• Journal of Advanced Marine Engineering and Technology
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• 제36권8호
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• pp.1104-1110
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• 2012

도립진자 시스템은 제어이론의 다양한 기본 요소를 포함하는 제어문제를 다루는데 많이 사용되고 있다. 초기에 도립진자 시스템의 안정화 제어는 PD, PID 등의 고전적인 방법이 주로 사용되었으나 최근에는 현대제어 이론과 지능제어 기법을 이용한 방법이 주로 적용된다. 최근 비선형 제어에 종종 사용되는 퍼지제어기는 도립진자 시스템과 같이 시스템의 상태 변수가 많으면 퍼지 규칙은 급격하게 증가되어 설계가 까다롭게 된다. 또한 상태 변수를 2개씩 구분하여 퍼지제어기를 설계하면 하나의 제어시스템에 2개의 퍼지제어기를 설계해야 하는 번거로움이 발생한다. 본 논문에서는 이러한 문제점을 해결하기 위해 도립진자 시스템의 4개의 상태변수를 물리적 의미에 따라 새로운 2개의 신호로 재구성하고, 이를 퍼지 입력 변수로 사용하는 상태변수 조합 퍼지 제어기(FCSC)를 제안한다. 제안한 제어기는 컴퓨터 시뮬레이션을 통해 그 유효성을 확인한다.

• 제어로봇시스템학회논문지
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• 제5권5호
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• pp.577-584
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• 1999

In this paper, the double inverted pendulum having a single actuator is built and the controller for the system is proposed. The lower link of the target pendulum system is hinged on the plate to free for rotation in the specified range($10^{\cire}$) on the x-z plane. The upper link is connected to the lower link through a DC motor. The double inverted pendulum built can be kept upright posture by controlling the position of the upper link even though it has no actuator in lower hinge. The algorithm to control the inverted pendulum consists of a state feedback controller within a linearizable range and a fuzzy logic controller coupled with a nonlinear feedback compensator for the rest of the range. Conventional state feedback control is employed, and the fuzzy controller is responsible for generating the reference joint angle of the upper link for the nonlinear feedback compensator which drives a DC motor to generate an indirect torque to the lower joint. As a result, we can get the upright posture of the proposed pendulum system. Simulations and experiments are conducted to show the validity of the proposed controller.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(5)
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• pp.5-8
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• 2002

In this paper, we applied a PC interface and an embedded system in order to design a non-linear system and implement the PID algorithm as our control one. We used the inverted pendulum, one of the most generally used non-linear system models, to control uncertain factors in the environment. This paper showed how to use this non-linear system model to control the factors completely as well as to understand the PID algorithm. Furthermore, this paper applied and understood the embedded system.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.172-175
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• 1996

In the paper is proposed a hierarchical self-learning fuzzy controller for balancing and position control of an circular inverted pendulum system. To stabilize the pendulum at a specified position, the hierarchical fuzzy controller consists of a supervisory controller, a self-learning fuzzy controller, and a forced disturbance generator. Simulation example shows the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.207-210
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• 1997

In this paper, a hierarchical fuzzy controller for stabilization of the inverted pendulum system is proposed. The facility of this hierarchical fuzzy controller which has a swing-up control mode and a stabilization one, moves a pendulum in an initial natural stable equilibrium point and a cart in arbitrary position to an unstable equilibrium point and a center of rail. Specially, the virtual equilibrium point (.PHI.$_{VEq}$ ) which describes functionally considers the interactive dynamics between a position of cart and a angle of inverted pendulum is introduced. And comparing with the convention optimal controller, the proposed hierarchical fuzzy inference made substantially the inverted pendulum system robust and stable.e.

• International Journal of Control, Automation, and Systems
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• 제2권1호
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• pp.92-99
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• 2004

In this paper, the decoupled neural network reference compensation technique (DRCT) is applied to the control of a two degrees-of-freedom inverted pendulum mounted on an x-y table. Neural networks are used as auxiliary controllers for both the x axis and y axis of the PD controlled inverted pendulum. The DRCT method known to compensate for uncertainties at the trajectory level is used to control both the angle of a pendulum and the position of a cart simultaneously. Implementation of an on-line neural network learning algorithm has been implemented on the DSP board of the dSpace DSP system. Experimental studies have shown successful balancing of a pendulum on an x-y plane and good position control under external disturbances as well.

• 한국정밀공학회지
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• 제17권7호
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• pp.162-169
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• 2000

In this paper, we develop a parallel inverted pendulum system that has the characteristics of the strongly coupled dynamics of motion by an elastic spring, the time-variant system parameters, and inherent instability, and so on. Hence, it is possible to approximate some kinds of a physical system into this representative system and to apply the various control theories to this system in order to verie their fidelity and efficiency. For this purpose, an experimental system of the parallel inverted pendulum has been implemented, and a control scheme using the eigenstructure assignment for decoupling control is presented in comparison with the conventional LQR optimal control method. Furthermore, this system can be utilized as a testbed to develop and evaluate new control algorithms through various setups. Finally, in this paper, the results of the experiment are compared with those of numerical simulations for validation.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2008년도 추계학술대회 논문집
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• pp.395-396
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• 2008

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권2호
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• pp.109-114
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• 2002

Various inverted pendulum systems have been frequently used as a model for the performance test of the proposed control system. We first identify a rotary-type inverted pendulum system by the Euler-Lagrange method and then design a FLC (Fuzzy Logic Controller) fur the plant. FLC`s are one of useful control schemes fur plants having difficulties in deriving mathematical models or having performance limitations with conventional linear control schemes. Many FLC`s imitate the concept of conventional PD (Proportional-Derivative) or PI (Proportional-Integral) controller. That is, the error e and the change-of-error are used as antecedent variables and the control input u the change of control input Au is used as its consequent variable for FLC`s. In this paper we design a simple-structured FLC for the rotary inverted pendulum system. We also perform some computer simulations to examine the tracking performance of the closed-loop system.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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• pp.45-49
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• 1997

In this paper, we controlled a Rotary Inverted Pendulum System using Neuro-Fuzzy Controller(NFC). The inverted pendulum system is widely used as a typical example of an unstable nonlinear control system which is difficult to control. Fuzzy theory have been because membership functions and rules of a fuzzy controller are often given by experts or a fuzzy logic control system. This controller is a feedforward multilayered network which integrates the basic elements and functions of a tradtional fuzzy logic controller into a connectionist structure which has distributed learning abilities. Such NFC can be constructed from training examples by learning rule, and the structure can be trained to develop fuzzy logic rules and find optimal input/output membership functions. Using this controller, we presented the results that controlled a Rotary Inverted Pendulum System and the associated algorithms.