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Author: search.filters.author.Kaitwanidvilai, SomyotSubject: search.filters.subject.PSO

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    Remote sensing to minimize energy consumption of six-axis robot arm using particle swarm optimization and artificial neural network to control changes in real time
    (2020-01-01)
    Kaitwanidvilai, Somyot
    ;
    Chanarungruengkij, Veerasak
    ;
    Konghuayrob, Poom
    We propose a new method for the analysis and design of a robotic system that minimizes the energy consumption of a six-axis robot arm by controlling the velocity and acceleration of each arm of the robot to achieve the specified trajectory of the robot determined from a lean manufacturing method. A dynamic model of the PUMA 560 robot has been simulated on MATLAB, while the Robotics Toolbox and particle swarm optimization (PSO) are utilized to search for optimal paths and the optimal velocity and acceleration of the robot arms. The optimal velocity and acceleration are described as those giving minimum overall energy consumption constrained by a specified cycle time of the entire robotic system. Typically, the picking and placing of materials are carried out by humans, causing a variation in production rate, whereas our system using a robot arm ensures a stable production rate. Moreover, the optimal results obtained from PSO are adopted to train an artificial neural network (ANN) to extend the design system from discrete optimal values to a continuous and near-optimal value. In other words, the ANN is used to obtain an approximate optimal value between those obtained from PSO to make the system applicable to a real-world system. As shown by the simulation results, this method reduces the energy consumption of 12.3% from the initial energy and reduces the time for optimization by 99.8% compared with that for the PSO technique.
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    Hybrid adaptive notch filter and fixed-structure pid H ∞ robust loop shaping control based pso for hard disk drive servo actuator
    (2019-02-01)
    Konghuayrob, Poom
    ;
    Kaitwanidvilai, Somyot
    ;
    Aoyama, Hisayuki
    In order to achieve the high precision head-positioning of the voice coil motor (VCM) actuator with narrow track pitch, the adaptive notch filter based limited-search-range of particle swarm optimization (PSO), as well as the fixed-structure propor-tional-integral-derivative H <inf>∞</inf> robust loop shaping controller using the concept of four closed loop disturbance norms is proposed. Generally the conventional method, fixed-frequency notch filter (FFNF), is combined with the nominal plant to reduce the effect of the mechanical vibration resonance; however, the resonance mode of servo system can be shifted with various factors such as the ambient temperature change, and the unbalanced disk. In addition, mathematical solving in the H <inf>∞</inf> robust control problems and the suitable notch filter design are very complex and the final results of the conventional controller with notch filters are normally complicated structure and high order which is difficult to implement. Thus, the adding of intelligent system in the proposed design with the careful range of the search space is utilized to suppress the vibration caused by resonance mode shifting and also reduce the order of the final robust controller. Simulation results of six scenarios test demonstrate the effectiveness of the proposed design compared with FFNF in the commercial product.