• Title/Summary/Keyword: Neural network identifier(NNI)

Search Result 4, Processing Time 0.018 seconds

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
    • /
    • v.21 no.10
    • /
    • pp.65-77
    • /
    • 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.

A Study on Driving Control of an Autonomous Guided Vehicle Using Humoral Immune Algorithm(HIA) Adaptive Controller (생체면역알고리즘 적응 제어기를 이용한 AGV 주행제어에 관한 연구)

  • Lee, K.S.;Suh, J.H.;Lee, Y.J.
    • Journal of Power System Engineering
    • /
    • v.9 no.4
    • /
    • pp.194-201
    • /
    • 2005
  • In this paper, we propose an adaptive mechanism based on humoral immune algorithm and neural network identifier technique. It is also applied for 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 slove this problem, we use the neural network identifier technique for modeling the plant humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. Finally, the experimental results for control of steering and speed of AGV system illustrate the validity of the proposed control scheme. Also, these results for the proposed method show that it has better performance than other conventional controller design method such as PID controller.

  • PDF

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
    • /
    • v.10 no.12
    • /
    • pp.1137-1147
    • /
    • 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.

Adaptive Feedrate Neuro-Control for High Precision and High Speed Machining (고정밀 고속가공을 위한 신경망 이송속도 적응제어)

  • Lee, Seung-Soo;Ha, Soo-Young;Jeon, Gi-Joon
    • Journal of the Korean Institute of Telematics and Electronics S
    • /
    • v.35S no.9
    • /
    • pp.35-42
    • /
    • 1998
  • Finding a technique to achieve high machining precision and high productivity is an important issue for CNC machining. One of the solutions to meet better performance of machining is feedrate control. In this paper we present an adaptive feedrate neuro-control method for high precision and high speed machining. The adaptive neuro-control architecture consists of a neural network identifier(NNI) and an iterative learning control algorithm with inversion of the NNI. The NNI is an identifier for the nonlinear characteristics of feedrate and contour error, which is utilized in iterative learning for adaptive feedrate control with specified contour error tolerance. The proposed neuro-control method has been successfully evaluated for machining circular, corner and involute contours by computer simulations.

  • PDF