• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.374-377
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• 2006

본 논문은 에어컨 시스템의 효율성과 안정성에 기초하여, 과열도와 저압을 제어하는 Fuzzy 제어기 설계를 제안한다. 에어컨 시스템은 Compressor(압축기), Condenser(응축기), Evaporator(증발기), Expansion Valve(확장 밸브) 로 구성되며, 각각의 기기에 대한 제어가 독립적으로 이루어져 있다. 기존의 제어가 한 제어기를 사용한 단일방식으로 이루어지다보니 에어컨 시스템의 특성인 냉매의 상태가 달라지면 시스템 전반적으로 그 영향이 파급되는 부분까지 고려를 해 주지 못하고, 제어기의 성능이 효율적이고 안정적이지 못했다. 본 논문에서는 에어컨 시스템의 효율과 안정도에 결정적인 영향을 미치는 과열도와 저압(증발기의 압력)을 제어하기 위해, 비선형성이 강하고 불확실하며 복잡한 시스템을 쉽게 제어할 수 있는 Fuzzy 제어기를 구성하여, Expansion Valve 와 Compressor 에서 동시에 제어하는 Multi 제어기를 설계한다. 제안된 Fuzzy 제어기는 이산형 lookup_table 방식과 연속형 간략추론 방식을 사용하여 제어기를 설계하고, 유전자 알고리즘(GAs)을 이용하여 최적의 Fuzzy 제어기의 환산계수를 구한다. 그리고 시뮬레이션 결과를 통해 이산형 lookup_table 방식과 연속형 간략추론 방식의 각각의 제어기를 사용한 결과를 비교한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.603-610
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• 2001

Industrial processes are normally operated by skilled humans who have the cumulative and logical information about the system. Fuzzy control has been investigated for many application. Intelligent control approaches based on fuzzy logic have a chance to include human thinking. This paper represents modeling approach based upon operators knowledge without mathematical model of the system and optimize the controller. The experimented system is constructed for sending a ball to the goal position using wind of two DC motors in the predefined path. A vision camera to mimic human eyes detects the ball position. The system used in this experiment could be hardly modeled by mathematical methods and ould not be easily controlled by conventional manners. The controller is designed based on the input-output data and experimental knowledge obtained by trials, and optimized under the predefined performance criterion. And this paper shows the data adaptation for changeable operating condition. When the system is driven in the abnormal condition with unconsidered noise, the new optimal operating parameters could be defined by adjusting membership functions. Thus, this technique could be applied in industrial fields.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.2
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• pp.85-91
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• 2000

This paper proposes a novel method with pseudo-on-line scheme using the optimized look-up table based on the genetic algorithm which does not use the gradient and finds the global optimum of an un-constraint optimization problem. The technique is a pseudo-on-line method that optimally estimates the parameters of fuzzy PID(FPID) controller for systems with non-linearity, using the genetic algorithm. The proposed controller(GFPID) with the auto-tuning function is applied to the on-line and real-time control of speed at 3-phase induction motor, and its computer simulation is carried out. simulation results show that the proposed methodis more excellent that conventional FPID and PID controllers.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.12
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• pp.566-574
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• 2001

In designing fuzzy models and controllers, we encounter a major difficulty in the identification f an optimized fuzzy rule base, which is traditionally achieved by a tedious trial-and-error process. This paper presents an approach to the evolutionary design of an optimal fuzzy rule base for modeling and control. Evolutionary programming is used to simultaneously evolve the structure and the parameter of fuzzy rule base for a given task. To check the effectiveness of the suggested approach, four numerical examples are examined. The performance of the identified fuzzy rule bases is demonstrated.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.58-65
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• 2001

This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that he selected solution become the global optimal solution by optimizing the Akaikes information criterion expressing the quality of the inference rules. The trajectory tracking simulation and experiment of the polishing robot show that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding mode controller provides reliable tracking performance during the polishing process.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.182-182
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• 2000

This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that the selected solution become the global optimal solution by optimizing the Akaike's information criterion. The trajectory trucking experiment of the polishing robot system shows that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding model controller provides reliable tracking performance during the polishing process.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.179-183
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• 1999

This paper describes a new method for indirect sensing of the rotor position in switched reluctance motors using fuzzy logic algorithm. Through a novel fuzzy algorithm, the complete SRM magnetizing characterization is first constructed, and then used to estimate the rotor position. And also, the optimized phase is selected by phase selector. To demonstrate the promise of this approach, the proposed rotor position estimation algorithm is simulated for variable speed range.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.138.5-138
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• 2001

The autonomous robot has the ability of obstacle avoidance and target tracking with some manufactured information. In this paper, it is shown that autonomous mobile robot can avoid fixed obstacles using the map made before and the fuzzy controller is adopted with the global path planing and the local path planing when the robot navigates. With that map sensor, information will be used when an autonomous robot navigates. This paper proves that robot can navigate through optimized route and keep the stable condition.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1949-1954
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• 2005

One of control methods for underactuated manipulators is known as a switching control which selects a partially-stable controller using a prespecified switching rule. A switching computed torque control with a fuzzy energy region method was proposed. In this approach, some partly stable controllers are designed by the computed torque method, and a switching rule is based on fuzzy energy regions. Design parameters related to boundary curves of fuzzy energy regions are optimized offline by a genetic algorithm (GA). In this paper, we discuss on parameters obtained by GA. The effectiveness of the switching fuzzy energy method is demonstrated with some simulations.

• International Journal of Automotive Technology
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• v.3 no.4
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• pp.165-170
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• 2002

For a vehicle Anti-lock Braking System (ABS), the control target is to maintain friction coefficients within maximum range to ensure minimum stopping distance and vehicle stability. But in order to achieve a directionally stable maneuver, tire side forces must be considered along with the braking friction. Focusing on combined braking and turning operation conditions, this paper presents a new control scheme for an ABS controller design, which calculates optimal target wheel slip ratio on-line based on vehicle dynamic states and prevailing road condition. A fuzzy logic approach is applied to maintain the optimal target slip ratio so that the best compromise between braking deceleration, stopping distance and direction stability performances can be obtained for the vehicle. The scheme is implemented using an 8-DOF nonlinear vehicle model and simulation tests were carried out in different conditions. The simulation results show that the proposed scheme is robust and effective. Compared with a fixed-slip ratio scheme, the stopping distance can be decreased with satisfactory directional control performance meanwhile.