• Journal of Power Electronics
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• v.11 no.4
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• pp.393-400
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• 2011

The main objective of this paper is to control the speed of Nonlinear Hybrid Electric Vehicle (HEV) by controlling the throttle position. Various control techniques such as well known Proportional-Integral-Derivative (PID) controller in conjunction with state feedback controller (SFC) such as Pole Placement Technique (PPT), Observer Based Controller (OBC) and Linear Quadratic Regulator (LQR) Controller are designed. Some Intelligent control techniques e.g. fuzzy logic PD, Fuzzy logic PI along with Adaptive Controller such as Self Organizing Controller (SOC) is also designed. The design objective in this research paper is to provide smooth throttle movement, zero steady-state speed error, and to maintain a Selected Vehicle (SV) speed. A comparative study is carried out in order to identify the superiority of optimal control technique so as to get improved fuel economy, reduced pollution, improved driving safety and reduced manufacturing costs.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.145-152
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• 1995

This paper presents a novel SOFLIC(self organizing fuzzy logic intelligent controller) for reactor rod control system in nuclear power plant. The output of fuzzy controller is gener ated by using two signal : the error between reference and average temperature, and the error between reference and neutron flux-converted temperatures. Flexibility of the controller is enhanced by using self-organizing feature and the controller respond to variation of system parameter with more precision. performances of the SOFLIC and PID are simulated with the model developed for a nuclear power plant. The SOFLIC is superior to PID : SOFLIC provides more rapid load following capability. more robustiness for variation in process dynamics and minimization of engineer's mistakes in controller design.

• Journal of Internet Computing and Services
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• v.2 no.2
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• pp.105-116
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• 2001

According to increase of the factory-automation's(FA) in the field of production, the autonomous guided vehicle's(AGV) role is also increased, The study about an active and effective controller which can flexibly prepare for the changeable circumstance is in progressed. For this study. the research about ac1ion base system to evolve by itself is also being actively considered In this paper. we composed an ac1ive and effective AGV fuzzy controller to be able to do self-organization, For composing it. we tuned suboptimally membership function using genetic algorithm(GA) and improved the control efficiency by the self-correction and generating the control rules. self-organizing controlled(SOC) fuzzy controller proposed in this paper is capable of Self-organizing by using the characteristics of fuzzy controller and genetic algorithm. It intuitionally controls AGV and easily adapts to the circumstance.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.127-130
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• 1995

Fuzzy controllers have proven to be powerful in controlling dynamic processes where mathematical models are unknown or intractable and ill-defined. The way of improving the performance of a fuzzy controller is based on making up rules, constructing membership functions, selecting a defuzzification method and adjusting input-output scaling factors. But there are many difficulties in tuning those to optimize a fuzzy controller. So, in this paper, we propose the look-up table based self-orgenizing fuzzy controller (LSOFC) which optimizes look-up values resulting from the above fuzzy processes. We use the plus-minus tuning method(PMTM), scanning the value through the processes of addition and subtraction. Simulation results demonstrate that the performance of LSOFC is far better than that of a non-tuning fuzzy controller.

• KSBB Journal
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• v.15 no.1
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• pp.14-21
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• 2000

In this study, algae cultivation using the photobioreactor has been applied to remove the nitrogen and phosphorus compounds in the wastewater of the livestock industry. The optimal ratio of nitrate and ortho-phosphate concentration was found for the enhancement of removal efficiency. To achieve the high density culture of algae, the photobioreactor consisted of optical fibers wes developed to get the sufficient light intensity. The light could be illuminated uniformly from light source to the entire reactor by the optical fibers. The structured kinetic model was proposed to describe the growth rate, consumption rate of nitrates and ortho-phosphates in algae culture. The self-organizing fuzzy logic controller incorporated with genetic algorithm was constructed to control the semi-continuous wastewater treatment system. The proposed fuzzy logic controller was applied to maintain the nitrated concentration at the given set-point with the control of wastewater feeding rate. The experimental results showed that the self-organizing fuzzy logic controller could keep the nitrate concentration and enhance algae growth.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.737-741
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• 1993

In this paper, we design the fuzzy logic controller(FLC) for a nonlinear multivariable steam generating unit. Based on the knowledges of operator, the self-organizing controller(SOC) - a kind of FLC - is developed and tested. Both FLC and SOC based on linguistic rules have the advantages of not needing of some exact mathematical model for plant to be controlled. Beside, the SOC modifies the existing control rules by monitoring the control performance. The computer simulations have been carried out for the 200MW steam generating unit to show the usefulness of the proposed method and the effects of disturbances and parameter variations are considered.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.242-247
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• 2002

According to increase of the factory-automation(FA) in the field of production, the importance of the autonomous guided vehicle's(AGV) role has also increased. This paper is about an active and effective controller which can flexibly prepare for changeable circumstances. For this study, research about an behavior-based system evolving by itself is also being considered. In this Paper, we constructed an active and effective AGV fuzzy controller to be able to carry out self-organization. To construct it, we tuned suboptimally membership function using a genetic algorithm(GA) and improved the control efficiency by self-correction and the generation of control rules.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.125-130
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• 1999

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.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.129-134
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• 1992

Fuzzy theory has shown good control performance for non-linear system that is difficult to be controlled by the conventional controller. Backpropagation neural network can interpolate output without the priori knowledge of its dynamics. In this paper, we proposes a Fuzzy-Neural Controller. The Fuzzy Control by deterministic rule may not be sensitive for uncertain conditions and has a disadvantage of setting the rule by repeatedly experience. To solve such problems, we construct Self organizing Fuzzy-Neural Controller which can reorganize the fuzzy rule according to the state of system. Experimental results show that proposed Fuzzy-Neural Controller has better performance than conventional controller(PID) has especially rising time and overshoot characteristics.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.65-69
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• 2002

The main drawback of “classical”fuzzy systems is the inability to design and maintain their database. To overcome this disadvantage many types of extensions adding the adaptivity property to those systems were designed. This paper deals with one of them a new hybrid adaptation structure, called gradient-incremental adaptive fuzzy controller connecting gradient-descent methods with the so-called self-organizing fuzzy logic controller designed by Procyk and Mamdani. The aim is to incorporate the advantages of both Principles. This controller was implemented and tested on the system of LEGO robots. The results and comparison to a ‘classical’(non-adaptive) fuzzy controller designed by a human operator are also shown here.