Konghuayrob, Poom
Loading...
9 results
Now showing 1 - 9 of 9
- Some of the metrics are blocked by yourconsent settings
Item type:Publication, Microprocessor based fuzzy MPPT for PV-AC module DCM-flyback Inverter(2013-01-01); This paper proposes a maximum power point tracking using fuzzy based perturb and observe (P&O) algorithm for a photovoltaic (PV) system (an AC module). In AC module flyback inverter, modulation index (Δma) are adopted as a control variable to track the maximum power point (MPP) of PV array. In the conventional technique, step size of modulation index (Δma) is adopted in the simple P&O technique; Although this technique is easy to be implemented but there is some problems regarding large oscillation around the MPP and slow tracking when improper step size is selected. The proposed technique, fuzzy based P&O technique, is adopted to provide non-equal step size of Δma. The proposed fuzzy system was programmed on microcontroller which is a low cost processing device. Experimental result confirms that the proposed system can effectively track the power from PV system, and is better than the conventional technique. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Robust H∞ Mixed-sensitivity PID structural based on PSO considering input constraint(2017-01-01); Kaitwanividvilai, SomyotRobust control is one of the potential design methods to maintain system performance and system stability from the familial uncertainties. In addition, the limitation of performance as an input energy constraint needs to be considered to prevent the system stability degradation as well. This paper focuses on the design of H<inf>∞</inf> mixed sensitivity based on structural PID controller for high accuracy hard disk drive servo system which examines the input saturation constraint. Particle swarm optimization (PSO) is utilized in the proposed design to maximize the system stability index called stability margin (), which consists of three norms of H<inf>∞</inf> mixed sensitivity control. In order to confirm the effectiveness of the proposed controller, full order H<inf>∞</inf> mixed sensitivity, the proposed PID design with considering the input constraint and trial-error tuning based PID are compared in the simulation section. It is clearly illustrated that the considering input saturation constraint is important to design the controller for sustaining the system performance. Moreover, the results confirm the robustness and performance of three controllers under the repeatable runout (RRO) disturbance. The structure of the proposed PID controller based on PSO is more simple and appropriate to apply into the actual application than the conventional H<inf>∞</inf> mixed sensitivity full order. In addition, the results of the proposed PID controller and conventional H<inf>∞</inf> are quite similar which can reduce the effect of RRO by 50 times and gains 50% more effective than the normal PID in terms of output error. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Maximum power point tracking using hybrid fuzzy based p&o and back propagation (BP) neural network for photovoltaic system(2014-10-01); Photovoltaic system is one of the most popular renewable energy sources to solve the problem of energy crisis. The important problem of solar PV systems is their low efficiency and nonlinear output characteristics in the changing weather that causes the difficulty in tracking of maximum power. To overcome this problem, this paper proposes “Hybrid Fuzzy based P&O and Back Propagation (BP) neural network” for improving the efficiency and reducing the power oscillation of PV system. The proposed system composes of two parts which are fuzzy based P&O and Neural Network. The fuzzy based P&O is used to find the maximum power point (MPP) while the neural network is used to find the appropriate modulation index (ma). The proposed algorithm is adopted in the AC module flyback inverter in which modulation index (Δma) is used as the control variable to track the MPP of the PV array. Simulation results verify that the proposed technique can effectively track the power from PV system, and is better than the conventional P&O techniques - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Maximum power point tracking using neural network in flyback MPPT inverter for PV systems(2012-12-01); Generally, perturb and observe (P&O) technique is widely adopted in photovoltaic (PV) system to maximize the output power. In flyback inverter, the modulation index needs to be adjusted based on the P&O algorithm. However if the changing step size of modulation index (Δma) is too large, the fast MPP (Maximum Power Point) tracking can be achieved but the power oscillation around the MPP will be large. In contrary, the small changing step size results in long tracking time and small oscillation. Consequently, this paper proposes a technique to adjust the changing step size (Δma) of Flyback inverter to achieve both acceptable tracking time and low power oscillation. In the proposed technique, irradiance is adopted as the input of a neural network which is used to estimate the appropriate modulation step size. Simulation results confirm that the proposed neural network based inverter can find the appropriate changing step size (Δma) which is adequate for any irradiance conditions. © 2012 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Particle swarm optimization based specified order robust-gap H∞ loop shaping controller design(2017-01-01); Kaitwanividvilai, SomyotThe demand of data storage capacity in hard disk drive is expected to increase significantly which the areal density will achieve 10 Tbit/in<sup>2</sup> in the near future. An increase of high areal density leads to the reduction of distance per data tracks. Due to the narrow track pitch, hard disk drive system is easily sensitive to the disturbance and noise. This is the