Outputs (51)

Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring (2022)
Journal Article
Kureshi, R., Mishra, B., Thakker, D., John, R., Walker, A., Simpson, S., Thakkar, N., & Wante, A. (2022). Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring. Sensors, 22(3), Article 1093. https://doi.org/10.3390/s22031093

With the emergence of Low-Cost Sensor (LCS) devices, measuring real-time data on a large scale has become a feasible alternative approach to more costly devices. Over the years, sensor technologies have evolved which has provided the opportunity to h... Read More about Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring.

Fixed-time nonlinear homogeneous sliding mode approach for robust tracking control of multirotor aircraft: Experimental validation (2022)
Journal Article
Mechali, O., Xu, L., Xie, X., & Iqbal, J. (2022). Fixed-time nonlinear homogeneous sliding mode approach for robust tracking control of multirotor aircraft: Experimental validation. Journal of The Franklin Institute, 359(5), 1971-2029. https://doi.org/10.1016/j.jfranklin.2022.01.010

This paper presents a robust scheme for fixed-time tracking control of a multirotor system. The aircraft is subjected to matched lumped disturbances, i.e., unmodeled dynamics, parameters uncertainties, and external perturbations besides measurement n... Read More about Fixed-time nonlinear homogeneous sliding mode approach for robust tracking control of multirotor aircraft: Experimental validation.

Highly Accurate and Reliable Wireless Network Slicing in 5 th Generation Networks: A Hybrid Deep Learning Approach (2022)
Journal Article
Khan, S., Khan, S., Ali, Y., Khalid, M., Ullah, Z., & Mumtaz, S. (2022). Highly Accurate and Reliable Wireless Network Slicing in 5 th Generation Networks: A Hybrid Deep Learning Approach. Journal of Network and Systems Management, 30, Article 29. https://doi.org/10.1007/s10922-021-09636-2

In current era, the next generation networks like 5 th generation (5G) and 6 th generation (6G) networks requires high security, low latency with a high reliable standards and capacity. In these networks, reconfigurable wireless network slicing is co... Read More about Highly Accurate and Reliable Wireless Network Slicing in 5 th Generation Networks: A Hybrid Deep Learning Approach.

Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems (2022)
Journal Article
Haq, I. U., Khan, Q., Ullah, S., Ahmed Khan, S., Akmeliawati, R., Khan, M. A., & Iqbal, J. (2022). Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems. PLoS ONE, 17(1), Article e0260480. https://doi.org/10.1371/journal.pone.0260480

The increasing energy demand and the target to reduce environmental pollution make it essential to use efficient and environment-friendly renewable energy systems. One of these systems is the Photovoltaic (PV) system which generates energy subject to... Read More about Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems.

Collaborative position control of pantograph robot using particle swarm optimization (2022)
Journal Article
Ali, N., Ayaz, Y., & Iqbal, J. (2022). Collaborative position control of pantograph robot using particle swarm optimization. International journal of control, automation and systems, 20(1), 198-207. https://doi.org/10.1007/s12555-019-0931-6

This article presents the design and real-time implementation of an optimal collaborative approach to obtain the desired trajectory tracking of two Degree of Freedom (DOF) pantograph end effector position. The proposed controller constructively syner... Read More about Collaborative position control of pantograph robot using particle swarm optimization.

Improving Graduate Futures and Employability Through Embedded Industrial Experience (2022)
Journal Article
Dixon, J., & Gordon, N. (2022). Improving Graduate Futures and Employability Through Embedded Industrial Experience. New Directions in the Teaching of Physical Sciences, https://doi.org/10.29311/ndtps.v0i17.3596

The financial cost to individuals of higher education is now regularly exceeding £50k before maintenance in the UK; consequently, students are more concerned than ever that their degree should offer value for money when they enter the jobs marketplac... Read More about Improving Graduate Futures and Employability Through Embedded Industrial Experience.

Adaptive FIT-SMC Approach for an Anthropomorphic Manipulator With Robust Exact Differentiator and Neural Network-Based Friction Compensation (2022)
Journal Article
Ali, K., Ullah, S., Mehmood, A., Mostafa, H., Marey, M., & Iqbal, J. (2022). Adaptive FIT-SMC Approach for an Anthropomorphic Manipulator With Robust Exact Differentiator and Neural Network-Based Friction Compensation. IEEE Access, 10, 3378-3389. https://doi.org/10.1109/ACCESS.2021.3139041

In robotic manipulators, feedback control of nonlinear systems with fast finite-time convergence is desirable. However, because of the parametric and model uncertainties, the robust control and tuning of the robotic manipulators pose many challenges... Read More about Adaptive FIT-SMC Approach for an Anthropomorphic Manipulator With Robust Exact Differentiator and Neural Network-Based Friction Compensation.

IoP System Dependability Evaluation Method Based on AADL (2022)
Journal Article
Shi, X., Mian, Z., & Gao, Y. (2022). IoP System Dependability Evaluation Method Based on AADL. Jisuanji Gongcheng/Computer Engineering, 48(1), 204-213. https://doi.org/10.19678/j.issn.1000-3428.0059738

The Internet of People(IoP)is characterized by the complex architecture and massive changing data, which adds to the difficulty of the analysis on IoP-based system dependability.Currently, there is still no robust dependability modelling and analysis... Read More about IoP System Dependability Evaluation Method Based on AADL.

Toward Efficient Mobile Electric Vehicle Charging under Heterogeneous Battery Switching Technology (2022)
Journal Article
Ahmad, A., Ullah, Z., Khalid, M., & Ahmad, N. (2022). Toward Efficient Mobile Electric Vehicle Charging under Heterogeneous Battery Switching Technology. Applied Sciences, 12(2), Article 904. https://doi.org/10.3390/app12020904

The fast increase in adoption and development of Electric Vehicles (EVs) has invited a significant challenge to the existing charging management techniques and infrastructure. It is necessary to efficiently manage a large number of mobile EVs. As com... Read More about Toward Efficient Mobile Electric Vehicle Charging under Heterogeneous Battery Switching Technology.

A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms (2022)
Journal Article
Walker, C., Rothon, C., Aslansefat, K., Papadopoulos, Y., & Dethlefs, N. (2022). A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms. Lecture notes in computer science, 13525 LNCS, 189-203. https://doi.org/10.1007/978-3-031-15842-1_14

With an increasing emphasis on driving down the costs of Operations and Maintenance (O &M) in the Offshore Wind (OSW) sector, comes the requirement to explore new methodology and applications of Deep Learning (DL) to the domain. Condition-based monit... Read More about A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms.