• Title, Summary, Keyword: Adaptive PID controller

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Nonlinear Adaptive PID Controller based on a Cell-mediated Immune Response and a Gradient Descent Learning (세포성 면역 반응과 경사감소학습에 의한 비선형 적응 PID 제어기)

  • Park Jin-Hyun;Lee Tae-Hwan;Choi Young-Kiu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.1
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    • pp.88-95
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    • 2006
  • PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They we difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

Digital adaptive control of electro hydraulic velocity control system (전기.유압 속도제어 시스템의 디지탈 적용제어에 관한 연구)

  • 장효환;전윤식
    • 제어로봇시스템학회:학술대회논문집
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    • pp.321-325
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    • 1988
  • The objective of this study is to develop a microcomputer-based adaptive controller for an electro hydraulic velocity control system subjected to the variation of system parameters. The step response performance of the system with the adaptive controller is investigated for the variation of the external load torque, the moment of inertia and the reference inputs, and compared with that obtained by PID controller whose gains are constant. The experimental results show that this proposed model reference adaptive controller is robust to the variation of system parameters and yield much better control performance compared with the conventionel PID controller.

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PID and Adaptive Controllers for a Transportation Mobile Robot with Fork-Type Lifter

  • Nguyen, Van Vui;Tran, Huu Luat;Kim, Yong-Tae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.3
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    • pp.216-223
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    • 2016
  • This paper proposes a new controller design method for a fork-type lifter (FTL) of a transportation mobile robot. The transportation robot needs to pick up a package from a stack on a storage shelf and move on by a planned path in a logistics center environment. The position of the storage shelf is recognized by reading a QR code on the floor, and using this position, the robot can move to reach the storage shelf and pick up the package. PID controllers and an adaptive controller are designed to control the velocity of two wheels and the position of the FTL. An adaptive controller for the lifter is designed to elevate up and down on a slideway to the correct height position of the package on the stack of the storage shelf. The simulation results show that the PID controllers can respond smoothly to the desired angular velocity and the adaptive controller can adapt quickly and correctly to the desired height.

A controller Design using Immune Feedback Mechanism (인체 면역 피드백 메카니즘을 활용한 제어기 설계)

  • Park, Jin-Hyun;Kim, Hyun-Duck;Choi, Young-Kiu
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.2
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    • pp.701-704
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    • 2005
  • PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They are difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

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Nonlinear PID Controller with Neural Network based Compensator (신경회로망 보상기를 갖는 비선형 PID 제어기)

  • Lee, Chang-Gu
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.5
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    • pp.225-234
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    • 2000
  • In this paper, we present an nonlinear PID controller with network based compensator which consists of a conventional PID controller that controls the linear components and neuro-compensator that controls the output errors and nonlinear components. This controller is based on the Harris's concept where he explained that the adaptive controller consists of the PID control term and the disturbance compensating term. The resulting controller's architecture is also found to be very similar to that of Wang's controller. This controller adds a self-tuning ability to the existing PID controller without replacing it by compensating the output errors through the neuro-compensator. Various simulations and comparative studies have proven that the proposed nonlinear PID controller produces superior results to other existing PID controllers. When applied to an actual magnetic levitation system which is known to be very nonlinear, it has also produced an excellent results.

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Application of a PID Feedback Control Algorithm for Adaptive Queue Management to Support TCP Congestion Control

  • Ryu, Seungwan;Rump, Christopher M.
    • Journal of Communications and Networks
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    • v.6 no.2
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    • pp.133-146
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    • 2004
  • Recently, many active queue management (AQM) algorithms have been proposed to address the performance degradation. of end-to-end congestion control under tail-drop (TD) queue management at Internet routers. However, these AQM algorithms show performance improvement only for limited network environments, and are insensitive to dynamically changing network situations. In this paper, we propose an adaptive queue management algorithm, called PID-controller, that uses proportional-integral-derivative (PID) feedback control to remedy these weak-Dalles of existing AQM proposals. The PID-controller is able to detect and control congestion adaptively and proactively to dynamically changing network environments using incipient as well as current congestion indications. A simulation study over a wide range of IP traffic conditions shows that PID-controller outperforms other AQM algorithms such as Random Early Detection (RED) [3] and Proportional-Integral (PI) controller [9] in terms of queue length dynamics, packet loss rates, and link utilization.

