• 제목/요약/키워드: Deterministic nonlinear controller

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2관절 유연한 로봇 팔에 대한 비선형 제어 (Deterministic Nonlinear Control of Two-Link Flexible Arm)

  • 한종길;손영수
    • 한국전자통신학회논문지
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    • 제4권3호
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    • pp.236-242
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    • 2009
  • 2관절 유연한 로봇 팔는 관절 축을 회전할 때 진동이 발생한다. 본 논문에서는 유연한 로봇팔의 진동 동력학은 bernoulli-Euler의 beam이론과 라그란지 방정식을 이용하여 구하였고, $\dot{D}$-2C가 skew symmetric이다는 사실을 사용하여 계산량을 줄이는 단순한 구조의 새로운 제어기를 제안한다. Lyapunov 안정도 이론은 관절을 조절하기 위한 안정한 확정적인 비선형 제어기를 성취하기 위하여 적용된다.

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신경회로망을 사용한 비선형 확률시스템 제어에 관한 연구 (A Study on a Stochastic Nonlinear System Control Using Neural Networks)

  • 석진욱;최경삼;조성원;이종수
    • 제어로봇시스템학회논문지
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    • 제6권3호
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    • pp.263-272
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    • 2000
  • In this paper we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastcic approximation method it is regarded as a stochastic recursive filter algorithm. In addition we provide a filtering and control condition for a stochastic nonlinear system called the perfect filtering condition in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable and the proposed neural controller is more efficient than the conventional LQG controller and the canonical LQ-Neural controller.

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수중운동체의 롤 제어를 위한 Deep Deterministic Policy Gradient 기반 강화학습 (Reinforcement Learning based on Deep Deterministic Policy Gradient for Roll Control of Underwater Vehicle)

  • 김수용;황연걸;문성웅
    • 한국군사과학기술학회지
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    • 제24권5호
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    • pp.558-568
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    • 2021
  • The existing underwater vehicle controller design is applied by linearizing the nonlinear dynamics model to a specific motion section. Since the linear controller has unstable control performance in a transient state, various studies have been conducted to overcome this problem. Recently, there have been studies to improve the control performance in the transient state by using reinforcement learning. Reinforcement learning can be largely divided into value-based reinforcement learning and policy-based reinforcement learning. In this paper, we propose the roll controller of underwater vehicle based on Deep Deterministic Policy Gradient(DDPG) that learns the control policy and can show stable control performance in various situations and environments. The performance of the proposed DDPG based roll controller was verified through simulation and compared with the existing PID and DQN with Normalized Advantage Functions based roll controllers.

Hyperbolic Quotient 경쟁학습 신경회로망을 사용한 비선형 확률시스템 제어에 관한 연구 (A Study on a Stochastic Nonlinear System Control Using Hyperbolic Quotient Competitive Learning Neural Networks)

  • 석진욱;조성원;최경삼
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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    • pp.346-352
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    • 1998
  • In this paper, we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastic approximation method, it is regarded as a stochastic recursive filter algorithm. In addition, we provide a filtering and control condition for a stochastic nonlinear system, called perfect filtering condition, in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence, the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable. and the proposed neural controller is more efficient than the conventional LQG controller and the canoni al LQ-Neural controller.

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비선형 견실 확정제어를 이용한 하드디스크 드라이브의 트랙추종제 (Track-Following Control of a Hard Disk Drive Actuator Using Nonlinear Robust Deterministic Control)

  • 위병열;강철구
    • 제어로봇시스템학회논문지
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    • 제6권10호
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    • pp.881-887
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    • 2000
  • There are significant nonlinearities and uncertainties in hard disk drive actuators. In particular, pivot bearing nonlinearity and repeatable run-out make track-following control difficult as track density increases. In this paper, we design a robust track-following controller using a robust deterministic control scheme in which the pivot bearing nonlinearity and repeatable run-out are considered as uncertainties. Simulation study is conducted to evaluate the control performance of the proposed control scheme.

