchii muscle and coracobrachialis muscle and the sensor signals are passed the sensing system. 4 motion of the forearm - flexion and extension, the pronation and supination are classified from this. Also position of forearm is measured from the classified signals. Finally, A two D.O.F prosthesis arm with RC servo-motor is designed to verify the validity of the algorithm. At this time, fuzzy controller is used to reduce the position error by rotary inertia and noise. From the experiment, the position error had occurred within about 5 degree.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.1
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• pp.34-48
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• 2017

This study proposes a new approach to control a trajectory control of vertical type articulated robot arm with six revolution joints by computed torque method for manufacturing process automation. The proposed control scheme takes advantage of the properties of the fuzzy controllers. The proposed method is suitable to control of the trajectory and path control in cartesian space for vertical type articulated robot manipulator for forging manufacturing process automation. The results is illustrated that the proposed fuzzy computed torque controller is more stable and robust than the conventional computed torque controller. This study is included with an analytical methodology of inverse kinematic computation for 6 DOF manipulators. And an intelligent PID based on feed forward fuzzy control structure is applied to control the working path control with disturbances caused by uncertainty parameters of the manipulator dynamic model. Lastly, the validity of proposed is verified by simulations and experiments.