• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.12
• /
• pp.1137-1147
• /
• 2004

In this paper, we proposed two types of adaptive control mechanism which is named HIA(Humoral Immune Algorithm) PID and CMIA(Cell-Mediated Immune Algorithm) controller based on biological immune system under engineering point of view. The HIA PID which has real time control scheme is focused on the humoral immunity and the latter which has the self-tuning mechanism is focused on the T-cell regulated immune response. To verify the performance of the proposed controller, some experiments for the control of AGV which is used for the port automation to carry container without human are performed. The experimental results for the control of steering and speed of an AGV system illustrate the effectiveness of the proposed control scheme. Moreover, in that results, proposed controllers have better performance than other conventional PID controller and intelligent control method which is the NN(neural network) PID controller.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.23 no.9A
• /
• pp.2211-2220
• /
• 1998

This paper presetns an adaptive critic self-learning control system with cerebellar model articulation controller (CMAC)-based decoder integrated with the associative search element (ASE) and adatpive critic element(ACE)- based scheme. The tast of the system is to balance a pole that is hinged to a movable cart by applying forces to the cart's base. The problem is that error feedback information is limited. This problem can be sloved when some adaptive control devices are involved. The ASE incorporates prediction information for reinforrcement from a critic to produce evaluative information for the plant. The CMAC-based decoder interprets one state to a set of patways into the ASE/ACE. These signals correspond to te current state and its possible preceding action states. The CMAC's information interpolation improves the learning speed. And design inverted pendulum hardware system to show control capability with neural network.

• Proceedings of the KIEE Conference
• /
• 1988.11a
• /
• pp.430-433
• /
• 1988

An adaptive control system for D.C servo drive is developed via minimum variance control theory. The problem of designing this controller under varying load conditions is discussed. A robust self tuning controller that can track a constant reference and reject constant load disturbance is developed. Simulation study shows that the controller has excellent adaptation, capability as well as transient recovery under load changes.

• The Journal of Korean Association of Computer Education
• /
• v.9 no.2
• /
• pp.69-78
• /
• 2006

Educational evaluation is not the work to rank learners hierarchically, but the thing to increase the educational effectiveness by solving a learner's problem and improving the education process from the proper evaluation. The conventional evaluation systems have measured a learner's recognition level by dichotomy. Although they support the evaluation depending on a learner's academic ability and supply the feedback for wrong selection, it is insufficient to take out study-motive and give the establishment for a guidance point of learning. In this paper, we propose the web-based individual adaptive testing system in considering partial score for a learner. Our system are effective to estimate the ability of learner by considering partial score in detail and offer an feedback study from the self-diagnosis function for a learning results.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.28 no.3
• /
• pp.262-273
• /
• 1992

In this study, we selected a DC servo motor as an actuator of the marine diesel engine governor and constructed the position control system of the DC servo motor using the algorithm proposed by authors. Next, we proposed an another method to construct an adaptive control system for marine diesel engine by regarding the controlled system including the DC servo motor as a second order controlled system and verified the validity of this method through the real time control responses. Finally, the results have shown a good response characteristic.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.9
• /
• pp.122-132
• /
• 1993

In this paper, a self tuning control algorithm is proposed for the high performance drive of DC servo motor, which is adequate to the servo system having frequent load variation. In order to realization of the algorithm, the control system is developed using a fixed point high speed digital signal processor. TMS320C25. Control algorithm is composed of two parts. One is estimation law part using recursive least mean square method, the other is control law part using minimum variance control method. For the purpose of easiness of applying adaptive algorithm, developed control system is based o PC-DSP structure which can develop, debug programs and monitor the dynamic behaviors,etc. Through computer simulation and experimental results, it was verified that proposed control system could estimate system parameters and was robust to the variation of the load and as a result, was adequate to the servo motor drives.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37A no.9
• /
• pp.762-771
• /
• 2012

In this paper, we propose an adaptive power control scheme employing a self-optimization concept in femtocell systems, in order to improve system capacity, thereby reducing call-drop probability. In the proposed scheme, each femto base station(FBS) controls individual channel's transmission power base on two parameters; the neighboring cell's transmission power for each individual channel which is delivered from a femto-gateway and the received power strength from neighboring cells which is periodically measured by means of a spectrum sensing. Adaptive adjustment of individual channel's transmission power in accordance with femto mobile station(FMS) mobility features can also reduce undesirable handovers and evenly distribute traffic load over all femtocells. In addition, the manipulative control of channel's transmission power is able to keep the system coverage and the call-drop probability within an acceptable range, regardless of density of femtocells. Computer simulation shows that the proposed scheme outperforms existing schemes in terms of the system coverage and the call-drop probability.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.825-829
• /
• 2005

This paper presents an approach for designing a fuzzy logic-based adaptive SVC damping In controller for damping low frequency power oscillations. Power systems are often subject to low Frequency electro-mechanical oscillations resulting from electrical disturbances. Generally, power system stabilizers are designed to provide damping against this kind of oscillations. Another means to achieve damping is to design supplementary damping controllers that are equipped with SVC. Various approaches are available for designing such controllers, many of which are based on the concepts of damping torque and others which treat the damping controller design as a generic control problem and apply various control theories on it. In our proposed approach, linear optimal controllers are designed and then a fuzzy logic tuning mechanism is constructed to generate a single control signal. The controller uses the system operating condition and a fuzzy logic signal tuner to blend the control signals generated by two linear controllers, which are designed using an optimal control method. First, we design damping controllers for the two extreme conditions; the control action for intermediate conditions is determined by the fuzzy logic tuner. The more the operating condition belongs to one of the two fuzzy sets, the stronger the contribution of the control signal from that set in the output signal. Simulation studies done on a one-machine infinite-bus and a four-machine two-area test system, show that the proposed fuzzy adaptive damping SVC controller effectively enhances the damping of low frequency oscillations.

• Proceedings of the KIEE Conference
• /
• 2006.07d
• /
• pp.1860-1861
• /
• 2006

In this paper, we design a robust controller of biped robot system with uncertainties, using recurrent neural network. In our proposed control system, we use the self-recurrent wavelet neural network (SRWNN). The SRWNN makes up for the weak points in wavelet neural network(WNN). While the WNN has fast convergence ability, it dose not have a memory. So the WNN cannot confront unexpected change of the system. However, the SRWNN, having advantage of WNN such as fast convergence, can easily encounter the unexpected change of the system. For stable walking control of biped robot, we use sliding mode control (SMC). Here, uncertainties are predicted by SRWNN. The weights of SRWNN are trained by adaptive laws based on Lyapunov stability theorem. Finally, we carry out computer simulations with a biped robot model to verify the effectiveness of the proposed control system,.

• Proceedings of the KIEE Conference
• /
• 2006.10c
• /
• pp.315-317
• /
• 2006

In this paper, we design a terminal sliding mode controller based on neural network for nonlinear systems with uncertainties. Terminal sliding mode control (TSMC) method can drive the tracking errors to zero within finite time. Also, TSMC has the advantages such as improved performance, robustness, reliability and precision by contrast with classical sliding mode control. For the control of nonlinear system with uncertainties, we employ the self-recurrent wavelet neural network(SRWNN) which is used for the prediction of uncertainties. The weights of SRWNN are trained by adaptive laws based on Lyapunov stability theorem. Finally, we carry out simulations to illustrate the effectiveness of the proposed control.