• Title/Summary/Keyword: direct controller

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Direct Controller for Nonlinear System Using a Neural Network

  • Bae, Cheol-Soo;Park, Young-Cheol;Nam, Kee-Hwan;Kang, Yong-Seok;Kim, Tae-Woo;Hwang, Suen-Ki;Kim, Hyon-Yul;Kim, Moon-Hwan
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.5 no.1
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    • pp.7-12
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    • 2012
  • In this paper, a direct controller for nonlinear plants using a neural network is presented. The controller is composed of an approximate controller and a neural network auxiliary controller. The approximate controller gives the rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not put too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network is trained and the system has a stable performance for the inputs it has been trained for. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system.

New Fuzzy Controller for Speed Control of Induction Motor Drive (유도전동기 드라이브의 속도제어를 위한 새로운 퍼지제어기)

  • Lee, Jung-Chul;Lee, Hong-Gyun;Jung, Tack-Gi;Chung, Dong-Hwa
    • Proceedings of the KIEE Conference
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    • 2002.11d
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    • pp.224-227
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    • 2002
  • This paper is proposed new fuzzy controller for speed control of induction motor drive. New fuzzy controller take out appropriate amounts of accumulated control input according to fuzzily described situations in addition to the incremental control input calculated by conventional direct fuzzy controller. The structures of the proposed controller is motivated by the problems of direct fuzzy controller. Proposed controller fuzzily clear out integrated quantifies according to situation. This paper attempts to provide a thorough comparative insight into the behavior of induction motor drive with direct and new fuzzy speed controller. The validity of the comparative results is confirmed by simulation results for induction motor drive system.

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Force control of the direct-drive robot using learning controller (학습제어기를 이용한 직접구동형 로봇의 힘제어)

  • Hwang, Yeong-Yeun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.21 no.11
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    • pp.1819-1826
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    • 1997
  • Direct-drive robots are suitable to the position and force control with high accuracy, but it is difficult to design a controller because of the system's nonlinearity and link-interactions. This paper is concerned with the study of the force control of direct-drive robots. The proposed algorithm consists of feedback controllers and a neural network. After the completion of learning, the output of feedback controller is nearly equal to zero, and the neural network controller plays an important role in the control system. Therefore, the optimum retuning of parameters of feedback controllers is unnecessary. In other words, the proposed algorithm does not require any knowledge of the controlled system in advance. The effectiveness of the proposed algorithm is demonstrated by the experiment on the force control of the parallelogram link-type direct-drive robot.

Direct Adaptive Control for Trajectory Tracking Control of a Pneumatic Cylinder (공기압 실린더의 궤적 추적 제어를 위한 직접 적응제어)

  • Lee, Su-Han;Jang, Chang-Hun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.24 no.12
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    • pp.2926-2934
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    • 2000
  • This study presents a direct adaptive controller which is derived by using Lyapunovs direct methods for trajectory tracking control of a pneumatic cylinder. The structure of the controller is very simple and computationally efficient because it does not use either the dynamic model or the parameter values of the pneumatic system. The bounded stability of the system is shown in the presence of the bounded unmodeled dynamics. The bounded size of tracking errors can be made arbitrarily small without giving andy influences on either input or output variables. The trajectory tracking performance and the stability of the control system is verified experimentally. The results of the experiments show that the proposed controller tracks the given trajectories, sine function and cycloidal function trajectories, more accurately than PD controller does, and it stabilizes the system and adaptive variables.

Design of a direct multivariable neuro-generalised minimum variance self-tuning controller (직접 다변수 뉴로 일반화 최소분산 자기동조 제어기의 설계)

  • 조원철;이인수
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.41 no.4
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    • pp.21-28
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    • 2004
  • This paper presents a direct multivariable self-tuning controller using neural network which adapts to the changing parameters of the higher order multivariable nonlinear system with nonminimum phase behavior, mutual interactions and time delays. The nonlinearities are assumed to be globally bounded, and a multivariable nonlinear system is divided linear part and nonlinear part. The neural network is used to estimate the controller parameters, and the control output is obtained through estimated controller parameter. In order to demonstrate the effectiveness of the proposed algorithm the computer simulation is done to adapt the multivariable nonlinear nonminimm phase system with time delays and changed system parameter after a constant time. The proposed method compared with direct multivariable adaptive controller using neural network.

