• Title/Summary/Keyword: Inverted Pendulum(IP)

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The Output Feedback Control of Inverted Pendulum Systems for The Verification of Practical Use of Linear State Observers (선형 상태 관측기의 실용화 검증을 위한 도립진자 시스템의 출력 피드백 제어 실험)

  • Lee, Jong-Yeon;Cho, Kyu-Jung;Hyun, Chang-Ho
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.2
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    • pp.192-197
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    • 2011
  • In this paper, the output feedback control of inverted pendulum systems is experimented for the practicality verification of the linear state observer. For the experiment, a pendulum system, CEM-IP-01 of Cemware Inc. is used and Lagrange equation and Jacobian linearization are adopted for the dynamic analysis of the pendulum system. In addition, the output responses of the state feedback control and the output feedback control of the pendulum system are compared before the experiment by Matlab. Finally, we directly verify the practical use of the linear state observer by recognizing and solving some real problem to control the inverted pendulum system in practice.

A Study on Stabilization Control of Inverted Pendulum System using Evolving Neural Network Controller (진화 신경회로망 제어기를 이용한 도립진자 시스템의 안정화 제어에 관한 연구)

  • 김민성;정종원;성상규;박현철;심영진;이준탁
    • Proceedings of the Korean Society of Marine Engineers Conference
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    • 2001.05a
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    • pp.243-248
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    • 2001
  • The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Thus, in this paper, an Evolving Neural Network Controller(ENNC) without Error Back Propagation(EBP) is presented. An ENNC is described simply by genetic representation using an encoding strategy for types and slope values of each active functions, biases, weights and so on. By an evolutionary programming which has three genetic operation; selection, crossover and mutation, the predetermine controller is optimally evolved by updating simultaneously the connection patterns and weights of the neural networks. The performances of the proposed ENNC(PENNC) are compared with the ones of conventional optimal controller and the conventional evolving neural network controller(CENNC) through the simulation and experimental results. And we showed that the finally optimized PENNC was very useful in the stabilization control of an IP system.

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Stabilized Control of Inverted Pendulum System by ANFIS

  • Lee, Joon-Tark;Lee, Oh-Keol;Shim, Young-Zin;Chung, Hyeng-Hwan
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.691-695
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    • 1998
  • Most of systems has nonlinearity . And also accurate modelings of these uncertain nonlinear systems are very difficult. In this paper, a fuzzy modeling technique for the stabilization control of an IP(inverted pendulum) system with nonlinearity was proposed. The fuzzy modeling was acquired on the basis of ANFIS(Adaptive Neuro Fuzzy Infernce System) which could learn using a series of input-output data pairs. Simulation results showed its superiority to the PID controller. We believe that its applicability can be extended to the other nonlinear systems.

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The Performance Verification of Optimal State Feedback Controllers via The Inverted Pendulum (도립진자 시스템을 통한 최적 상태 되먹임 제어기의 성능 검증)

  • Lee, Jong-Yeon;Lee, Bo-Ra;Hyun, Chang-Ho
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.6
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    • pp.768-773
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    • 2010
  • This paper presents the performance verification of the optimal state feedback controller via inverted pendulum systems. The proposed method generates the optimal control inputs satisfying both the constrained input and the performance specification. In addition, it reduces the steady-state error by adopting the integral control technique. In order to verify the performance of the proposed method, we apply both the proposed method and the general state feedback control to an inverted pendulum, CEM-IP-01 in the experiment.

Evolving Neural Network Controller for Stabilization of Inverted Pendulum System (도립 진자 시스템의 안정화를 위한 진화형 신경회로망 제어기)

  • Sim, Yeong-Jin;Lee, Jun-Tak
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.3
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    • pp.157-163
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    • 2000
  • In this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algoithm(RVEGA) was presented for stabilization of an Inverter Pendulum(IP) system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the determinations of input or output neuron, the deleted neuron and the activation functions types are given according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. Through the simulations, we showed that the finally acquired optimal ENNC was successfully applied to the stabilization control of an IP system.

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A Study on the Stabilization Control of IP System Using Evolving Neural Network (진화 신경망을 이용한 도립진자 시스템의 안정화 제어기에 관한 연구)

  • 박영식;이준탁;심영진
    • Journal of Advanced Marine Engineering and Technology
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    • v.25 no.2
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    • pp.383-394
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    • 2001
  • The stabilization control of inverted pendulum (IP) system is difficult because of its nonlinearity and structural unstability. In this paper, an Evolving Neural Network Controller (ENNC) without Error Back Propagation (EBP) is presented. An ENNC is described simply by genetic representation using an encoding strategy for types and slope values of each active functions, biases, weights and so on. By an evolutionary programming which has three genetic operation; selection, crossover and mutation, the predetermine controller is optimally evolved by updating simultaneously the connection patterns and weights of the neural networks. The performances of the proposed ENNC(PENNC)are compared with the one of conventional optimal controller and the conventional evolving neural network controller (CENNC) through the simulation and experimental results. And we showed that the finally optimized PENNC was very useful in the stabilization control of an IP system.

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Implementation of Evolving Neural Network Controller for Inverted Pendulum System (진화형 신경회로망에 의한 도립진자 제어시스템의 구현)

  • Shim, Young-Jin;Kim, Min-Sung;Park, Doo-Hwan;Choi, Woo-Jin;Ha, Hong-Gon;Lee, Joon-Tark
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.3013-3015
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    • 2000
  • The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions, At the same time, the fine tunings of their gain parameters are also troublesome, Thus, in this paper, an Evolving Neural Network ControlleY(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm (RVEGA) was presented for stabilization of an IP system with nonlinearity, This proposed ENNC was described by a simple genetic chromosome. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.

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Networked Control System Design Accounting for Time-Delays with Application to Inverted Pendulum

  • Park, Byung-In;Yoo, Ho-Jun;Kwon, Oh-Kyu
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1470-1473
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    • 2003
  • In this paper the networked control systems (NCS) problem is discussed where plants and controllers are distributed and interconnected by a common network. NCS is designed with LQ regulator and applied to an inverted pendulum accounting for the multiple time delays. We are to deals with a networked control system with a single controller, multiple sensors and multiple actuators. Since these parts are distributed, they are interconnected by communication networks. An NCS with LQ regulator is designed and applied to an inverted pendulum as a benchmark plant to check its performance under time delays induced by the network. Network induced delays are composed of two parts. One is the delay from controller to plant, and another is from plant to controller. They are assumed to be constant in this paper, and the plant and controller are discretized. To apply the LQ regulator the NCS model is transformed to a standard model with delayed states as state variable. And real network induced delay is measuring in TCP/IP network assuming that two delays are constant.

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Implementation of Evolving Neural Network Controller for Inverted Pendulum System (도립진자 시스템을 위한 진화형 신경회로망 제어기의 실현)

  • 심영진;김태우;최우진;이준탁
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.14 no.3
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    • pp.68-76
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    • 2000
  • The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Thus, in this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm(RVEGA) was presented for stabilization of an IP system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. And the proposed ENNC was implemented successfully on the ADA-2310 data acquisition board and the 80586 microprocessor in order to stabilize the IP system. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.

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Real-Time Networked Control System Design via Ethernet (Ethernet을 통한 실시간 네트워크 제어시스템 설계)

  • Kim, Chang-Yu;Lim, Hyun;Lee, Young-Sam;Kwo, Oh-Kyu
    • Proceedings of the KIEE Conference
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    • 2006.10c
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    • pp.136-138
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    • 2006
  • Recently, network systems are widely used in several areas, and some considerable attentions have been directed to the Networked Control System(NCS). In NCS, network-induced delays are inevitable, and they sometimes degrade the performance of networked control systems to be a source of potential instability. In this paper, We proposes a compensation method for networked control system subject to network-induced delays by using a simple method, which is based on a sort of predictive strategy. To evaluate its feasibility and effectiveness, a real-time NCS for a rotary inverted pendulum is implemented via an Ethernet. Based on the experimental results. we show that the proposed simple method can be a practical and feasible solution to NCS design.

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