• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.15 no.2
• /
• pp.126-131
• /
• 2015

Studies on the control of inverted pendulum type systems have been widely reported. This is because this type of system is a typical complex nonlinear system and may be a good model to verify the performance of a proposed control system. In this paper, we propose the design of two fuzzy logic control systems for the control of a Segway mobile robot which is an inverted pendulum type system. We first introduce a dynamic model of the Segway mobile robot and then analyze the system. We then propose the design of the fuzzy logic control system, which shows good performance for the control of any nonlinear system. In this paper, we here design two fuzzy logic control systems for the position and balance control of the Segway mobile robot. We demonstrate their usefulness through simulation examples. We also note the possibility of simplifying the design process and reducing the computational complexity. This possibility is the result of the skew symmetric property of the fuzzy rule tables of the system.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.2270-2273
• /
• 2003

Fuzzy logic control has been widely implemented in air conditioning and ventilation systems which has uncertainty or high robust system. Since the dynamic behaviors of the systems contain complexity and uncertainty in its parameters , several fuzzy logic controllers had been implemented to control room temperature in the field of air conditioning system. In this paper, the fuzzy logic control has been developed to control room temperature and humidity in the precision air conditioning systems. The nonlinear mathematical model was formulated using energy and continuity equations. MATLAB was used to simulate the fuzzy logic control of the multi-variable air conditioning systems. The simulation results show that fuzzy logic controller can reduce the steady-state errors of the room temperature and relative humidity in multivariable air conditioning systems. The offset are less than 0.5 degree Celsius and 3 percent in relative humidity respectively under random step disturbance in heating load and moisture load respectively

• Transactions of the Korean Society of Automotive Engineers
• /
• v.2 no.5
• /
• pp.23-29
• /
• 1994

The design procedure for fuzzy logic controller depends on the expert's knowledge or trial and error. Moreover, it is very difficult to guarantee the stability and robustness of the system due to the linguistic expression of fuzzy control. However, fuzzy logic control has succeeded in many control problems that the conventional control theory has difficulties to deal with. As a result, this control theory is applied to the engine control system which a mathematical model is difficult. In this study, the fuzzy logic is applied to obtain the gain of PI control at idle speed control system, and a simple engine model is developed in order to perform simulation. Experimental results show that the response to reach the target engine speed at idle speed control system is improved by adopting the gain obtained with fuzzy logic.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1264-1267
• /
• 2005

Fuzzy logic control has been widely applied for handling the system which has uncertainty or high robust system. Since the dynamic behaviors of the systems contain complexity and uncertainty in its parameters, several fuzzy logic controllers have been implemented to control room temperature in the field of air conditioning system. In this paper, the fuzzy logic control has been developed to control both in door temperature and humidity in the air conditioning systems. The manipulating variables are speed of compressor, heater and supply air flow rate. The microcomputer was used to interface with in system. The experimental results show the superior of multivaiable fuzzy logic control to keep room temperature and humidity in air conditioning system for the best comfortable.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.1
• /
• pp.104-111
• /
• 2000

A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.640-643
• /
• 1997

This paper describes speed controller of a induction motor for electric vehicles using PLL and Fuzzy logic. The proposed system is combined precise speed control of PLL and robust, fast speed control of Fuzzy logic. The motor speed is adaptively incremented or decremented toward the PLL locking range by the Fuzzy logic using information of sampled speed errors and then is maintained accurately by PLL. The results of experiment show excellence of proposed system and that the proposed system is appropriates to control the speed of induction motor for electric vehicles.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.8 no.5
• /
• pp.196-206
• /
• 2000

These days, the fuzzy logic or the fuzzy set theory has received attention from a number of researchers in the area of industrial application. Moreover, the fuzzy logic control has been successfully applied to a large numbers of control problems where the conventional control methods had failed. Using this control theory we designed a climate controller for an automotive climate control system whose mathematical model is difficult. This paper describes an automotive climate control where the fuzzy control has been used to stabilize parameter uncertainties and disturbance effects. To show the validity and effectiveness of the proposed control method, the fuzzy logic controller was implemented with a philips 80C552 microcomputer chip and tested in an actual vehicle. From the experimental results, it could be conduced that the proposed controller is superior to conventional controllers in both control performance and thermal comfort. The climate control system in cars is difficult to model mathematically so we tested a fuzzy logic control system which promised better results.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.3
• /
• pp.46-54
• /
• 1997

In this paper, we psropose the feedback linearization technique for a nonlinear system using genetic algorithms (GAs) and fuzzy logic system. The proposed control scheme approximates the nonlinear term of a nonlinear system using the fuzzy logic system and computes the control input for cancelling the nonlinear term. Then in the fuzzy logic system, the number and shape of membership function of the premise aprt will be tuned to minimize the control error boundary using GAs. And the parameters of the consequence of fuzzy rule will be tuned by the adaptive laws based on lyapunov stability theory in order to guarantee the closed loop stability of control system. The evolution of fuzzy logic system is processed during the on-line adaptive control. The effectiveness of proposed method will be demonstrated by computer simulation of simple nonlinear sytem.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.4
• /
• pp.352-357
• /
• 2007

This paper deals with modeling method and application of Fuzzy Discrete Event System(FDES). FDES have characteristics which Crisp Discrete Event System(CDES) can't deals with and is constituted with the events that is determined by vague and uncertain judgement like biomedical or traffic control. We proposed Real-time Fuzzy Temporal Logic Framework(RFTLF) to model Fuzzy Discrete Event System. It combines Temporal Logic Framework with Fuzzy Theory. We represented the model of traffic signal systems for intersection to have the property of Fuzzy Discrete Event System with Real-time Fuzzy Temporal Logic Framework and designed a traffic signal controller for smooth traffic flow. Moreover, we proposed the method to find the minimum-time route to reach the desired destination with information obtained in each intersection. In order to evaluate the performance of Real-time Fuzzy Temporal Logic Framework model proposed in this paper, we simulated unit-time extension traffic signal controller model of the latest signal control method on the same condition.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.490-493
• /
• 1996

This paper presents a control scheme for the motion of a 2 DOF robot manipulator. Robot manipulators are multivariable nonlinear systems. Fuzzy logic is avaliable human-like control without complex mathematical operation and is suitable to nonlinear system control. In this paper, Implementation of fuzzy logic control of robotic manipulators shows. Algorithm has been performed with simulation packages MATRIXx and SystemBuild.