• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.432-439
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• 2012

In this paper, instead of the conventional PD controller for balancing control of two wheeled inverted pendulum robots, an improved PD controller using the neural network is proposed and implemented for performance verification. First, a two wheeled inverted pendulum robot system is constructed for experiment. Next proper gains of the conventional PD controller according to users' weights are obtained for balancing the robot by use of the trial and error method. The PD gains based on the trial and error method are generalized through the neural network. Experiment results show that the PD controller based on the neural network has better performance than the conventional PD controller.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1370-1377
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• 2004

Optimal control gain for time-delay systems is made by an optimal control gain for delay-free systems multiplied by a state transition function for the delay time. The optimal control gain for delay-free systems is obtained by pushing two zeros of the PID controller closely to a larger pole of the second order plant. Thus the optimal tuning of PID controller for time-delay second order system is able to be obtained by calculation for the state transition function.

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.4
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• pp.352-357
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• 2000

The vector control scheme is usually applied to the high performance induction motor drives. The PI controller is adopted traditionally to control the motor speed and currents in the vector control scheme. In this case, the dynamic performance of the induction motor is dependent on the PI gains and the gain optimization is necessary in order to get a good dynamic performance. But, it is very hard to optimize the PI gains uniquely within the speed control range because the equivalent model of the motor control system should be known exactly. In this paper, we propose the hybrid control scheme to remove the defects of PI controller. The hybrid control scheme includes the simplified fuzzy controller which operates in the transient state and the PI controller which operates in the steady state. The proposed scheme is applied to the vector control for induction motor, and the digital simulation and the experimental results are given to verify the proposed scheme.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.301-307
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• 2004

This paper suggests a fuzzy variable structure control scheme for Takagi-Sugeno(T-S) fuzzy model and presents the attitude control of the wheel-driven inverted pendulum(WDIP) based on the proposed control algorithm. The proposed controller is designed based on the T-S fuzzy modeling of nonlinear system and the unification of gain matrices in linear subsystems that constitute the overall fuzzy model. The uncertainties generated in the gain matrix unifying procedure can be interpreted as the input disturbances of the conventional variable structure control. These unifying disturbances can be resolved by using the robustness property of the conventional variable structure system. Design example for wheel-driven inverted pendulum demonstrates the utility and validity of the proposed control scheme.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.56-62
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• 2010

Auto-exposure control automatically calculates and adjusts the exposure for consecutive input image. Recently, this is usually controlled by the sensor gain, however, unsuitable control causes oscillation of luminance for sonsecutive input images, called as flickering. Also, in mobile phone cameras, only simple information, such as the average luminance value, can be utilized due to coarse performance. Therefore, this paper presents a new real-time AE control method using a Look Up Table(LUT) based on Scene-Luminance curves to avoid the generation of flickering. Prior to the AE control, a LUT is constructed, which illustrates the characteristic of outputs for input patches corresponding to sensor gains. The AE control is first performed by estimating a current scene as a patch using the proposed LUT. A new sensor gain is then estimated using also LUT with previously estimated patch. The entire estimation process is performed using linear interpolation to achieve real-time execution. Based on experimental results, the proposed AE control is demonstrated with real-time, flicker-free.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.88-95
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• 2006

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They we difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.4
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• pp.388-398
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• 1998

In constructing fuzzy control systems. there are many parameters such as rule base. membership functions. inference m method. defuzzification. and I/O scaling factors. To control the system in properly using fuzzy logic. we have to consider t the correlation with those parameters. This paper deals with self-tuning of fuzzy control systems. The fuzzy controller h has parameters that are input and output scaling factors to effect control output. And we propose the looklongleftarrowup table b based self-tuning fuzy controller. We propose the PMTM(Plus-Minus Tuning Method) for self tuning method, self-tuning the initial look-up table to the appropriate table by adding and subtracting the values.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.701-704
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• 2005

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They are difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.36-45
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• 1998

In this paper, a method of on-line PI gain-tuninng is proposed for the speed control of brushless D.C. motor by investigating the pattern of input and output without estimating parameter. Proportional gain is tuned in the process to obtain a fast speed response by supplying the maximum constant input. And integral gain is appropriately tuned in the process of proportional control so that the response may be stably converged and the overshoot may be prevented. Therefore because both control and gain-tuning are executed concurrently, additional works that estimate parameters and so on aren't required in the proposed method. In the proposed method, both fast-response and overshoot problem are well solved, and it is more useful and convenient than existing auto-tuning methods in the speed control of D.C. motor. It is illustrated by simulations and experimental results that the proposed method is useful and stable.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.355-367
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• 2007

This paper proposes a design method of the PI(Proportional-Integral)+D(Derivative) controller using self-tuning of the design variables and controller gains. The used fuzzy PI+D controller is the approximated conventional continuos time linear PI+D controller and the used fuzzification method is the fuzzy single tone and the adapted defuzzification method is the simplified tenter of gravity. Fuzzy estimation result would be calculated in the other function elements from the classified fuzzy variables and the result determined by the design variables decides the controller gains. As a result, the proposed method shows the capability of the high speed tuning and can be applied to the case of input variables with many fuzzy partitions and also can bring out the advantage to reduce the reconstruction(digital sampling reconstruction) error. Most simulation results show that this controller makes much bettor efficiency and improvement by using design variables and controller gains.