Boonchana Purahong

King Mongkut's Institute of Technology Ladkrabang, Krung Thep, Bangkok, Thailand

Are you Boonchana Purahong?

Claim your profile

Publications (8)0 Total impact

  • Boonchana Purahong
    [Show abstract] [Hide abstract]
    ABSTRACT: Fuzzy P<sup>2</sup>ID is the controlling algorithm, which derived from the combination of the fuzzy PD and fuzzy PI in order to reduce the Rise-time and Overshoot. The recent development of SS fuzzy P<sup>2</sup>ID is based on the original algorithm of fuzzy P<sup>2</sup>ID, in which the SS fuzzy P<sup>2</sup>ID is the algorithm developed in order to correct the crisp signal problem of the original algorithm. This report describes the application of the soft-switching fuzzy P<sup>2</sup>ID controller to be used as the navigation system of the wheel chair-propel robots. The results of using both original and recent developed algorithms were compared by using the Simulation under the same parameter to both algorithms, as a result the satisfactory result of the recent development algorithm was found.
    No preview · Conference Paper · Jul 2008
  • Boonchana Purahong
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper shows the development of controlling system of snake robot's movement in order to make the Serpentine movement more effective when it goes into narrow path. Snake robot consists of many servo motors serially linked to each other and has its length like a medium-sized snake's. This controlling system measures the side lengths, which are inputs, from the sensors attached on the head of the robot. The robot then processes the inputs and uses them to control the width of crawling in order to perform the crawling at the best speed on limited path. The ways to control it to move forward, backward, left, right, and algorithms used to control are already explained. The result of this experiment, which is an achievement of movement in different locations, shows that it works effectively.
    No preview · Conference Paper · Nov 2007
  • Boonchana Purahong · Tuanjai Archevapanich
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper shows the result of T. Takagi and M. Sugeno (1989) experiment and shows how to design and status of the robot in face emotion. We implement with the a vacuum robot, and we will show how to setup the system into hardware, which consists of fuzzy emotion generator that processes the inputs from the heat sensors of the main board and the battery indicator to the outputs for using in visualization step which is a displaying board. Visualization has been developed to show the robot's emotion through the face completely by limited hardware. The result of the experiment of showing the emotion through the face of the robot works naturally.
    No preview · Article · Jan 2007
  • [Show abstract] [Hide abstract]
    ABSTRACT: The issue of this paper is to show working status of a robot in the form of face emotion which shows the creation of fuzzy emotion generator. This fuzzy emotion generator uses Takagi-Sugeno (TS) fuzzy system to process input data from heat sensors on CPU and batter indicator into emotional output of a robot for visualization. The visualization system that was built can completely show robot's emotions. The experimental results show the advantages of the application of fuzzy system in presenting the output and its advantages are natural continuation which is the result of successful implementation
    No preview · Conference Paper · Nov 2006
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper shows how to design the hybrid control system based on hydra control structure by introducing two design strategies which are as following: double head and line up. These two strategies use genetic algorithms to improve parameters in control system and they also situate the challenge and best-selection processes which are the methods to compare the efficiency of the system after they have been genetically calculated. In order to select an appropriate control system in each layer, the simulation's results in the end will show the test with non-linear plant to show the efficiency of control system after it has been developed by designing and tuning process
    No preview · Article · May 2006
  • M. Chatpoj · B. Purahong · T. Thossansin · P. Sooraksa
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper is about using fuzzy PI controller in order to help control the gap in magnetic levitation system (maglev). The details of this paper concerns about the model of maglev system which is applied to floating robots; it is also about how to use fuzzy PI controller for assisting the maglev system in order to make this system more accurate and faster. From the simulation which compared the reactions between fuzzy PI and the original PI, it showed that fuzzy PI had faster response without swaying the output values while it was reaching the setpoint values. Therefore, the fuzzy PI is suitable to control the maglev system in floating robots.
    No preview · Conference Paper · Jan 2005
  • Source
    K. Maneesilp · B. Purahong · P. Sooraksa
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a new design of cellular neural network for controlling hexapod robot movement on forward motion. It shows a set of new state equations which higher propagation than the original one. These new equations reduce number of CNN pattern generation cells from 12 to 6 cells. As a result, this provides a new technique for designing CNN analog control circuits which can be reduced circuit components and simplified the system architectures.
    Full-text · Conference Paper · Dec 2004
  • Source
    Boonchana Purahong · Pitikhate Sooraksa
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a GA-fuzzy P2ID control system for the flexible-joint robot arm. This controller is designed based on the parameter adjustment using fuzzy logic and genetic algorithms. According to the simulations, the better performance has been achieved acquired that the robot moved smoothly and met its required objectives. The results of comparison between 8 parameters and 10 parameters can be conclusion that the 10 parameters have setting time little than 8 parameters. In usability can be use 8 or 10 parameters these one.
    Preview · Article ·