• Title, Summary, Keyword: Adaptive PID controller

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Efficient Multicasting Mechanism for Mobile Computing Environment (경사 감소 학습을 이용한 적응 PID 제어기)

  • Park, Jin-Hyun;Jun, Hyang-Sig;Choi, Young-Kiu
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.1
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    • pp.289-292
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    • 2005
  • PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But it is difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose an adaptive PID controller based on a gradient descent learning. This algorithm has a simple structure like conventional PID controller and robustness to system parameters variation. To verify performances of the proposed 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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An FPGA-Based Modified Adaptive PID Controller for DC/DC Buck Converters

  • Lv, Ling;Chang, Changyuan;Zhou, Zhiqi;Yuan, Yubo
    • Journal of Power Electronics
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    • v.15 no.2
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    • pp.346-355
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    • 2015
  • On the basis of the conventional PID control algorithm, a modified adaptive PID (MA-PID) control algorithm is presented to improve the steady-state and dynamic performance of closed-loop systems. The proposed method has a straightforward structure without excessively increasing the complexity and cost. It can adaptively adjust the values of the control parameters ($K_p$, $K_i$ and $K_d$) by following a new control law. Simulation results show that the line transient response of the MA-PID is better than that of the adaptive digital PID because the differential coefficient $K_d$ is introduced to changes. In addition, experimental results based on a FPGA indicate that the MA-PID control algorithm reduces the recovery time by 62.5% in response to a 1V line transient, 50% in response to a 500mA load transient, and 23.6% in response to a steady-state deviation, when compared with the conventional PID control algorithm.

Controller Transition Management of Hybrid Position Control System for Unmanned Expedition Vehicles (무인탐사차량의 위치제어를 위한 복합제어 시스템의 제어기 전이관리)

  • Yang, Cheol-Kwan;Shim, Duk-Sun
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.10
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    • pp.969-976
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    • 2008
  • A position control problem is studied for UEV(Unmanned Expedition Vehicles), which is to follow pre-determined paths via fixed way-points. Hybrid control systems are used for position control of UEV depending on the operating condition. Speed control consists of three controllers: PID control, adaptive PI control, and neural network. Heading control consists of two controllers, PID and adaptive PID control. The controllers are selected based on the changes of road conditions. We suggest an adaptive PI control algorithm for speed control and an transition management algorithm among the controllers. The algorithm adapts the road conditions and variation of vehicle dynamical characteristics and selects a suitable controller.

Longitudinal Automatic Landing in AdaptivePID Control Law Under Wind Shear Turbulence

  • Ha, Cheol-keun;Ahn, Sang-Won
    • International Journal of Aeronautical and Space Sciences
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    • v.5 no.1
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    • pp.30-38
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    • 2004
  • This paper deals with a problem of automatic landing guidance and control ofthe longitudinal airplane motion under the wind shear turbulence. Adaptive gainscheduled PID control law is proposed in this paper. Fuzzy logic is the main part ofthe adaptive PID controller as gain scheduler. To illustrate the successful applicationof the proposed control law to the automatic landing control problem, numericalsimulation is carried out based on the longitudinal nonlinear airplane model excited bythe wind shear turbulence. The simulation results show that the automatic landingmaneuver is successfully achieved with the satisfactory performance and the gainadaptation of the control law is made adequately within the limited gains.

Convergence Progress about Applied Gain of PID Controller using Neural Networks (신경망을 이용한 PID 제어기 이득값 적용에 대한 수렴 속도 향상)

  • Son, Jun-Hyug;Seo, Bo-Hyeok
    • Proceedings of the KIEE Conference
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    • pp.89-91
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    • 2004
  • Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And in practice since it is difficult to the PID gains suitably lots of researches have been reported with respect to turning schemes of PID gains. A Neural Network-based PID control scheme is proposed, which extracts skills of human experts as PID gains. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based PID control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident. This paper goal is convergence speed progress about applied gain of PID controller using the neural networks.

