• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.812-814
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• 1999

In this paper, we are applied the Genetic Algorithm (GA) to design of fuzzy logic controller (FLC) for a DC Servo-Motor Speed Control. GA is used to design of the membership functions and scaling factor of FLC. To evaluate the performances of the proposed FLC, we make an experiment on FLC for the speed control of an actual DC servo-motor system with nonlinear characteristics. Experimental results show that proposed controller have better performance than those of PD controller.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.12
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• pp.85-98
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• 1998

This paper proposes a new design method of neuro-FLC by the Lamarckian co-adaptation scheme that incorporates the backpropagation learning into the GA evolution in an attempt to find optimal design parameters (fuzzy rule base and membership functions) of application-specific FLC. The design parameters are determined by evolution and learning in a way that the evolution performs the global search and makes inter-FLC parameter adjustments in order to obtain both the optimal rule base having high covering value and small number of useful fuzzy rules and the optimal membership functions having small approximation error and good control performance while the learning performs the local search and makes intra-FLC parameter adjustments by interacting each FLC with its environment. The proposed co-adaptive design method produces better approximation ability because it includes the backpropagation learning in every generation of GA evolution, shows better control performance because the used COG defuzzifier computes the crisp value accurately, and requires small workspace because the optimization procedure of fuzzy rule base and membership functions is performed concurrently by an integrated fitness function on the same fuzzy partition. Simulation results show that the Lamarckian co-adapted FLC produces the most superior one among the differently generated FLCs in all aspects such as the number of fuzzy rules, the approximation ability, and the control performance.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2423-2425
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• 2004

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and the floor decreases suddenly, the robot has slip state. First of all, this paper models adhesion characteristics and slip in wheeled robot. Secondly, the paper proposes estimation method of adhesion force coefficient(AFC) according to slip velocity. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. The paper proposes an anti-slip control system based on an ordinary disturbance observer, that is, the re-adhesion control is achieved by reducing the driving torque enough to give maximum adhesion force coefficient. fuzzy logic controller(FLC) is petty useful with slip through that compare fuzzy with PI control for the controller performance. These procedure is implemented using a Pioneer 2-DXE parameter.

• Journal of Power Electronics
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• v.7 no.3
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• pp.265-270
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• 2007

Equal rating DC-DC converter modules can be connected in series at the input for circuits requiring higher input voltages and in parallel at the output for circuits requiring higher output currents. Since the converter modules may not be practically identical, closed loop control has to ensure that each module equally shares the total input voltage and the load current. A control scheme consisting of a common output voltage loop, individual inner current loops and individual input voltage loops have been designed in this work to achieve input voltage and load current sharing as well as load voltage regulation under supply and load disturbances. The output voltage loop provides the basic reference for the inner current loops, which are also modified by the respective input voltage loops. The average of the converter input voltages, which is dynamically varying, is chosen as the reference for input voltage loops. This choice of reference eliminates interaction among different control loops. Type II compensators and Fuzzy Logic Controllers (FLCs) are designed and compared through MATLAB based simulation and FLC is found to be satisfactory. Hence TMS320F2407A DSP based FLC is implemented and the results are presented which prove the superiority of the FLC developed for this research.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.4
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• pp.233-237
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• 2012

In this paper, We propose a control system which compensate a output of a main Neual Network using a RTDNN(Recurrent Time Delayed Neural Network) with a FLC(Fuzzy Logic Controller)After a learn of main neural network, it can occur a Over shoot or Under shoot from a disturbance or a load variations. In order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of learning a inverse model neural network of plant, so a expected dynamic characteristics of plant can be got. We can confirm good response characteristics of proposed neural network controller by the results of simulation.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.494-500
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• 2004

The wing rock phenomenon is a high angle of attack aerodynamic motion manifested by limit cycle roll oscillations. Experimental studies reveal that direct control and manipulation of leading edge vortices, through the use of 'blowing' techniques is effective in the suppression of wing rock. This paper presents the design of a robust controller for the experimental implementation of one such 'blowing' technique - recessed angle spanwise blowing (RASB), to achieve wing rock suppression over a range of operating conditions. The robust controller employs Takagi - Sugeno fuzzy system, which is fine-tuned by experimental simulations. Performance of the controller is assessed by real-time wind tunnel experiments with an 80 degree swept back delta wing. Robustness is demonstrated by the suppression of wing rock at a range of angles of attack and free stream velocities. Numerical simulation results are used to further substantiate the experimental findings.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1377-1379
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• 1996

In this paper, each parameter was identified by the gradient descent method to overcome difficulty deciding fuzzy rules of FLC for the unknown process and the type of membership Junctions. Usually PID or optimal control theories have been mostly usee in control field so far. However, optimal control requires much time for calculation because of adaptation for disturbance and nonlinearity. And intricate technique such as MRAS which can be realized only by an expert are limited to be used in the systems requiring rapid and precise response because of comparatively longer calculating time and complicateness. Gradient descent method is a method to find Z minimizing a function about a certain vector Z. And required output of FLC is gained using gradient approaching method in order to adapt control rule parameters of FLC. Simulation proved validation of this algorithm.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.550-555
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• 2002

In this paper, it is presented a new technique to the design and real-time implementation of fuzzy control system based-on digital signal processors in order to improve the precision and robustness for system of industrial robot. Fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the real of industrial processes. In this thesis, a self-organizing fuzzy controller or the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variable of the controller, In the synthesis of a FLC, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult, SOFC is proposed for a hierarchical control structure consisting of basic level and high level that modify control rules.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.202-207
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• 2001

In this paper, it is presented a new technique to the design and real-time implementation of fuzzy control system based-on digital signal processors in order to improve the precision and robustness for system of industrial robot. Fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the real of industrial processes. In this thesis, a self-organizing fuzzy controller for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variable of the controller, In the synthesis of a FLC, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult, SOFC is proposed for a hierarchical control structure consisting of basic level and high level that modify control rules.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.165-170
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• 2000

In this paper, it is presented a new technique to the design and real-time implementation of fuzzy control system based-on digital signal processors in order to improve the precision and robustness for system of industrial robot. Fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the real of industrial processes. In this thesis, a self-organizing fuzzy controller for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variable of the controller, in the synthesis of a FLC, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult, SOFC is proposed for a hierachical control structure consisting of basic level and high level that modify control rules.