• Title, Summary, Keyword: Adaptive PID controller

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An Adaptive Speed Control of a Diesel Engine by means of a Model Matching method and the Nominal Model Tracking Method (모델 매칭법과 규범모델 추종방식에 의한 디젤기관의 적응속도제어)

  • 유희한;소명옥;박재식
    • Journal of the Korean Society of Marine Engineering
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    • v.27 no.5
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    • pp.609-616
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    • 2003
  • The purpose of this study is to design the adaptive speed control system of a marine diesel engine by combining the Model Matching Method and the Nominal Model Tracking Method. The authors proposed already a new method to determine efficiently the PID control Parameters by the Model Matching Method. typically taking a marine diesel engine as a non-oscillatory second-order system. But. actually it is very difficult to find out the exact model of a diesel engine. Therefore, when diesel engine model and actual diesel engine are unmatched as an another approach to promote the speed control characteristics of a marine diesel engine, this paper Proposes a Model Reference Adaptive Speed Control system of a diesel engine, in which PID control system for the model of a diesel engine is adopted as the nominal model and Fuzzy controller and derivative operator are adopted as the adaptive controller.

Analysis and Design of a Separate Sampling Adaptive PID Algorithm for Digital DC-DC Converters

  • Chang, Changyuan;Zhao, Xin;Xu, Chunxue;Li, Yuanye;Wu, Cheng'en
    • Journal of Power Electronics
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    • v.16 no.6
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    • pp.2212-2220
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    • 2016
  • Based on the conventional PID algorithm and the adaptive PID (AD-PID) algorithm, a separate sampling adaptive PID (SSA-PID) algorithm is proposed to improve the transient response of digitally controlled DC-DC converters. The SSA-PID algorithm, which can be divided into an oversampled adaptive P (AD-P) control and an adaptive ID (AD-ID) control, adopts a higher sampling frequency for AD-P control and a conventional sampling frequency for AD-ID control. In addition, it can also adaptively adjust the PID parameters (i.e. $K_p$, $K_i$ and $K_d$) based on the system state. Simulation results show that the proposed algorithm has better line transient and load transient responses than the conventional PID and AD-PID algorithms. Compared with the conventional PID and AD-PID algorithms, the experimental results based on a FPGA indicate that the recovery time of the SSA-PID algorithm is reduced by 80% and 67% separately, and that overshoot is decreased by 33% and 12% for a 700mA load step. Moreover, the SSA-PID algorithm can achieve zero overshoot during startup.

Position Control of Shape Memory Alloy Actuators Using Self Tuning Fuzzy PID Controller

  • Ahn Kyoung-Kwan;Nguyen Bao Kha
    • International Journal of Control, Automation, and Systems
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    • v.4 no.6
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    • pp.756-762
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    • 2006
  • Shape Memory Alloy(SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications such as aeronautics, surgical tools, robotics and so on. Although the conventional PID controller can be used with slow response systems, there has been limited success in precise motion control of SMA actuators, since the systems are disturbed by unknown factors beside their inherent nonlinear hysteresis and changes in the surrounding environment of the systems. This paper presents a new development of a SMA position control system by using a self-tuning fuzzy PID controller. This control algorithm is used by tuning the parameters of the PID controller thereby integrating fuzzy inference and producing a fuzzy adaptive PID controller, which can then be used to improve the control performance of nonlinear systems. The experimental results of position control of SMA actuators using conventional and self-tuning fuzzy PID controllers are both included in this paper.

A Study on Adaptive Control of AGV using Immune Algorithm (면역알고리즘을 이용한 AGV의 적응제어에 관한 연구)

  • 이영진;최성욱;손주한;이진우;조현철;이권순
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • pp.56-63
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    • 2000
  • Abstract - In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. 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 adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. 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 immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.

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A Study on Implementation of Immune Algorithm Adaptive Controller for AGV Driving Control (AGV의 주행 제어를 위한 면역 알고리즘 적응 제어기 실현에 관한 연구)

  • 이영진;이진우;손주한;이권순
    • Journal of Korean Port Research
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    • v.14 no.2
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    • pp.187-197
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    • 2000
  • In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied to the driving control of the autonomous guided vehicle(AGV). When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged by the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined through this off-line manner, these parameters are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted more accurately through the on-line fine tuning. The experiment for the control of steering and speed of AGV is performed. The results show that the proposed controller provides better performances than other conventional controllers.