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TCSC Nonlinear Adaptive Damping Controller Design Based on RBF Neural Network to Enhance Power System Stability

  • Yao, Wei;Fang, Jiakun;Zhao, Ping;Liu, Shilin;Wen, Jinyu;Wang, Shaorong
    • Journal of Electrical Engineering and Technology
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    • v.8 no.2
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    • pp.252-261
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    • 2013
  • In this paper, a nonlinear adaptive damping controller based on radial basis function neural network (RBFNN), which can infinitely approximate to nonlinear system, is proposed for thyristor controlled series capacitor (TCSC). The proposed TCSC adaptive damping controller can not only have the characteristics of the conventional PID, but adjust the parameters of PID controller online using identified Jacobian information from RBFNN. Hence, it has strong adaptability to the variation of the system operating condition. The effectiveness of the proposed controller is tested on a two-machine five-bus power system and a four-machine two-area power system under different operating conditions in comparison with the lead-lag damping controller tuned by evolutionary algorithm (EA). Simulation results show that the proposed damping controller achieves good robust performance for damping the low frequency oscillations under different operating conditions and is superior to the lead-lag damping controller tuned by EA.

Automatic Performance Tuning of PID Trajectory Tracking Controller for Robotic Systems (로봇 시스템에 대한 PID 궤적추종 제어기의 자동 성능동조)

  • 최영진
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.6
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    • pp.510-518
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    • 2004
  • The PID trajectory tracking controller for robotic systems shows performance limitation imposed by inverse dynamics according to desired trajectory. Since the equilibrium point can not be defined for the control system involving performance limitation, we define newly the quasi-equilibrium region as an alternative for equilibrium point. This analysis result of performance limitation can guide us the auto-tuning method for PID controller. Also, the quasi-equilibrium region is used as the target performance of auto-tuning PID trajectory tracking controller. The auto-tuning law is derived from the direct adaptive control scheme, based on the extended disturbance input-to-state stability and the characteristics of performance limitation. Finally, experimental results show that the target performance can be achieved by the proposed automatic tuning method.

Improved Neural Network-based Self-Tuning Fuzzy PID Controller for Sensorless Vector Controlled Induction Motor Drives (센서리스 유도전동기의 속도제어를 위한 개선된 신경회로망 기반 자기동조 퍼지 PID 제어기 설계)

  • Kim, Sang-Min;Han, Woo-Yong;Lee, Chang-Goo;Han, Hoo-Suk
    • Proceedings of the KIEE Conference
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    • pp.1165-1168
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    • 2002
  • This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for sensorless vector controlled induction motor drives. MRAS(Model Reference Adaptive System) is used for rotor speed estimation. When induction motor is continuously used long time. its electrical and mechanical parameters will change, which degrade the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. The proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using DS1102 board show the robustness of the proposed controller to parameter variations.

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Design of Model Following PID Controller Using Fuzzy Tuner (퍼지 동조기법을 이용한 기준모델 추종 PID제어기의 설계)

  • Hong, Hyug-Gi;Moon, Dong-Wook;Kim, Lark-Kyo;Nam, Moon-Hyun
    • Proceedings of the KIEE Conference
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    • pp.621-623
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    • 1999
  • In this paper, Model following PID control system, which is combined PID controller with Model Reference Adaptive Controller, is proposed. To decrease complex and much calculation which is produced in tuning process, the tuning method of parameter with fuzzy algorithm is introduced. Fuzzy algorithm isn't used in the form of controller generally much used, but tuner. Experimental results show that proposed controller has the PID parameter be tuned by fuzzy algorithm. Therefore, We expect model following PID to be operated in the real-time control.

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A Design of Stable Adaptive Composite Control Systems (안정한 적응 이중 제어시스템의 설계)

  • Zhang, Jeong-Il;Yang, Hai-Won
    • Proceedings of the KIEE Conference
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    • pp.370-372
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    • 1994
  • In this paper, a stable adaptive composite control system consisting of a PID and a fuzzy controllers is designed to control nonlinear systems. In the fuzzy controller, parameters of membership functions characterizing the linguistic terms change according to some adaptive law. Also, parameters of PID controller change according to some adaptive law. These adaptive laws are based on the Lyapunov synthesis approach. Then, it is proved that the closed-loop system using such an adaptive composite control system is globally stable in the sense that all signals involved are bounded and the tracking error converges to zero. We apply this adaptive composite control system to control a nonlinear system.

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