• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.3
• /
• pp.261-268
• /
• 2002

This paper represents that auto tunings of membership functions and weights in the fuzzy neural networks are effectively performed by immune algorithm. A number of hybrid methods in fuzzy-neural networks are considered in the context of tuning of learning method, a general view is provided that they are the special cases of either the membership functions or the gain modification in the neural networks by genetic algorithms. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also, it can provide optimal solution. Simulation results reveal that immune algorithms are effective approaches to search for optimal or near optimal fuzzy rules and weights.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.106.5-106
• /
• 2002

1. Introduction 2. Artificial Immune Networks and Navigation Algorithm 3. Obstacle Avoidance and Goal Approach Behavior 4. Weights Adjustment Using Neural Network 5. Velocity Control and Local Minimum Avoidance 6. Simulation 7. Conclusion

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2004.11a
• /
• pp.16-16
• /
• 2004

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.358-363
• /
• 2003

Optimal tuning plays an important role in operations or tuning of the complex process such as the main steam temperature of the thermal power plant. However, it is very difficult to maintain the steam temperature of power plant using conventional optimization methods, since these processes have the time delay and the change of the dynamic characteristics in the reheater. Up to the present time, the Pm controller has been used. However, it is not easy to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper suggests immune algorithm based tuning technique for PID Controller on steam temperature process with long dead time and its results are compared with genetic algorithm based tuning technique.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.19 no.11
• /
• pp.1103-1109
• /
• 2009

In this paper, the control of a membrane used in reverse osmosis desalination plant by using immune algorithm(IA) is addressed. The proposed algorithm IA of auto tuning method can find optimal gains and compared with conventional Ziegler-Nichols tuning method. The results of computer simulation represent that the proposed IA shows a good control performances better than Ziegler-Nichols tuning method.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.41 no.4
• /
• pp.51-58
• /
• 2004

This paper proposes a new artificial immune approach to on-line hardware test which is the most indispensable technique for fault tolerant hardware. A novel algorithm of generating tolerance conditions is suggested based on the principle of the antibody diversity. Tolerance conditions in artificial immune system correspond to the antibody in biological immune system. In addition, antigen presenting cell (APC) is realized by Quine-McCluskey method in this algorithm and tolerance conditions are generated through GA (Genetic Algorithm). The suggested method is applied to the on-line monitoring of a typical FSM (a decade counter) and its effectiveness is demonstrated by the computer simulation.

• Proceedings of the KIEE Conference
• /
• 1998.11a
• /
• pp.286-288
• /
• 1998

A digital distance relaying algorithm immune to the effect of the fault resistance in single-phase to ground fault is proposed. The power frequency components of relaying signals are extracted by the 1 cycle DFT. To compensate the magnitude and phase of the estimated impedance, which is calculated by the general method, this algorithm uses phase difference between the zero sequence impedance of networks on both sided of the system.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.51 no.1
• /
• pp.8-17
• /
• 2002

This paper suggests that the immune algorithm can effectively be used in tuning of a PID controller. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems with a less flexible result to the external behavior. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. In addition to that, tuning performance cannot be guaranteed with regards to a plant with non-linear characteristics or many kinds of disturbances. Along with these, this paper used immune algorithm in order that a PID controller can be more adaptable controlled against the external condition, including moise or disturbance of plant. Parameters P, I, D encoded in antibody randomly are allocated during selection processes to obtain an optimal gain required for plant. The result of study shows the artificial immune can effectively be used to tune, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.9 no.5
• /
• pp.269-276
• /
• 2014

In recent, autonomous navigation techniques to avoid obstacles have been studied by using unmanned aircraft vehicles(UAVs) since the increment of UAV's interest and utilization. Particularly, autonomous navigation based UAVs are utilized in several areas such as military, police, media, and so on. However, there are still some problems to avoid obstacle when UVAs perform autonomous navigation. For instance, the UAV can not forward in the corner of corridors even though it utilizes the improved vanish point algorithm that makes an autonomous navigation system. Therefore, in this paper, we propose an obstacle avoidance technique based on immune algorithm for autonomous navigation of Quadrotor. The proposed algorithm is consisted of two steps such as 1) single color discrimination and 2) multiple color discrimination. According to the result of experiments, we can solve the previous problem of the improved vanish point algorithm and improve the performance of autonomous navigation of Quadrotor.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.525-530
• /
• 2003

This paper focuses on design of nonlinear power plant controller using immune based multiobjective fuzzy approach. The thermal power plant is typically regulated by the fuel flow rate, the spray flow rate, and the gas recirculation flow rate. However, Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature. the change of the dynamic characteristics in the steam-turbine system. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. These parameters tuned by multiobjective based on immune network algorithms could be used for the tuning of nonlinear power plant.