• Journal of Korean Society of Environmental Engineers
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• v.22 no.10
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• pp.1905-1919
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• 2000

The main motivation of this research is to develop an intelligent control strategy for Activated Sludge Process (ASP). ASP is a complex and nonlinear dynamic system because of the characteristic of wastewater, the change in influent flow rate, weather conditions, and etc. The mathematical model of ASP also includes uncertainties which are ignored or not considered by process engineer or controller designer. The ASP is generally controlled by a PID controller that consists of fixed proportional, integral, and derivative gain values. The PID gains are adjusted by the expert who has much experience in the ASP. The ASP model based on $Matlab^{(R)}5.3/Simulink^{(R)}3.0$ is developed in this paper. The performance of the model is tested by IWA(International Water Association) and COST(European Cooperation in the field of Scientific and Technical Research) data that include steady-state results during 14 days. The advantage of the developed model is that the user can easily modify or change the controller by the help of the graphical user interface. The ASP model as a typical nonlinear system can be used to simulate and test the proposed controller for an educational purpose. Various control methods are applied to the ASP model and the control results are compared to apply the proposed intelligent control strategy to a real ASP. Three control methods are designed and tested: conventional PID controller, fuzzy logic control approach to modify setpoints, and fuzzy-PID control method. The proposed setpoints changer based on the fuzzy logic shows a better performance and robustness under disturbances. The objective function can be defined and included in the proposed control strategy to improve the effluent water quality and to reduce the operating cost in a real ASP.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.2335-2342
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• 2014

If you want to use the unmanned quad rotor for emergency information provision and information about the traffic situation of real-time and moving information is included in the car to help in emergency vehicle operation of the city and in the distribution future innovation the need to consider to have enough safety of the use of silent quad rotor. Therefore, in this study, the unmanned quad rotor system research of safe landing control from the center for the improvement of safety of unmanned quad rotor system you have a motor of four, has taken a good structural balance system based on the dynamic model and motion considering the nonlinear characteristics, and attempts to proceed via non-linearity and system disturbances, tough Fuzzy controller, and analyzed through a computer simulation result.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2908-2914
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• 1998

This paper presents an intelligent signal for controling the traffic lights on traffic junction network with dynamic traffic flow, When a junction is connected to adjacent junctions on four sides. Prior researches have been done on the single traffic junction. However, it is dificult to apply single junction controller to real traffic situation. In this paper, we develop a fuzzy taffic network controller which adjusts the extension time of current green phase by using teh fuzzy input variables such as the number of entering cars at the green light, the number of waiting cars during the red light, and the traffic volume. The proposed method was compared to the existing junction signal control methods on controllers in terms of average delay time of cars and the cost function defined in this paper.

• Geomechanics and Engineering
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• v.31 no.4
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• pp.353-364
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• 2022

This study presents a hybrid algorithm for classifying the rock joints, where the improved artificial bee colony (IABC) and the fuzzy C-means (FCM) clustering algorithms are incorporated to take advantage of the artificial bee colony (ABC) algorithm by tuning the FCM clustering algorithm to obtain the more reasonable and stable result. A coefficient is proposed to reduce the amount of blind random searches and speed up convergence, thus achieving the goals of optimizing and improving the ABC algorithm. The results from the IABC algorithm are used as initial parameters in FCM to avoid falling to the local optimum in the local search, thus obtaining stable classifying results. Two validity indices are adopted to verify the rationality and practicability of the IABC-FCM algorithm in classifying the rock joints, and the optimal amount of joint sets is obtained based on the two validity indices. Two illustrative examples, i.e., the simulated rock joints data and the field-survey rock joints data, are used in the verification to check the feasibility and practicability in rock engineering for the proposed algorithm. The results show that the IABC-FCM algorithm could be applicable in classifying the rock joint sets.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.3
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• pp.394-401
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• 2010

In this article, we investigate a robust friction compensation scheme for the purpose of accomplishing precision positioning performance a servo mechanical system with nonlinear dynamic friction. To estimate the friction state and tackle robustness problem for uncertainty, a RFNN and reconstructed error compensator as well as a robust friction state observer are developed. The asymptotic stability of the series of friction compensation methodologies are verified from the Lyapunov's stability theory. Some simulations and experiments on a servo mechanical system were carried out to evaluate the effectiveness of the proposed control scheme.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1079-1082
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• 1996

To automate an excavator the control issues resulting from environmental uncertainties must be solved. In particular the interactions between the excavation tool and the excavation environment are dynamic, unstructured and complex. In addition, operating modes of an excavator depend on working conditions, which makes it difficult to derive the exact mathematical model of excavator. Even after the exact mathematical model is established, it is difficult to design of a controller because the system equations are highly nonlinear and the state variable are coupled. The objective of this study is to design a fuzzy logic controller(FLC) which controls the position of excavator's attachment. This approach enables the transfer of human heuristics and expert knowledge to the controller. Excavation experiments are carried out to check the performance of the FLC.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.219-225
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• 1991

The characteristics of a power plant changes as it operates for a long time and/or for different operating points. As a result, operators must retune gains of the controllers for better performance. In fact, skilled operators can retune the gains in reference to recorded data obtained by a test called dynamic test. The dynamic test, however, requires much time, and can be heavy burden for operators. In this paper, an expert knowledge-based auto-tuner is designed for drum-type boiler controllers of a fossil power plant using fuzzy logic. The performance of the proposed auto-tuner is shown via computer simulation and the simulation results show that the proposed auto-tuner is satisfactory for the desired performance.

• IE interfaces
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• v.13 no.1
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• pp.92-99
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• 2000

Conflicts and interruptions caused by resource failures and rush orders require a nonlinear dynamic production management. Generally the PP&C systems used in industry presently do not meet these requirements because of their rigid concepts. Starting with the grasp of the disadvantages of current approaches, this paper presents a control structure that enables system to react to various malfunctions using a planning tolerance concept. Also, production processes are modeled by using Fuzzy-Petri-Net modeling tool in other to handle the complexity of job allocation and the existence of many disparities. On the basis of this model the developed system support the short-term shop control by rule based decision.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.177-182
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• 1997

A visual servoing method is proposed for a robot with a camera in hand. Specifically, vanishing point features are suggested by employing a viewing model of perspective projection to calculate the relative rolling, pitching and yawing angles between the object and the camera. To compensate dynamic characteristics of the robot, desired feature trajectories for the learning of visually guided line-of-sight robot motion are obtained by measuring features by the camera in hand not in the entire workspace, but on a single linear path along which the robot moves under the control of a commercially provided function of linear motion. And then, control actions of the camera are approximately found by fuzzy-neural networks to follow such desired feature trajectories. To show the validity of proposed algorithm, some experimental results are illustrated, where a four axis SCARA robot with a B/W CCD camera is used.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.325-329
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• 2001

This paper addresses a control architecture for the hospital service robot, SmartHelper. With a sensing-reasoning-acting paradigm, the deliberation takes place at planning layer while the reaction is dealt through the parallel execution of operations. Hence, the system presents both a hierarchical and an heterarchical decomposition, being able to show a predictable response while keeping rapid reactivity to the dynamic environment. The deliberative controller accomplishes four functions which are path generation, selection of navigation way, command and monitoring. The reactive controller uses fuzzy and potential field method for robot navigation. Through simulation under a virtual environment IGRIP, the effectiveness of the control architecture is verified.