International Journal of Intelligent Systems and Applications @ijisa
Статьи журнала - International Journal of Intelligent Systems and Applications
Все статьи: 1187
Research of Self-Tuning PID for PMSM Vector Control based on Improved KMTOA
Статья научная
The Permanent Magnet Synchronous Motor has been applying widely due to it's high efficiency, high reliability, relatively low cost and low moment of inertia. However, the PMSM drives are easily affected by the uncertain factors such as the variation of motor parameters and load disturbance. In order to realize the control of the PMSM accurately, a novel adaptive chaotic kinetic molecular theory optimization algorithm was implemented for seeking the best parameters of PID controller. In the PMSM vector control system, the speed loop will be adjusted by a CKMTOA PID controller. In modified kinetic molecular theory optimization algorithm, the adaptive inertia weight factors are used to accelerate the convergence speed, and chaotic searching is conducted within the neighbor set of the solutions to avoid the local minima. The model of PMSM and its` space vector control system are set up in the software of MATLAB/Simulink. The effectiveness of the self-tuning CKMTOA PID controller is verified by comparing with the conventional PID and particle swarm optimization algorithm. The extensive simulations and analysis also show the effectiveness of the proposed approach.
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Research on Adaptive Fuzzy PID Synchronous Control Strategy of Double-Motor
Статья научная
The double-motor synchronous control system is widely used in industrial field. Its performance plays an important role in production. Traditional PID controller parameters are difficult to tune when used in control system, as well as the control effect can not satisfy the requirement of producing process when the controller plant is complex non-linear system. In this paper, adaptive fuzzy PID which can tune the parameters on-line is introduced to apply in the double-motor synchronous control system. In MATLAB / SMULINK simulation environment, the speed of master motor is perfectly followed by slave motor, and high robustness and precision are obtained. The simulation results show that fuzzy logic PID control strategy has better performances than traditional controller.
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Research on Association with Freight Transit Period and Forwarding Time base on Logistics conditions
Статья научная
The whole process of freight forwarding includes multiple links. The consumption time of every link and its operational efficiency may affect the entire freight forwarding time, which can influence the transit period of freight, as well as the formulation and achievement of the transportation organizations scheme and the transportation contract. In order to analyze the existed problems in present calculation method of railway transit period, and the effects of logistics on forwarding time, on the basis of investigating and literature, Railway freight forwarding process and factor of logistics on railway freight forwarding time were analyzed, and average speed of through train, ordinary through train and high-speed train, and daily average running tariff kilometer and time were analyzed, and statistical results were exained by adopting 2χtesting method, finally, daily average running tariff kilometer and time of logistics developed and under-developed area were comparative analyzed, from which daily average running tariff kilometer and time were obtained. The analytical results show that the average speed, daily average running tariff kilometer and time respectively obeys normal distribution, the maximum difference value between the transit period calculated by present method and the practical forwarding time of freight is four 4.5 days, which show that the method can not objectively responds the freight forwarding time of each kind of freight transport product under logistics condition.
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Research on Canal System Operation Based on Controlled Volume Method
Статья научная
An operating simulation mode based on storage volume control method for multireach canal system in series was established. In allusion to the deficiency of existing controlled volume algorithm, the improved algorithm was proposed, that is the controlled volume algorithm of whole canal pools, the simulation results indicate that the storage volume and water level of each canal pool can be accurately controlled after the improved algorithm was adopted. However, for some typical discharge demand change operating conditions of canal, if the controlled volume algorithm of whole canal pool is still adopted, then it certainly will cause some unnecessary regulation, and consequently increases the disturbed canal reaches. Therefor, the idea of controlled volume operation method of continuous canal pools was proposed, and its algorithm was designed. Through simulation to practical project, the results indicate that the new controlled volume algorithm proposed for typical operating condition can comparatively obviously reduce the number of regulated check gates and disturbed canal pools for some typical discharge demand change operating conditions of canal, thus the control efficiency of canal system was improved. The controlled volume method of operation is specially suitable for large-scale water delivery canal system which possesses complex operation requirements.
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Research on Key Technology of New Concept Tyre Building Production Line
Статья научная
Tyre building production line gradually transits from stand-alone production to combined production mode. The transformation of work mode from traditional serial intermittent to the parallel continuous has been the key technology research of tire production enterprise. And intelligent robots and other automated equipment have been the first choice of the tyre enterprise’s production line. Considering the combination of the equipment between upper and lower processes in tyre production line, the manual operations in some processes replaced by intelligent robots will improve production efficiency of tyre production enterprise, and will make outstanding contribution in reduce process losses and reduce production costs. This article studies on the key technology of combined application in production line, and makes simulation comparison for the same technical process that using different scheme, to prove the priorities and superiorities of combined production line relatives to the traditional production mode.