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단일관절 유연성 로보트 팔에 대한 비선형 관측기 (Nonlinear Observer for One-Link Flexible Robot Arm)

  • 임규만;안봉만
    • 융합신호처리학회 학술대회논문집
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    • 한국신호처리시스템학회 2003년도 하계학술대회 논문집
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    • pp.183-187
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    • 2003
  • When a flexible arm is rotated by a motor about an axis through the arm's fixed end, transverse vibration may occur. The motor torque should be controlled in such a way that the motor rotates by a specified angle, while simultaneously stabilizing vibration of the flexible arm so that it is arrested at the end of rotation. In this paper, we propose nonlinear observer for one-link flexible am. Then based on the error dynamic equation between the plant dynamic equation and the nonlinear observer dynamic equation of the flexible one-link am, Lyapunov candidate function is applied to achieve a stable deterministic nonlinear feedback controller for the regulation of joint angle.

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적응제어 이론을 이용한 유연한 로봇팔의 제어 (The Control of Flexible Robot Arm using Adaptive Control Theory)

  • 한종길
    • 한국전자통신학회논문지
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    • 제7권5호
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    • pp.1139-1144
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    • 2012
  • 산업용 로봇의 하중률은 1대 10에서 1대 30이고, 3대 1의 하중률을 가지는 인간과 비교하여 매우 낮다. 다음 세대 로봇의 목표 중에 하나는 하중률이 될 것이고, 이것은 가벼운 로봇을 개발함으로 가능할 것이다. 2관절 유연한 로봇팔은 관절 축을 회전할 때 진동이 발생한다. 본 논문에서는 유연한 로봇팔의 진동 동력학은 오일러 베르누이의 보 이론과 라그랑지 방정식을 이용하여 구하였고, $\dot{D}-2C$가 skew symmetric이다는 사실을 사용하여, 계산량을 줄이는 리아프노프 안정도 이론을 이용한 단순한 구조의 새로운 제어기를 제안한다. 2링크 유연한 로봇에 대한 확정적인 적응제어 법칙을 제안하고, 시뮬레이션을 통하여 그 타당성을 보인다.

Position estimation and control of SMA actuators based on electrical resistance measurement

  • Song, Gangbing;Ma, Ning;Lee, Ho-Jun
    • Smart Structures and Systems
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    • 제3권2호
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    • pp.189-200
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    • 2007
  • As a functional material, shape memory alloy (SMA) has attracted much attention and research effort to explore its unique properties and its applications in the past few decades. Some of its properties, in particular the electrical resistance (ER) based self-sensing property of SMA, have not been fully studied. Electrical resistance of an SMA wire varies during its phase transformation. This variation is an inherent property of the SMA wire, although it is highly nonlinear with hysteresis. The relationship between the displacement and the electrical resistance of an SMA wire is deterministic and repeatable to some degree, therefore enabling the self-sensing ability of the SMA. The potential of this self-sensing ability has not received sufficient exploration so far, and even the previous studies in literature lack generality. This paper concerns the utilization of the self-sensing property of a spring-biased Nickel-Titanium (Nitinol) SMA actuator for two applications: ER feedback position control of an SMA actuator without a position sensor, and estimation of the opening of a SMA actuated valve. The use of the self-sensing property eliminates the need for a position sensor, therefore reducing the cost and size of an SMA actuator assembly. Two experimental apparatuses are fabricated to facilitate the two proposed applications, respectively. Based on open-loop testing results, the curve fitting technique is used to represent the nonlinear relationships between the displacement and the electrical resistance of the two SMA wire actuators. Using the mathematical models of the two SMA actuators, respectively, a proportional plus derivative controller is designed for control of the SMA wire actuator using only electrical resistance feedback. Consequently, the opening of the SMA actuated valve can be estimated without using an extra sensor.