• International Journal of Control, Automation, and Systems
• /
• v.2 no.3
• /
• pp.362-373
• /
• 2004

In this study, we introduce a noble neurogenetic approach to the design of the fuzzy controller. The design procedure dwells on the use of Computational Intelligence (CI), namely genetic algorithms and neurofuzzy networks (NFN). The crux of the design methodology is based on the selection and determination of optimal values of the scaling factors of the fuzzy controllers, which are essential to the entire optimization process. First, tuning of the scaling factors of the fuzzy controller is carried out, and then the development of a nonlinear mapping for the scaling factors is realized by using GA based NFN. The developed approach is applied to an inverted pendulum nonlinear system where we show the results of comprehensive numerical studies and carry out a detailed comparative analysis.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2000.05a
• /
• pp.228-231
• /
• 2000

A hybrid fuzzy controller by means of the genetic algorithms is presented. The control input for the system in the HFC is a convex combination of the FLC's output in transient state and PlD's output in steady state by a fuzzy variable. The HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance than any other controller. A auto-tuning algorithms is presented to automatically improve the performance of hybrid fuzzy controller using genetic algorithms. The algorithms estimates automatical Iy the optimal values of scaling factors, PID parameters and membership function parameters of fuzzy control rules. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA three kinds of estimation modes are effectively utilized. The HFCs are applied to the second process with time-delay. Computer simulations are conducted at step input and the performances of systems are evaluated and also discussed in ITAE(Integral of the Time multiplied by the Absolute value of Error ) and other ways.

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.695-698
• /
• 1995

The shape and width of fuzzy membership function has an effect on performance of fuzzy controller. In this paper, fuzzy controller is proposed to improve the control performance of fuzzy controller. It has two fuzzy inference engine. The one is typical fuzzy inference engine, the other is proposed to infer optimal width of membership function in fuzzy controller from plant constant (K,T,L). To show the effectiveness of this fuzzy controller with double fuzzy inference engine, it is applied to plant (dead time + 1st order delay) with various plant constant.

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.999-1001
• /
• 1995

In this study, the algorithm of optimal parameter inference is proposed. At this inferring method, we tried to acquire the follow-up to reference pattern through comparing the plant output pattern with random reference pattern. As an inference method, the fuzzy theory was applied and the proposed algorithm was proved by computer simulation.

• Proceedings of the KSME Conference
• /
• 2001.06b
• /
• pp.724-729
• /
• 2001

This paper discusses the composition of the theory of reinforcement learning, which is applied in real-time learning, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line learning method. The individuals are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because the learning process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.7
• /
• pp.22-28
• /
• 1998

This paper includes AC servo motor speed control usig the predictive control strategy. Generally, AC servo motor control should have the fast response characteristics. For the issue, sliding mode control and PID control have been applied. However, the former has the speed ripple response due to the chattering and the latter requires the many trial efforts. Originally, the predictive control which has been used in process control area does not need the priori knowledge for the application system and it is easy to compute the optimal gain with the prediction. In this paper, the TMS320C31 DSP pocessor is used for AC motor control with fst dynamics and the tuning guid-line for the parameters of the predictive control algorithm is given in order to reduce the computation load. Also, the actuator saturationis implemented uisngthe QP(Quadratic Programming) method and the transient response is improved by the identified intertia coefficient when AC motor is drived at forward/reverse rotation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.10a
• /
• pp.324-329
• /
• 1998

In this paper, neural networks predictive PID (NNPPID) control system is proposed to reduce the vibration of structure. NNPPID control system is made up predictor, controller, and self-tuner to yield the optimal parameters of controller. The neural networks predictor forecasts the future outputs based on present input and output of structure. The controller is PID type whose parameters are yielded by neural networks self tuning algorithm. Computer simulations show displacements of multi-story structures applied to NNPPID system about environmental load-wind forces and earthquakes.

• Journal of Communications and Networks
• /
• v.15 no.6
• /
• pp.606-613
• /
• 2013

This paper proposes a complete solution of a contention-based medium access control in wireless local networks to provide station level quality of service guarantees in both downstream and upstream directions. The solution, based on the mature distributed coordination function protocol, includes a new fixed contention window backoff scheme, a tuning procedure to derive the optimal parameters, a super mode to mitigate the downstream bottleneck at the access point, and a simple admission control algorithm. The proposed system guarantees that the probability of the delay bound violation is below a predefined threshold. In addition, high channel utilization can be achieved at the same time. The numerical results show that the system has advantages over the traditional binary exponential backoff scheme, including efficiency and easy configuration.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.1
• /
• pp.70-75
• /
• 2014

TMR(triple modular redundant) digital excitation system with simulator is developed for tuning optimal control parameters during commissioning test and coping with system faults rapidly. A new system which mocks up virtual generator, turbine, grid can simulate as if excitation system is connected to a real generator system by setting four switches. The maintenance crew using the simulator is able to test perfectly the phase controller rectifiers, field breaker, sequence relays as well as TMR controller of the excitation system. Commissioning and performance results about the excitation system with simulator is discussed. The trial product was installed and operated at a 500MW thermal power plant after the commissioning test.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.2
• /
• pp.390-398
• /
• 2014

The systematic optimal tuning of power system stabilizers (PSSs) using the dynamic embedded optimization (DEO) technique is described in this paper. A hybrid system model which has the differential-algebraic-impulsive-switched (DAIS) structure is used as a tool for the DEO of PSSs. Two numerical optimization methods, which are the steepest descent and Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithms, are investigated to implement the DEO using the hybrid system model. As well as the gain and time constant of phase lead compensator, the output limits of PSSs with non-smooth nonlinearities are considered as the parameters to be optimized by the DEO. The simulation results show the effectiveness and robustness of the PSSs tuned by the proposed DEO technique on the IEEE 39 bus New England system to mitigate system damping.