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Статья научная
In this paper, according to the structure char-acteristics of steer-by-wire (SBW) system for the TFC20 electric forklift, steering dynamics model and two degree of freedom vehicle model are deduced for SBW forklift. Aiming at the free design features of the angular trans-mission characteristics in the SBW system of electric forklift, the theory of active steering control strategy is studied. After analyzing the influence factors of the an-gular transmission ratio of the steering system, the ideal angular transmission ratio is proposed, which is based on the yaw rate gain invariance. Also, the control strategy of the yaw rate feedback and the full state feedback is stud-ied. The simulation results show that the above strategy is effective for the active steering control; it can improve the operating stability and the response speed of the fork-lift.
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Статья научная
Combined with the transmission ratio charac-teristics of forklift steering-by-wire (SBW) system, through the application of fuzzy control technology, the variable transmission ratio function is designed based on the steering handle angle and vehicle speed, and simula-tion analysis of sinusoidal steering is done at low-speed and high-speed. Simulation results show that the fuzzy variable transmission ratio control can make forklift steering light & sensitive at low-speed and steering steady & heavy at high speed, also it can improve the operation stability and reduce the driver's load. Discuss the relationship between yaw rate and forklift handling stability, propose the yaw rate feedback control strategy based on the fuzzy variable transmission ratio control, and design a fuzzy self-adaptive PID controller. Simula-tion results show that the SBW system based on the fuzzy variable transmission ratio control with yaw rate feedback can accurately and quickly track the desired yaw rate, and reduce or even eliminate the overshoot phenomenon, improve the forklift dynamic performance.
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Research on temperature field and temperature stress of prestressed concrete girders
Статья научная
This paper introduces the establishment and simplification of the temperature field and the general calculation method of temperature stress of the prestressed concrete box girders. Three kinds of sunshine temperature gradient models were loaded to a real bridge respectively, and got stress and displacement curves. Research data of several prestressed concrete box girders were selected from different regions of China to compare the relative error of the calculated and measured value. We indicate that the study of temperature field and thermal stress of prestressed concrete box girders is necessary, and will help engineers to solve the problem in structure design.
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Research on the Layout of National Economic Mobilization Logistics Centers
Статья научная
The problem of the layout of NEMLC (National Economic Mobilization Logistics Center) is one of the most important long-term decision-making issues. The result of NEMLC’s layout directly impacts many aspects of mobilization, such as time, reliability, quality, efficiency, cost, and so on, consequently affects the effect of the mobilization. Reasonable NEMLC layout can bring people convenience in the daily life, reduce costs, and improve service efficiency and competitiveness. Poor NEMLC layout often brings a great deal of inconvenience and loss, and even leads to mobilization failure. Under the restriction of mobilization time, the paper establishes the layout model that one or more mobilization logistics centers provide the material to the mobilization demanding place. The mobilization goods or service can reach the demanding place to carry into mobilization execution within the given time, and the number of the built NEMLCs is the least.
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Review and Comparison of Kernel Based Fuzzy Image Segmentation Techniques
Статья научная
This paper presents a detailed study and comparison of some Kernelized Fuzzy C-means Clustering based image segmentation algorithms Four algorithms have been used Fuzzy Clustering, Fuzzy C-Means(FCM) algorithm, Kernel Fuzzy C-Means(KFCM), Intuitionistic Kernelized Fuzzy C-Means(KIFCM), Kernelized Type-II Fuzzy C-Means(KT2FCM).The four algorithms are studied and analyzed both quantitatively and qualitatively. These algorithms are implemented on synthetic images in case of without noise along with Gaussian and salt and pepper noise for better review and comparison. Based on outputs best algorithm is suggested.
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Review, Design, Optimization and Stability Analysis of Fractional-Order PID Controller
Статья научная
This paper will establish the importance and significance of studying the fractional-order control of nonlinear dynamical systems. The foundation and the sources related to this research scope is going to be set. Then, the paper incorporates a brief overview on how this study is performed and present the organization of this study. The present work investigates the effectiveness of the physical-fractional and biological-genetic operators to develop an Optimal Form of Fractional-order PID Controller (O2Fo-PIDC). The newly developed Fo-PIDC with optimal structure and parameters can, also, improve the performances required in the modeling and control of modern manufacturing-industrial process (MIP). The synthesis methodology of the proposed O2Fo-PIDC can be viewed as a multi-level design approach. The hierarchical Multiobjective genetic algorithm (MGA), adopted in this work, can be visualized as a combination of structural and parametric genes of a controller orchestrated in a hierarchical fashion. Then, it is applied to select an optimal structure and knowledge base of the developed fractional controller to satisfy the various design specification contradictories (simplicity, accuracy, stability and robustness).
