Sirisuk, Phaophak

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Sirisuk, Phaophak
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Sirisuk, P.
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phaophak.si@kmitl.ac.th

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    Simple and Effective Design Concept for Constructing In-Situ Soil Dielectric Property Sensor with Dual Low-Cost COTS Microwave Modules
    (2022-01-01)
    Leekul, Prapan
    ;
    Mgawe, Bonny
    ;
    Kazema, Twahir
    ;
    Dao, Hoang Nam
    ;
    Sirisuk, Phaophak
    This paper presents a compact sensor system for estimating the dielectric properties of materials based on commercial, off-the-shelf (COTS) modules. The dielectric constant and conductivity of a material under test can be determined from the measurement of the microwave reflected from the material. By using dual microwave sensor modules with a slightly different radio frequency, an identical intermediate frequency at the mixers of the modules was obtained. The intermediate frequency was chosen such that the associated microwave and data processing components could be easily obtainable, leading to a practical realization of the sensor system. Synchronization of the two microwave sensor modules was achieved using electronically controlled relays that simultaneously switch on the power supplies of both modules. Two microcontrollers were used to capture the corresponding signals. The sensor was designed at a 10 GHz band for measuring reflected waves from various kinds of materials, especially soils with different moisture and fertilizer contents. The evaluation results indicate a good agreement between the measured results from the proposed sensor and the ones from a network analyzer, verifying that the proposed sensor is fully functional for monitoring variation in the dielectric properties of materials, including soil. The average sensitivity for the dielectric constant of moist soil is 0.26/% moisture content and the error rate for dielectric constant measurement is 4.83%.
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    Low cost RISC implementation of intelligent ultra fast charger for Ni-Cd battery
    (2008-02-01)
    Petchjatuporn, Panom
    ;
    Sirisuk, Phaophak
    ;
    Khaehintung, Noppadol
    ;
    Sunat, Khamron
    ;
    Wicheanchote, Phinyo
    This paper presents a low cost reduced instruction set computer (RISC) implementation of an intelligent ultra fast charger for a nickel-cadmium (Ni-Cd) battery. The charger employs a genetic algorithm (GA) trained generalized regression neural network (GRNN) as a key to ultra fast charging while avoiding battery damage. The tradeoff between mean square error (MSE) and the computational burden of the GRNN is addressed. Besides, an efficient technique is proposed for estimation of a radial basis function (RBF) in the GRNN. Hardware realization based upon the techniques is discussed. Experimental results with commercial Ni-Cd batteries reveal that while the proposed charger significantly reduces the charging time, it scarcely deteriorates the battery energy storage capability when compared with the conventional charger. © 2007 Elsevier Ltd. All rights reserved.
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    Hardware-assisted initialisation for constant modulus algorithm adaptive antenna
    (2008-05-26)
    Boonpoonga, A.
    ;
    Sirisuk, P.
    ;
    Chongcheawchamnan, M.
    ;
    Patisang, S.
    ;
    Krairiksh, M.
    A cost-effective approach for initialisation of an adaptive antenna based on the constant modulus algorithm (CMA) is proposed. The technique utilises 1 bit phase shifters and a power detector, which are normally integrated with a multibeam antenna, to determine the maximum power beam direction. Consequently, the beam is exploited as an initial beam for CMA. Development of hardware-assisted initialisation is discussed. In addition, field programmable gate array implementation of a CMA processor and associated control circuitry is presented. Several simulations are performed to evaluate the performance of the proposed initialisation technique. In addition, the developed prototype is tested with a phase array antenna designed for operation at the IMT2000 frequency of 1.95GHz. Experimental results confirm superiority of the proposed technique. © The Institution of Engineering and Technology 2008.
