• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2633-2635
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• 2000

In this paper, a new DNA coding method, namely modified DNA coding method based on the biological DNA and the evolution mechanism of genetic algorithm. In order to evaluate the propose algorithms, for an example, they are applied to the fuzzy control of parallel double inverted pendulum system. Simulation result show the method is effective in finding the fuzzy control rules and is more excellent than conventional methods in control the system.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.62-66
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• 2011

This paper proposes a parallel architecture of random signal-based learning (PRSL), merged with simulated annealing (SA), to optimize the fuzzy logic controller (FLC). Random signal-based learning (RSL) finds the local optima very well, whereas it can not finds the global optimum in a very complex search space because of its serial nature. To overcome these difficulties, PRSL, which consists of serial RSL as a population, is considered. Moreover, SA is added to RSL to help the exploration. The validity of the proposed algorithm is conformed by applying it to the optimization of a FLC for the inverted pendulum.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.236-242
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• 2008

In this paper, we propose an optimized fuzzy controller based on Hierarchical Fair Competition-based Genetic Algorithms (HFCGA) for rotary inverted pendulum system. We adopt fuzzy controller to control the rotary inverted pendulum and the fuzzy rules of the fuzzy controller are designed based on the design methodology of Linear Quadratic Regulator (LQR) controller. Simple Genetic Algorithms (SGAs) is well known as optimization algorithms supporting search of a global character. There is a long list of successful usages of GAs reported in different application domains. It should be stressed, however, that GAs could still get trapped in a sub-optimal regions of the search space due to premature convergence. Accordingly the parallel genetic algorithm was developed to eliminate an effect of premature convergence. In particular, as one of diverse types of the PGA, HFCGA has emerged as an effective optimization mechanism for dealing with very large search space. We use HFCGA to optimize the parameter of the fuzzy controller. A comparative analysis between the simulation and the practical experiment demonstrates that the proposed HFCGA based fuzzy controller leads to superb performance in comparison with the conventional LQR controller as well as SGAs based fuzzy controller.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.176.5-176
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• 2001

This paper presents a fuzzy dynamic output feedback controller design method for Parallel Distributed Compensation (PDC)-type Takagi-Sugeno (T-S) model based fuzzy dynamic system with H$\infty$ performance and additional constraints on the closed pole placement. Design condition for these controller is obtained in terms of the linear matrix inequalities (LMIs). The proposed fuzzy controller satisfies the disturbance rejection performance and the desired transient response. The design method is verified by this method for an inverted pendulum with a cart using the proposed method.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.810-815
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• 2004

In this paper, we propose new parallel mechanism of a 3 dimensional biped robot whose each leg is composed of two 3-dof parallel platforms linked serially. This proposed parallel mechanism is able to move freely in the man-made environment and is applied to various fields, such as medical, welfare, and so on. And a total weight of each leg is expected to be lighter than serial linked leg. One side leg consists of a 3-dof orientation platform and 3-dof asymmetric parallel platform. The former consists of three active linear actuators and seven passive joints, and the latter of two active linear actuators, one active rotational actuator and eight passive joints. Thus, there are two kinds of parallel platforms each chain's elements and active joint's positions are different for the biped robot to move freely like a serial link without the kinematics constraints. The effectiveness and the performance of the proposed parallel mechanism and locomotion trajectory are shown in computer simulations with a 12-DOF parallel biped robot.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.185-189
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• 1998

This paper addresses analysis and design of a fuzzy model-based-controller for the control of uncertain SISO nonlinear systems. In the design procedure, we represent the nonlinear system by using a Takagi-Sugeno fuzzy model and construct a global fuzzy logic controller via parallel distributed compensation and sliding mode control. Unlike other parallel distributed controllers, this globally stable fuzzy controller is designed without finding a common positive definite matrix for a set of Lyapunov equations, and has good tracking performance. The stability analysis is conducted not for the fuzzy model but for the real underlying nonlinear system. Furthermore, the proposed method can be applied to partially known uncertain nonlinear systems. A numerical simulation is performed for the control of an inverted pendulum, to show the effectiveness and feasibility of the proposed fuzzy control method.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.31 no.2
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• pp.178-189
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• 1995

In this pater, authors derive the state - space equiation about the patallel - type inverted pendulum which is adopted as control object, and constitute the control system by $H_\infty$control theory. The modeling error is unavoidably existed by linearization error, and so on. We regard this modeling error which is determined from the identification through frequency response as unstructured model uncertainty. An augmented state - space equiation with frequency weighting function is constructed for application of the $H_\infty$theory, and the mixed sensitivity problem is considered. The weighting functions are determined in consideration of the model uncertainty and the response of system in frequency region. The $H_\infty$controller is designed by using software package for controller design. From results of response simulation, the control system designed with $H_\infty$theory guarantees low sensitivity for disturbance as well as robustness against the model uncertainties.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.181-184
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• 1996

This paper deals with the design problem of model reference adaptive controllers for MIMO plants with unknown orders. A design scheme for an adaptive control system based on CGT theorem, which has hierarchical structures derived from backstepping strategies, is proposed for MIMO plants with unknown orders but with known relative MacMillan degrees(relative degrees for SISO plants). It is also shown that all the signals in the resulting control system are bounded, and that the asymptotic tracking is achieved in the case where reference inputs are step.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.630-632
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• 1999

In this paper, we develop intelligent digitally redesigned PAM and PWM fuzzy controllers for nonlinear systems. Takagi-Sugeno fuzzy model is used to model the nonlinear systems and a continuous-time fuzzy-model-based controller is designed based on the extended parallel-distributed-compensation method. The digital controllers are determined from existing analogue controllers. The proposed method provides an accurate and effective method for digital control of continuous·time nonlinear systems and enables us to efficiently implement a digital controller via pre-determined continuous-time TS fuzzy-model-based controller. We have applied the proposed method to the balancing problem of the inverted pendulum to show the effectiveness and feasibility of the method.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.510-512
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• 1999

In this paper, we present a method for the analysis and design of fuzzy controller for nonlinear systems. In the design procedure, we represent the dynamics of nonlinear systems using a Takagi-Sugeno fuzzy model and formulate the controller rules, which shares the same fuzzy sets with the fuzzy system, using parallel distributed compensation method. Then, after the feedback gain of each local state feedback controller is obtained using the existing optimal pole-placement scheme, we construct an overall fuzzy logic controller by blending all local state feedback controller. Finally, the effectiveness and feasibility of the proposed fuzzy-model-based controller design method has been evaluated through an inverted pendulum system.