The irrigation systems in nurseries can be the cause of various water supply errors- ranging from lack of sufficient water supply to over-watering and imbalance in the water pH levels. Based on the statistics recorded...
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One of the crucial software elements in the upcoming generation of autonomous vehicles is image recognition. Traditional approaches to image recognition using computer vision and machine learning typically have a leng...
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This paper proposes a generalized dynamics model for a Non-Grounded System (NGS) mounted with a Reaction Force Sensing Series Elastic Actuator (RFSEA), focusing on scenarios where the actuator's base is unfixed an...
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ISBN:
(数字)9798331533892
ISBN:
(纸本)9798331533908
This paper proposes a generalized dynamics model for a Non-Grounded System (NGS) mounted with a Reaction Force Sensing Series Elastic Actuator (RFSEA), focusing on scenarios where the actuator's base is unfixed and interacts with the ground. In RFSEA-based force control, the actuator base, which provides the necessary reaction force as dictated by Newton's third law, plays a critical role. This study examines how the interaction between the actuator base and the ground it is attached to influences the response of the series elasticity that generates force in the RFSEA. The investigation involves two steps. First, a generalized dynamics model that considers the dynamics between the actuator base and the ground is derived. Second, the Small Gain Theorem (SGT) is applied to evaluate the robustness of force control under load-side model uncertainties when a Force-based Disturbance Observer (FDOB), originally designed for GS, is adapted to NGS. The analysis reveals that force control utilizing FDOB can become unstable when the actuator base is unfixed, and simulations validate these findings.
A two-wheeled self-balancing robot (TWSBR) is non-linear and unstable system. This study compares the performance of model-based and data-based control strategies for TWSBRs, with an explicit practical educational app...
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A two-wheeled self-balancing robot (TWSBR) is non-linear and unstable system. This study compares the performance of model-based and data-based control strategies for TWSBRs, with an explicit practical educational approach. Model-based control (MBC) algorithms such as Lead-Lag and PID control require a proficient dynamic modeling and mathematical manipulation to drive the linearized equations of motions and develop the appropriate controller. On the other side, data-based control (DBC) methods, like fuzzy control, provide a simpler and quicker approach to designing effective controllers without needing in-depth understanding of the system model. In this paper, the advantages and disadvantages of both MBC and DBC using a TWSBR are illustrated. All controllers were implemented and tested on the OSOYOO self-balancing kit, including an Arduino microcontroller, MPU-6050 sensor, and DC motors. The control law and the user interface are constructed using the LabVIEW-LINX toolkit. A real-time hardware-in-loop experiment validates the results, highlighting controllers that can be implemented on a cost-effective platform.
We present a design optimisation method for the routing of tendons in a tendon-driven mechanism with the objective of maximising force transmission efficiency (FTE). We formulate a friction model for the different rou...
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ISBN:
(数字)9798350373578
ISBN:
(纸本)9798350373585
We present a design optimisation method for the routing of tendons in a tendon-driven mechanism with the objective of maximising force transmission efficiency (FTE). We formulate a friction model for the different routing elements, accounting for routing point radii and slipping/rolling contacts. We then construct a numerical design optimisation problem to optimise the design parameters, routing point locations, for a given tendon routing topology. We apply the method to the design of an existing tendon-driven gripper. The results show that frictional losses can be reduced by approximately half compared to the baseline design, and that taking into account the routing point radii is indeed of significant influence.
In recent years, microgrid systems have gained popularity as reliable, efficient, and clean energy sources for local communities. Among these, solar PV systems stand out as a widely used microgrid variant. However, th...
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We propose a new multirotor aerial vehicle class of designs composed of a multi-body structure in which a main body is connected by passive joints to links equipped with propellers. We have investigated some instances...
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This paper presents the Design and Development of IoT Based Weather and Air Quality Monitoring stations that provide weather-related information for agriculture, and aviation climate forecasting purposes. The prototyp...
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With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service *** volume is an influential parameter for planning and operatin...
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With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service *** volume is an influential parameter for planning and operating traffic *** study proposed an improved ensemble-based deep learning method to solve traffic volume prediction problems.A set of optimal hyperparameters is also applied for the suggested approach to improve the performance of the learning *** fusion of these methodologies aims to harness ensemble empirical mode decomposition’s capacity to discern complex traffic patterns and long short-term memory’s proficiency in learning temporal ***,a dataset for automatic vehicle identification is obtained and utilized in the preprocessing stage of the ensemble empirical mode decomposition *** second aspect involves predicting traffic volume using the long short-term memory ***,the study employs a trial-and-error approach to select a set of optimal hyperparameters,including the lookback window,the number of neurons in the hidden layers,and the gradient descent ***,the fusion of the obtained results leads to a final traffic volume *** experimental results show that the proposed method outperforms other benchmarks regarding various evaluation measures,including mean absolute error,root mean squared error,mean absolute percentage error,and *** achieved R-squared value reaches an impressive 98%,while the other evaluation indices surpass the *** findings highlight the accuracy of traffic pattern ***,this offers promising prospects for enhancing transportation management systems and urban infrastructure planning.
To address the global challenge of population aging, our goal is to enhance successful aging through the introduction of robots capable of assisting in daily physical activities and promoting light exercises, which wo...
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