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    Efficient parallel architecture for implementation of the CMA adaptive antenna
    (2013-07-01)
    Boonpoonga, Akkarat
    ;
    Sirisuk, Phaophak
    ;
    Krairiksh, Monai
    This paper presents an efficient parallel architecture for implementation of a constant modulus algorithm (CMA) adaptive array antenna. By inserting delay units into the original CMA, a novel delayed CMA (DCMA) that can significantly reduce the associated critical path is derived. Consequently, a pipelining architecture that supports parallel processing is introduced for implementation of the DCMA. In addition to the pipelining technique, a power-of-two multiplier is proposed for the DCMA leading to the efficient FPGA implementation. The effects of delays and finite word-length on the convergence property of CMA are investigated via simulations. Moreover, the synthesized results demonstrate that FPGA implementation of the proposed architecture using power-of-two arithmetic achieves 26.9% resource reduction in comparison with that of fixed-point arithmetic and operating clock frequency higher than 65 MHz. The implemented FPGA was tested to confirm that the designed architecture operates well for CMA.
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    A novel fuzzy logic control technique tuned by particle swarm optimization for maximum power point tracking for a photovoltaic system using a current-mode boost converter with bifurcation control
    (2010-04-01)
    Khaehintung, Noppadol
    ;
    Kunakorn, Anantawat
    ;
    Sirisuk, Phaophak
    This paper presents a novel fuzzy logic control technique tuned by particle swarm optimization (PSO-FLC) for maximum power point tracking (MPPT) for a photovoltaic (PV) system. The proposed PV system composes of a current-mode boost converter (CMBC) with bifurcation control. An optimal slope compensation technique is used in the CMBC to keep the system adequately remote from the first bifurcation point in spite of nonlinear characteristics and instabilities of this converter. The proposed PSO technique allows easy and more accurate tuning of FLC compared with the trialand-error based tuning. Consequently, the proposed PSO-FLC method provides faster tracking of maximum power point (MPP) under varying light intensities and temperature conditions. The proposed MPPT technique is simple and particularly suitable for PV system equipped with CMBC Experimental results are shown to confirm superiority of the proposed technique comparing with the conventional PVVC technique and the trial-and-error based tuning FLC. © ICROS, KIEE and Springer 2010.
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    Single-Frequency Sensor for Thick Rind Fruit Quality Assessment
    (2025-01-01)
    Leekul, Prapan
    ;
    Dao, Hoang Nam
    ;
    Sirisuk, Phaophak
    ;
    Phongcharoenpanich, Chuwong
    ;
    Krairiksh, Monai
    A sensor capable of estimating the dielectric properties of the outer and inner materials of a concentric dielectric sphere is essential for assessing the quality of thick rind fruits. This article presents a sensor design that operates at a single frequency and is straightforward. The underlying principle of the sensor involves transmitting a microwave signal to a concentric dielectric sphere with two power levels. The low-power signal yields backscattered waves from the outer sphere, while the high-power signal provides information about backscattered waves from both the outer and inner spheres. The sensor, which operates at a frequency of 10 GHz using cost-effective components, effectively detects defects in spherical-shaped fruits, e.g., mangosteens. The accuracy in classifying translucent mangosteens from normal mangosteens is 92.5%, enabling effective classification of defected fruits.
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    A Low-cost Autonomous Lawn Mower with AI-Based Obstacle Avoidance and GPS Guidance System
    (2025-07-01)
    Kosri, Thanapon
    ;
    Seekhamharn, Tossawat
    ;
    Phoonsrichaiyasit, Phasawut
    ;
    Khungpo, Poowadon
    ;
    Sirisuk, Phaophak
    This paper presents a cost-effective robotic system capable of manual control via RF remote and autonomous navigation using GPS-based information. The system employs artificial intelligence to dynamically classify and avoid non-grass obstacles, ensuring safe operation in real environments. The prototype integrates affordable hardware including Arduino board, sensors, actuators and Raspberry Pi with lightweight algorithms to balance performance and cost. Experimental validation confirms its ability to follow predefined paths with ±1.5 meters deviation in open area and 90% obstacle avoidance success rate. With a total hardware cost under $200, this prototype highlights feasibility for larger-scale implementation.