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Rice Leaf Disease Recognition using Local Threshold Based Segmentation and Deep CNN
Статья научная
Timely detection of rice diseases can help farmers to take necessary action and thus reducing the yield loss substantially. Automatic recognition of rice diseases from the rice leaf images using computer vision and machine learning can be beneficial over the manual method of disease recognition through visual inspection. During the recent years, deep learning, a very popular and efficient machine learning algorithm, has shown great promise in image classification task. In this paper, a segmentation-based method using deep neural network for classifying rice diseases from leaf images has been proposed. Disease-affected regions of the rice leaves have been segmented using local segmentation method and the Convolutional Neural Network (CNN) has been trained with those images. Proposed method has been applied on three different datasets including the one created by us which consists of the rice leaf images collected from Bangladesh Rice Research Institute (BRRI). Three state-of-the-art CNN architectures VGG, ResNet and DenseNet, used in the proposed method, have been trained with these three datasets for classifying the diseases. Classification performance of the proposed method using the said three CNN architectures for the three datasets have been analyzed and compared. These results show that this model is quite promising in classifying rice leaf diseases. Outcome of this research is an enhancement in the performance of rice disease classification which is quite significant for the viability of this work to be transformed into a real-time application for the farmers.
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Robot Based Preventive Maintenance System for In-Service Inspection of Equipments
Статья научная
The current tendency in the petrochemical plants and Aerospace industry is to save weight and life of the equipments in the processing units, in order to reduce costs and to ensure remaining life of components. The world of today is improving with respect to new technologies. As a result, new composites are added to material for gaining a new shape and structure of material. This has made it compulsory for new innovative in non destructive testing specially in ultrasonic inspection, from conventional ultrasonic based on pulse echo method to phased array methods. In parallel to this innovative in ultrasonic, mechanical manipulator have evolved for grinding and take a setup to unapproachable zones. Industrial robot with ultrasonic inspection developed in this paper, with the collaboration of Indian Oil Corporation, Faridabad, India. Which are bringing reliability, durability, accuracy, flexibility, good maintenance and reproducibility for different sizing components to in-service inspection? This paper focused on the evolution of in-service ultrasonic probe with mechanical manipulator in non destructive testing. This evolution system has led to the current scenario systems, where a perfect combination of innovative methods in ultrasonic techniques and robots is meet to our expected delivers.
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Robust Fuzzy PD Method with Parallel Computed Fuel Ratio Estimation Applied to Automotive Engine
Статья научная
Both fuzzy logic and computed fuel ratio can compensate the steady-state error of proportional-derivative (PD) method. This paper presents parallel computed fuel ratio compensation for fuzzy plus PID control management with application to internal combustion (IC) engine. The asymptotic stability of fuzzy plus PID control methodology with first-order computed fuel ratio estimation in the parallel structure is proven. For the parallel structure, the finite time convergence with a super-twisting second-order sliding-mode is guaranteed.
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Robust, Interactive, and Intelligent Captcha Model Based on Image Processing
Статья научная
Ensuring online security against automated attacks remains a critical challenge, as traditional CAPTCHA mechanisms often struggle to balance robustness and usability. This study proposes a novel intelligent and interactive CAPTCHA system that integrates advanced image processing techniques with a convolutional neural network (CNN)-based evaluation model to enhance security and user engagement. The proposed CAPTCHA dynamically generates images with randomized object placement, adaptive noise layers, and geometric transformations, making them resistant to AI-based solvers. Unlike conventional CAPTCHAs, this approach requires users to interact with images by selecting and marking specific objects, creating a human-in-the-loop validation process. For evaluation, a CNN-based classifier processes user selections and determines their validity. A lightweight embedded software module tracks user interactions in real-time, monitoring selection accuracy and response patterns to improve decision-making. The system was tested on 6,000 images across five categories (airplanes, cars, cats, motorcycles, and fish), with an 80% training and 20% testing split. Experimental results demonstrate a classification accuracy of 99.58%, validation accuracy of 96.15%, and a loss value of 0.2078. The CAPTCHA evaluation time was measured at 47–53 milliseconds for initial validation and 17–23 milliseconds for subsequent evaluations. These results confirm that the proposed CAPTCHA model effectively differentiates human users from bots while maintaining usability, demonstrating superior resilience against automated solvers compared to traditional approaches.