benchmark problem for controlling the high precision servo mechanism. The alternative robust loop shaping based v-gap metric is proposed to synthesize the optimal controller for stabilizing a voice coil motor in hard disk drive servo system. Additionally, the designed loop shaping is evaluated by the Riccati procedure with regard to the system robustness. This paper applies the potential particle swarm optimization (PSO) to minimize the close loop gap between the loop shaping of the plant with weighting function and the plant with proposed controller. Moreover, the structure of proposed controller can be specified as the 2<sup>nd</sup> order controller which is uncomplicated to implement in the actual application. The simulation illustrates similar results in terms of the performance tracking and disturbance rejection of proposed controller against the H<inf>∞</inf> loop shaping. Furthermore, the system stability index called stability margin with 0.434 emphasizes the robustness of the proposed controller. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Specified order - H∞ loop shaping control for hard disk drive servo using pso(2016-08-01); The demand of data storage density has been increasing continuously, but the data access time and track pitch need to be decreased. The high precision servo control system is required to achieve the predicted goal that will be crossing 10 TB/in<sup>2</sup> area, I density before 2020. Due to the fact that the precision of read/write head is sensitive to disturbance and noise, it is the challenging problem for the practical control. To overcome this problem, this paper proposes a new servo controller designed, specified order - H<inf>∞</inf> loop shaping (SOHLS) which adapts the particle swarm optimization (PSO) for searching the optimal controller parameters. The proposed technique can solve the problem of high order that was caused from the conventional H<inf>∞</inf> loop shaping (HLS), in addition, it can guarantee the robustness of the servo system,. Based on simulation results, the performances of the proposed SOHLS approach are investigated in comparison with that of the conventional H<inf>∞</inf> robust loop shaping, fixed-structure H<inf>∞</inf> control based on nonsmooth algorithm including reduced order controller by Hangkel norm model reduction technique. The proper repeatable runout (RRO) and non-repea table runout (NRRO) were applied, to the system to verify the robustness of all designed, controllers. The results demonstrate the advantages of the proposed SOHLS which gains better performance and more robustness than the other conventional controllers. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Hybrid adaptive notch filter and fixed-structure pid H ∞ robust loop shaping control based pso for hard disk drive servo actuator(2019-02-01); ; Aoyama, HisayukiIn 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. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A convolutional neural network for segmentation of background texture and defect on copper clad lamination surface(2018-08-13); This research interprets the design and test process of copper clad lamination surface defects detection. The system was included four following stages: Image acquisition, image pre-processing and segmentation, convolutional neural network design and image classification. Image processing method and pattern recognition algorithm are utilized in the system. First, the author applies the smoothing filters to eliminate noise from the images and segmenting a defect from background texture. Then, the convolutional neural network architecture is created to learn local feature of defect and background texture. Finally, defect and background images from segmentation step are collected and fed into a convolutional neural network to train and perform the classification task. The classification results demonstrate that the proposed method can re-checked false positive detect from the conventional Sobel edge detection, Hence the accuracy was increased from 78.1% to 98.2%. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Low order robust ν-gap metric H∞ loop shaping controller synthesis based on particle swarm optimization(2017-12-01); The strong demand of the data storage capacity has been increasing significantly. According to the heat-assisted magnetic recording (HAMR) technology, the demand trend of hard disk drive (HDD) is predicted that the areal density will be achieved 10 Tbit/in<sup>2</sup> before the year 2020. High areal density results in a narrow track pitch which is quite sensitive to the external disturbance including the measured noise. This point is the benchmark problem of the high precision controller design for controlling the HDD servo mechanism. Moreover, the systematic uncertainties have to be taken into consideration in controller design procedure as well. The alternative robust ν-gap metric related to H<inf>∞</inf> loop shaping is proposed in this paper to stabilize a voice coil motor in HDD under the uncertainty condition. The potential particle swarm optimization (PSO) is adopted to minimize the gap between the plant with H<inf>∞</inf> controller and the plant with specified 3 controller orders. Instead of using the conventional H<inf>∞</inf> controller with high order with a complicated structure, this paper applies the proposed lower controller order based on ν-gap which is more appropriate implement in the actual application. The performance and robustness of both controllers are compared in the simulation studies. The results confirm the similar characteristics of both controllers in terms of performance tracking and disturbance rejection. Furthermore, the system stability index called stability margin with 0.472 and system perturbations testing condition also emphasizes the robustness and effectiveness of the proposed controller.