In this paper, a PID nested higher-order nonsingular terminal sliding mode observer is proposed for speed estimation of Permanent Magnet Synchronous Motor (PMSM). Here, the introduction of PID error embedded into the nonsingular terminal sliding manifold, which is now at higher order, smoothen the observer's control input, leading to significant chattering reduction as well as better accuracy and faster response of the resulted-in back-EMF and rotor's electrical angle estimation. The simulation and experimental results demonstrate the effectiveness and advantages of the proposed approach.
As autonomous driving gains widespread attention, extensive research is being conducted to enable robots to safely reach their destinations independently. Before the rise of advanced robotic artificial intelligence, much research focused on path planning for route exploration and planning. However, these methods have limitations in responding to dynamic environmental changes. To overcome this, efforts have been made to integrate reinforcement learning. This study proposes an adaptive path planning reinforcement learning algorithm, combining the efficiency of path planning with the adaptability of reinforcement learning to various environmental changes. The proposed method effectively integrates traditional path planning algorithms with reinforcement learning. We utilize the TD3 network as the backbone and apply the Artificial Potential Field algorithm, known for its robustness to obstacles. Experimental results demonstrate that our approach achieved approximately 14 points higher average rewards and similar maximum rewards compared to existing networks, indicating higher average success rates. Additionally, results specified above indicate faster or comparable convergence speeds relative to traditional networks.
Delta robots are parallel robots consisting of three arms connected to universal joints at the base and at the end -effector. They are known for their high -speed and precise movement, making them ideal for tasks requiring rapid pick-and-place operations, since the orientation of the end-effector is constant and usually parallel to the work surface. The design features lightweight arms and a fixed base, with intermediate joints consisting of universal joints or spherical joints, which add inertia and backlash to the system. This paper introduces a Delta robot with the use of compliant joints to minimize the number of components. The new compliant joints replicate a universal joint, reduce the inertia of the system, are easy to manufacture, and minimize backlash. The added stiffness alters the precision of the robot, but the stored potential energy in the joint increases the dynamics of the robot, which makes the robot suitable for tasks that requires speed instead of accurate positioning.
Accurate forecasting of pedestrian counts in the Central Business District of Melbourne during extreme scenarios such as the COVID-19 pandemic is crucial for optimizing resource allocation and ensuring public safety. Current models lack the incorporation of major disruptions, leading to a critical gap in urban traffic forecasting. This study addresses this gap by developing an adaptive forecasting model, namely hyperparam-eter finetuning-convolutional neural network-multivariate-long short-term memory. Using hourly pedestrian counts (2020–2022) and COVID-19 case data, historical trends are integrated with pandemic factors to capture long-term patterns and sudden disruptions. Based on three evaluation metrics (NRMSE, MAPE, and R2), the results demonstrate the accuracy of the model in predicting pedestrian traffic during disruptive events. This research advances context-aware pedestrian traffic predictive modelling, enabling informed decision-making in urban environments.
Wireless power transmission remains an open challenge for implantable devices as well as the active multifunctional capsule endoscope. This paper presents a development of high-powered wireless power transmission system for self-actuated soft capsule endoscope. The system consists of a transmitting unit and multiple receiving units. The transmitting unit is capable of generating a powerful uniform alternative magnetic field at multiple desired frequencies, while each of the receiving unit is designed to resonate with transmission signal at a desired frequency. As a result, the proposed wireless power transmission system can transfer 2.1 W power at frequency range from 70–100 kHz. This wireless power transmission system will be applied to control the morphology changing of each soft actuator to create the locomotion of the soft capsule endoscope.