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Role of Explainable AI in Crop Recommendation Technique of Smart Farming
Статья научная
Smart farming is undergoing a transformation with the integration of machine learning (ML) and artificial intelligence (AI) to improve crop recommendations. Despite the advancements, a critical gap exists in opaque ML models that need to explain their predictions, leading to a trust deficit among farmers. This research addresses the gap by implementing explainable AI (XAI) techniques, specifically focusing on the crop recommendation technique in smart farming. An experiment was conducted using a Crop recommendation dataset, applying XAI algorithms such as Local Interpretable Model-agnostic Explanations (LIME), Differentiable InterCounterfactual Explanations (dice_ml), and SHapley Additive exPlanations (SHAP). These algorithms were used to generate local and counterfactual explanations, enhancing model transparency in compliance with the General Data Protection Regulation (GDPR), which mandates the right to explanation. The results demonstrated the effectiveness of XAI in making ML models more interpretable and trustworthy. For instance, local explanations from LIME provided insights into individual predictions, while counterfactual scenarios from dice_ml offered alternative crop cultivation suggestions. Feature importance from SHAP gave a global perspective on the factors influencing the model's decisions. The study's statistical analysis revealed that the integration of XAI increased the farmers' understanding of the AI system's recommendations, potentially reducing food insufficiency by enabling the cultivation of alternative crops on the same land.
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Rope Climbing Robot with Surveillance Capability
Статья научная
In the past different engineers and researcher developed robots capable of climbing for various purposes. In this paper we have developed a robot capable of rope climbing in both horizontal and vertical direction. Furthermore, the robot has the ability to perform surveillance using a camera mounted on top of the robot. The quality of the transmitted video from the camera to the computer is clear and stable. Hence the developed robot is a good choice for surveillance purposes. In addition, it can be used to traverse floors of a building. It uses an IR sensor to sense strips attached at each floor. Once the strips are sensed, a dropping mechanism is activated in which a specific object is dropped to the targeted floor or location. The robot can work in automatic mode or manual through RF signals from an RF transmitter. Finally the robot is cost effective compared to many other developed robots for rope climbing.
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Rough Fuzzy Relation on Two Universal Sets
Статья научная
Fuzzy set theory was introduced by L.A. Zadeh in 1965. Immediately, it has many applications in practice and in building databases, one of which is the construction of a fuzzy relational database based on similar relationship. The study of cases of fuzzy relations in different environments will help us understand its applications. In this paper, the rough fuzzy relation on Cartesian product of two universe sets is defined, and then the algebraic properties of them, such as the max, min, and composition of two rough fuzzy relations are examined. Finally, reflexive, α-reflexive, symmetric and transitive rough fuzzy relations on two universe sets are also defined.
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Rough Set Model for Nutrition Management in Site Specific Rice Growing Areas
Статья научная
The optimized fertilizer usage for better yield of rice cultivation is influenced by key factors like soil fertility, crop variety, duration, season, nutrient content of the fertilizer, time of application etc., It is observed that 60 percent of yield gap in tamilnadu is due to farmers lack of knowledge on key factors and informal sources of information by pesticide dealers. In this study the major contributing factors for fertilizer requirement and optimum crop yield were analyzed based on rough set theory. In data analytics perspective the nutrient plan is sort of multiple attribute decision-making processes. To reduce the complexity of decision making, key factors that are indiscernible to conclusion are eliminated. Our rough set based approach improved the quality of agricultural data through removal of missing and redundant attributes. After pretreatment the data formed as target information, then attribute reduction algorithm was used to derive rules. The generated rules were used to structure the nutrition management decision-making. The precision was above 88% and experiments proved the feasibility of the developed decision support system for nutrient management.
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Rule Based Ensembles Using Pair Wise Neural Network Classifiers
Статья научная
In value estimation, the inexperienced people's estimation average is good approximation to true value, provided that the answer of these individual are independent. Classifier ensemble is the implementation of mentioned principle in classification tasks that are investigated in two aspects. In the first aspect, feature space is divided into several local regions and each region is assigned with a highly competent classifier and in the second, the base classifiers are applied in parallel and equally experienced in some ways to achieve a group consensus. In this paper combination of two methods are used. An important consideration in classifier combination is that much better results can be achieved if diverse classifiers, rather than similar classifiers, are combined. To achieve diversity in classifiers output, the symmetric pairwise weighted feature space is used and the outputs of trained classifiers over the weighted feature space are combined to inference final result. In this paper MLP classifiers are used as the base classifiers. The Experimental results show that the applied method is promising.
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