A Feasible Approach for the Unified PID Position Controller Including Zero-Phase Error Tracking Performance for Direct Drive Rotation Motor

  • Kim, Joohn-Sheok
    • Journal of Power Electronics
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    • v.9 no.1
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    • pp.74-84
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    • 2009
  • The design and implementation of a high performance PID (Proportional Integral & Differential) style controller with zero-phase error tracking property is considered in this article. Unlike a ball screw driven system, the controller in a direct drive system should provide a high level of tracking performance while avoiding the problems due to the absence of the gear system. The stiff mechanical element in a direct drive system allows high precise positioning capability, but relatively high tracking ability with minimal position error is required. In this work, a feasible position controller named 'Unified PID controller' is presented. It will be shown that the function of the closed position loop can be designed into unity gain system in continuous time domain to provide minimal position error. The focus of this work is in two areas. First, easy gain tunable PID position controller without speed control loop is designed in order to construct feasible high performance drive system. Second, a simple but powerful zero phase error tracking strategy using the pre-designed function of the main control loop is presented for minimal tracking error in all operating conditions. Experimental results with a s-curve based position pattern commonly used in industrial field demonstrate the feasibility and effective performance of the approach.

Design of the Combined Direct and Indirect Adaptive Neural Controller Using Fuzzy Rule (퍼지규칙에 의한 직.간접 혼합 신경망 적응제어시스템의 설계)

  • 이순영;장순용
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.3
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    • pp.603-610
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    • 2000
  • In this paper, the direct and indirect adaptive controller are combined based on the Lyapunov synthesis approach. The Proposed controller is constructed from RBF Neural Network and weighting parameters are adjusted on-line according to some adaptation law. In this scheme, fuzzy IF-THEN rules are used to decide the combined weighting factor. In the results, proposed controller has the main advantages of both the direct adaptive controller and the indirect adaptive controller. The effectiveness of the proposed control scheme is demonstrated through simulation results of control for one-link rigid robotics manipulator.

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Robust Trajectory Control of Direct Drive Manipulator based on combining H$\infty$ Controller and Computed Torque Method (구동력 계산법 및 H$\infty$제어를 병용한 직접구동방식 머니퓰레이터의 퀘적제어)

  • Kim, C.K.;Kang, B.S.;Kwak, Y.K.
    • Journal of the Korean Society for Precision Engineering
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    • v.13 no.10
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    • pp.123-129
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    • 1996
  • Computed torque method has been used for precise trajectory control of the robotic system that involves nonlinear dynamics. It is hard to know exact values of robot system parameters, and the robot arm receives umpredictable interference from the working environment. These disturbances, especially in a direct drive robot, are directly transmitted to actuating motor without reduction. Modelling error and distrubance can cause significant errors in a trajectory tracking problem. In this paper, we propose a new controller that $H_{\infty}$controller is conbined to robot system linearized by computed torque. Simula- tions are made for comparing the performance of the proposed controller with that of a nonlinear $H_{\infty}$ controller proposed by Chen and also computed torque method.hod.

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A study on the direct pole-placement PID self-tuner (직접 극배치 PID 자기 동조기에 관한 연구)

  • 이진원;송형근;윤인섭
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10a
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    • pp.452-456
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    • 1988
  • A PID controller must need not only good servo response but also little operation of a control valve. We suggest a direct pole-placement PID self-tuning algorithm using the structure of derivative-of-output controller and Bezout identity. This algorithm can much reduce the change of output of controller and well follow the desired trajectory.

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Controller Parameters Design of Direct Drive Servo Valve Using Genetic Algorithm and Complex Method (유전자 알고리즘과 콤플렉스법에 의한 직접구동형 서보밸브의 제어기 상수값 설계)

  • Lee, Seong Rae
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.37 no.4
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    • pp.475-481
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    • 2013
  • The control system of a direct drive servo valve is a nonlinear system, and the flow force effect on the spool motion is significant and dependent on the load pressure. To satisfy the control system design requirements, the optimal parameters of the lead-lag controller and the derivative feedback controller are searched for using a genetic algorithm and a complex constrained direct search type method. The obtained controller parameters successfully perform their role to satisfy the control system design requirements.