A Design of Adaptive Controller based on Immune System (면역시스템에 기반한 적응제어기 설계에 관한 연구)

  • Lee Kwon Soon;Lee Young Jin
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.12
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    • pp.1137-1147
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    • 2004
  • In this paper, we proposed two types of adaptive control mechanism which is named HIA(Humoral Immune Algorithm) PID and CMIA(Cell-Mediated Immune Algorithm) controller based on biological immune system under engineering point of view. The HIA PID which has real time control scheme is focused on the humoral immunity and the latter which has the self-tuning mechanism is focused on the T-cell regulated immune response. To verify the performance of the proposed controller, some experiments for the control of AGV which is used for the port automation to carry container without human are performed. The experimental results for the control of steering and speed of an AGV system illustrate the effectiveness of the proposed control scheme. Moreover, in that results, proposed controllers have better performance than other conventional PID controller and intelligent control method which is the NN(neural network) PID controller.

A Design Method For An On-line Adaptive Neural Networks Based Intelligent Controller (온라인 적응 신경회로망을 이용한 지능형 제어기 설계방법)

  • Kim, I.J.;Gu, S.W.;Choi, J.Y.;Choy, I.;Kim, K.B.
    • Proceedings of the KIEE Conference
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    • pp.1341-1343
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    • 1996
  • This paper presents a design method for an on-line adaptive neural networks based intelligent controller. The proposed neural controller, assuming PID controller is initially presented, learns the equivalent behaviors of the existing PID controller initially and switches to take over the PID control system. Then, it executes on-line adaptation via evaluating its performance and minimizing user defined cost function constantly so that the optimal control can be achieved. The PID controller and the proposed neural controller are investigated and compared in computer simulation.

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A Study on Driving Control of an Autonomous Guided Vehicle using Humoral Immune Algorithm Adaptive PID Controller based on Neural Network Identifier Technique (신경회로망 동정기법에 기초한 HIA 적응 PID 제어기를 이용한 AGV의 주행제어에 관한 연구)

  • Lee Young Jin;Suh Jin Ho;Lee Kwon Soon
    • Journal of the Korean Society for Precision Engineering
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    • v.21 no.10
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    • pp.65-77
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    • 2004
  • In this paper, we propose an adaptive mechanism based on immune algorithm and neural network identifier technique. It is also applied fur an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To solve this problem, we use the neural network identifier (NNI) technique fur modeling the plant and humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using an immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. Finally, the simulation and experimental result fur the control of steering and speed of AGV system illustrate the validity of the proposed control scheme. These results for the proposed method also show that it has better performance than other conventional controller design methods.

Design of an Adaptive Neuro-Fuzzy Inference Precompensator for Load Frequency Control of Two-Area Power Systems (2지역 전력계통의 부하주파수 제어를 위한 적응 뉴로 퍼지추론 보상기 설계)

  • 정형환;정문규;한길만
    • Journal of the Korean Society of Marine Engineering
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    • v.24 no.2
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    • pp.72-81
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    • 2000
  • In this paper, we design an adaptive neuro-fuzzy inference system(ANFIS) precompensator for load frequency control of 2-area power systems. While proportional integral derivative (PID) controllers are used in power systems, they may have some problems because of high nonlinearities of the power systems. So, a neuro-fuzzy-based precompensation scheme is incorporated with a convectional PID controller to obtain robustness to the nonlinearities. The proposed precompensation technique can be easily implemented by adding a precompensator to an existing PID controller. The applied neruo-fuzzy inference system precompensator uses a hybrid learning algorithm. This algorithm is to use both a gradient descent method to optimize the premise parameters and a least squares method to solve for the consequent parameters. Simulation results show that the proposed control technique is superior to a conventional Ziegler-Nichols PID controller in dynamic responses about load disturbances.

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