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Tension Control Using Adaptive PID Controller in the Two-Drum Winder Web Transport System (Two-Drum Winder 권취 공정 시스템에서의 적용 PID 제어기를 이용한 장력제어)

  • Park, Seung-Gyu;Lee, Dong-Bin;Yim, Hwa-Yeong
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.9
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    • pp.813-821
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    • 2000
  • In this paper, we developed modeling of tension and speed dynamics for a two-drum winder in a three span continuous web transport system which had not been previously. Dynamic modeling of the time-varying nonlinear system was derived by considering the effect of the radii and mass moment of inertia in the unwinder and the two-drum winder through winding up the web. After linearizing it, we designed with a variable-gain a PID controller for tension control and a PI controller for speed. Simulation is carried out with the variation of radii and moment of inertia at high speed for the proposed tension control system with the two-drum winder and the variavle-gain a PID controller. Results show good performance of tension control during the speed change speed at a start-up and stop.

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Design of a Self-tuning Controller with a PID Structure Using Neural Network (신경회로망을 이용한 PID구조를 갖는 자기동조제어기의 설계)

  • Cho, Won-Chul;Jeong, In-Gab;Shim, Tae-Eun
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.39 no.6
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    • pp.1-8
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    • 2002
  • This paper presents a generalized minimum-variance self-tuning controller with a PID structure using neural network which adapts to the changing parameters of the nonlinear system with nonminimum phase behavior and time delays. 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 nonlinear nonminimum phase system with time delays and changed system parameter after a constant time. The proposed method compared with direct adaptive controller using neural network.

Automatic Landing in Adaptive Gain Scheduled PID Control Law

  • Ha, Cheol-Keun;Ahn, Sang-Won
    • 제어로봇시스템학회:학술대회논문집
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    • pp.2345-2348
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    • 2003
  • This paper deals with a problem of automatic landing guidance and control system design. The auto-landing control system for the longitudinal motion is designed in the classical PID controller. The controller gains are properly adapted to variation of the performance using fuzzy logic as a gain scheduler for the PID gains. This control logic is applied to the problem of the automatic landing control system design. From the numerical simulation using the 6DOF nonlinear model of the associated airplane, it is shown that the auto-landing maneuver is successfully achieved from the start of the flight conditions: 1500 ft altitude, 250 ft/sec airspeed and zero flight path angle.

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Design of a smart MEMS accelerometer using nonlinear control principles

  • Hassani, Faezeh Arab;Payam, Amir Farrokh;Fathipour, Morteza
    • Smart Structures and Systems
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    • v.6 no.1
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    • pp.1-16
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    • 2010
  • This paper presents a novel smart MEMS accelerometer which employs a hybrid control algorithm and an estimator. This scheme is realized by adding a sliding-mode controller to a conventional PID closed loop system to achieve higher stability and higher dynamic range and to prevent pull-in phenomena by preventing finger displacement from passing a maximum preset value as well as adding an adaptive nonlinear observer to a conventional PID closed loop system. This estimator is used for online estimation of the parameter variations for MEMS accelerometers and gives the capability of self testing to the system. The analysis of convergence and resolution show that while the proposed control scheme satisfies these criteria it also keeps resolution performance better than what is normally obtained in conventional PID controllers. The performance of the proposed hybrid controller investigated here is validated by computer simulation.

Analysis and Implementation of ANFIS-based Rotor Position Controller for BLDC Motors

  • Navaneethakkannan, C.;Sudha, M.
    • Journal of Power Electronics
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    • v.16 no.2
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    • pp.564-571
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    • 2016
  • This study proposes an adaptive neuro-fuzzy inference system (ANFIS)-based rotor position controller for brushless direct current (BLDC) motors to improve the control performance of the drive under transient and steady-state conditions. The dynamic response of a BLDC motor to the proposed ANFIS controller is considered as standard reference input. The effectiveness of the proposed controller is compared with that of the proportional integral derivative (PID) controller and fuzzy PID controller. The proposed controller solves the problem of nonlinearities and uncertainties caused by the reference input changes of BLDC motors and guarantees a fast and accurate dynamic response with an outstanding steady-state performance. Furthermore, the ANFIS controller provides low torque ripples and high starting torque. The detailed study includes a MATLAB-based simulation and an experimental prototype to illustrate the feasibility of the proposed topology.