• 한국생산제조학회지
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• 제22권5호
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• pp.837-844
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• 2013

This study performs erection of a pendulum hanging at a free end of an arm by rotating the arm to the upright position. A mathematical model of a rotary inverted pendulum system (RIPS) is derived. A brain emotional learning based intelligent controller (BELBIC) is designed and used as a controller for swinging up and balancing the pendulum of the RIPS. In simulations performed in the study, a pendulum is initially inclined at $45^{\circ}$ with respect to the upright position. A simulation is also performed for evaluating the adaptiveness of the designed BELBIC in the case of system variation. In addition, a simulation is performed for evaluating the robustness of the designed BELBIC against a disturbance in the control input.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.104-106
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• 2007

In this paper, we propose an approach to design of optimized Cascade controller for Rotary Inverted Pendulum system using Hierarchical Fair Competition-based Genetic Algorithm(HFCGA). GAs may get trapped in a sub-optimal region of the search space thus becoming unable to find better quality solutions, especially for very large search space. The Parallel Genetic Algorithms(PGA) are developed with the aid of global search and retard premature convergence. HFCGA is a kind of multi-populations of PGA. In this paper, we design optimized Cascade controller by HFCGA for Rotary Inverted Pendulum system that is nonlinear and unstable. Cascade controller comprise two feedback loop, parameters of controller optimize using HFCGA. Then designed controller evaluate by apply to the real plant.

• 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.

• 한국지능시스템학회논문지
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• 제19권3호
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• pp.329-336
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• 2009

본 논문은 회전형 역 진자 시스템(Rotary Inverted Pendulum System : RIPS)의 제어를 위한 Fuzzy cascade 제어구조를 제안하고 병렬유전자 알고리즘의 하나인 계층적 공정 경쟁 기반 유전자 알고리즘(Hierarchical Fair Competition-based Genetic Algorithms : HFCGA)을 이용한 최적화 방법을 제시한다. 회전형 역 진자 시스템은 Rotating arm의 회전을 통해 Pendulum의 각도를 제어하는 시스템으로써 제어 목적은 Rotating arm을 원하는 위치에 오게 하고 진자를 수직 위치의 불안정 평형 점에 위치하도록 하는 것이다. 본 논문에서는 회전형 역 진자 시스템의 제어를 위해 두개의 Fuzzy 제어기로 구성된 Fuzzy cascade 제어 구조를 설계하고, HFCGA를 이용하여 설계된 제어기의 파라미터를 최적화한다. 시뮬레이션 및 실험에서 SGA와 HFCGA의 성능비교를 통해 HFCGA의 우수성을 보이고, LQR 및 PD cascade 제어기와 제안된 Fuzzy cascade 제어기의 성능 비교를 통하여 제안된 방법의 우수성을 보인다.

• 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.

• 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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.901-904
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• 1998

In this paper, we describes PID-neural network controller for the rotary inverted pendulum. PID control is applied to many fields but has some problems in nonlinear system due to a variation of parameter. So, we should desing the controller which is adjusted PI parameters by the neural network which is learned by backpropagation algorithm. And we show that on-line control is possible through the PID-neural network controller. The angle of the pendulum is controlled and then the position of the rotating arm is also controlled to maintain with in the set point. Measurement of the pendulum angle is obtained using a potentionmeter. The objective of the experiment is to design a PID-neural network control system that positions the arm as well as maintains the ivnerted pendulum vertical. Finally, we describe the actual experiment system and confirm the experimental results.

• 전기학회논문지
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• 제60권2호
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• pp.407-415
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• 2011

In this study, we propose the design of optimized fuzzy controller for the rotary inverted pendulum system by using differential evolution algorithm. The structure of the differential evolution algorithm has a simple structure and its convergence to optimal values is superb in comparison to other optimization algorithms. Also the differential evolution algorithm is easier to use because it have simpler mathematical operators and have much less computational time when compared with other optimization algorithms. The rotary inverted pendulum system is nonlinear and has a unstable motion. The objective is to control the position of the rotating arm and to make the pendulum to maintain the unstable equilibrium point at vertical position. The output performance of the proposed fuzzy controller is considered from the viewpoint of performance criteria such as overshoot, steady-state error, and settling time through simulation and practical experiment. From the result of both simulation and practical experiment, we evaluate and analyze the performance of the proposed optimal fuzzy controller from the comparison between PGAs and differential evolution algorithms. Also we show the superiority of the output performance as well as the characteristic of differential evolution algorithm.

• 한국정보전자통신기술학회논문지
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• 제16권6호
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• pp.400-405
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• 2023

현재 도립진자는 많은 분야에서 연구 중이며 미사일, 로켓, 등의 자세 제어와 2족 보행 로봇 등에 응용되고 있다. 본 연구에서는 256펄스의 로터리 엔코더와 DC 모터를 이용한 회전형 도립진자(Rotary Inverted Pendulum)를 구성하여 회전형 역 진자의 수직 자세 제어를 연구하였다. 비선형 시스템의 경우 복잡한 알고리즘과 제어기가 필요하지만 고전적이며 비교적 간단한 PID(Proportional Integral Derivation)알고리즘을 이용한 제어 방법을 회전형 도립진자 시스템에 적용하였으며 간단하지만 원하는 성능을 높이는 방안을 연구하였다. 본 연구에서 사용된 회전형 도립진자 시스템은 비선형적이고 불안정한 시스템으로 선형화된 모델링에서 마이크로칩 사의 dsPIC30F4013 임베디드 프로세서를 이용한 PID 제어기를 설계 및 구현하였다. 보통 PID 제어기는 하나 혹은 두 가지 이상을 조합하여 설계하며 우수한 제어 성능에 비해 구조가 간단하며 제어 이득 조정이 다른 제어기들에 비해 비교적 쉽다는 장점이 있다. 본 연구에서는 시스템의 물리적 구조를 수학적 방법으로 분석하고 모델링을 통한 회전형 도립진자의 수직 균형을 위한 제어를 실현하였다. 또한 회전형 역 진자를 이용하여 PID 제어기로 제어가 가능한지 시뮬레이션과 실험을 통하여 그 타당성을 검증하였다.

• 전기학회논문지P
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• 제58권2호
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• pp.130-135
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• 2009

In recent years, researches on rotary inverted pendulum control systems have been significantly focused due their highly nonlinear dynamics and complicated geometric structures. This paper presents a novel control approach for such systems by means of similarity transformation theory. At first, we represent nonlinear system dynamics to the controllability-formed state space model including a time-varying parameter vector. We establish the state-feedback control configuration based on the transformed model and derive an adaptive control law for adjusting desired characteristic equation. Numerical analysis is achieved to evaluate our control method and demonstrate its superiority by comparing it to the traditional control strategy. Furthermore, real-time control experiment is carried out to test its practical reliability.