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Author: search.filters.author.Dissanayaka, Supun

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    Novel Adaptive Intelligent Control System Design
    (2025-08-01)
    Duanyai, Worrawat
    ;
    Song, Weon Keun
    ;
    Ka, Min Ho
    ;
    Lee, Dong Wook
    ;
    Dissanayaka, Supun
    A novel adaptive intelligent control system (AICS) with learning-while-controlling capability is developed for a highly nonlinear single-input single-output plant by redesigning the conventional model reference adaptive control (MRAC) framework, originally based on first-order Lyapunov stability, and employing customized neural networks. The AICS is designed with a simple structure, consisting of two main subsystems: a meta-learning-triggered mechanism-based physics-informed neural network (MLTM-PINN) for plant identification and a self-tuning neural network controller (STNNC). This structure, featuring the triggered mechanism, facilitates a balance between high controllability and control efficiency. The MLTM-PINN incorporates the following: (I) a single self-supervised physics-informed neural network (PINN) without the need for labelled data, enabling online learning in control; (II) a meta-learning-triggered mechanism to ensure consistent control performance; (III) transfer learning combined with meta-learning for finely tailored initialization and quick adaptation to input changes. To resolve the conflict between streamlining the AICS’s structure and enhancing its controllability, the STNNC functionally integrates the nonlinear controller and adaptation laws from the MRAC system. Three STNNC design scenarios are tested with transfer learning and/or hyperparameter optimization (HPO) using a Gaussian process tailored for Bayesian optimization (GP-BO): (scenario 1) applying transfer learning in the absence of the HPO; (scenario 2) optimizing a learning rate in combination with transfer learning; and (scenario 3) optimizing both a learning rate and the number of neurons in hidden layers without applying transfer learning. Unlike scenario 1, no quick adaptation effect in the MLTM-PINN is observed in the other scenarios, as these struggle with the issue of dynamic input evolution due to the HPO-based STNNC design. Scenario 2 demonstrates the best synergy in controllability (best control response) and efficiency (minimal activation frequency of meta-learning and fewer trials for the HPO) in control.
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    Calibration of Bi-prism Stereo Systems: A Model Free Approach
    (2024-07-01)
    Dissanayaka, Supun
    ;
    Sooraksa, Pitikhate
    ;
    Kaitwanidvilai, Somyot
    ;
    Morris, John
    A simple stereo system can be constructed from a single camera using a prism in the optical path to provide the required two views of a system. The simplicity of these systems has several advantages, particularly if the target is an underwater robot, where compact size and ability to seal the optical components are key factors. However, dispersion by the prism, in addition to the lens distortion, makes calibration challenging. By using a model-free approach, we were able to calibrate a prism-based stereo system effectively. We also aimed to use readily available 45° prisms, which present significant dispersion in the system, but retain simplicity and reduce cost, compared to custom low angle prisms. Modern LEDs provide high intensity, low bandwidth light sources and we used a set of three sources, roughly centered on the RGB channels of a readily available commercial camera. Our system used a circular target pattern covering the binocularly visible region in the scene and collected sets of images at known distances, using three separate light sources. From these images, we generated two look-up tables, one for each pixel in the image and a disparity derived by matching corresponding points, Cp(u,v,du), which has three dimensions, and another look-up table, which has a single dimension, Cz(z), so are not quite large, and not beyond the memory capability of even small modern camera systems, but provide fast, O(1), lookup times, suitable for real-time systems. Our calibration strategy enables a simple stereo system built from a single camera to measure depths in a scene: the single camera requires no electronic synchronization and is built from a single, inexpensive, and readily available optical component – a right-angle prism.
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    Autonomous Modular Harvesting System for Vertical Aeroponic Farming
    (2023-01-01)
    Asnapetch, Papinwich
    ;
    Ruangrit, Chanet
    ;
    Tongsri, Nabhatara
    ;
    Chuenyoo, Napat
    ;
    Poonthongpan, Peeradon
    As the global population grows exponentially, food consumption rises at a drastic rate. However, the limited availability of agricultural lands and inadequate traditional farming techniques have led to an emergence of alternatives such as hydroponic and aeroponic farming. Nonetheless, these systems still have limits, especially in terms of their constrained expansion when reliant on machinery, and the restricted vertical reach for human labor-driven harvesting. Therefore, we proposed an autonomous modular harvesting system for vertical farming of green oak lettuce. The structure is designed as an expandable cartesian gantry. With the initial base area of 40 x 40 cm, the system could be expanded to 120 cm in length and 240 cm in height, potentially hosting up to 96 lettuces. The system is also integrated with advanced computer vision to detect the presence of a plant and evaluate its readiness, primarily through color detection. Additionally, a specialized mechanism is installed to harvest the ripe lettuce. The system shows a notably high level of accuracy and impressive success rate in both detecting and harvesting.
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    Feed Rate Optimization for Five Axis Milling with an Iso-scallop Tool Path
    (2022-01-01)
    Eranga, Ashan
    ;
    Dissanayaka, Supun
    ;
    Hamontree, Chaowalit
    Five-axis milling tool path generation and feed rate optimization are challenging tasks. Our previous attempt provided a solution for an iso-scallop initial path determination using an optimal feeding direction (OFD) method that was efficient and maintained the quality of the machining surface. This paper extended the method with feed rate optimization to improve the machining time. Maximal allowable feed rate concept was used to define the objective function which was depended on A and B axis of the machine. To achieve smooth rotary axes motion, two B-splines were used to represent each axis. Then the non-linear optimization problem was solved using the interior-point algorithm with the constraint on global collision. Finally, the predetermined iso-scallop path was combined with the optimized tool orientation. The orientation optimization strategy was compared with constant lead angle and tool orientation smoothing method. Simulation results showed that our variable feed rate assignment decrease the machining time.