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Trajectory tracking of a quadrotor using extend state observer based U-model enhanced double sliding mode control (2023)
Journal Article
Li, R., Zhu, Q., Nemati, H., Yue, X., & Narayan, P. (2023). Trajectory tracking of a quadrotor using extend state observer based U-model enhanced double sliding mode control. Journal of The Franklin Institute, 360(4), 3520-3544. https://doi.org/10.1016/j.jfranklin.2022.11.036

This paper develops a novel U-model enhanced double sliding mode controller (UDSMC) for a quadrotor based on multiple-input and multiple-output extended-state-observer (MIMO-ESO). UDSMC is designed using Lyapunov synthesis and Hurwitz stability to no... Read More about Trajectory tracking of a quadrotor using extend state observer based U-model enhanced double sliding mode control.

An improved U-control design for nonlinear systems represented by input/output differential models with a disturbance observer (2022)
Journal Article
Li, R., Zhu, Q., Zhang, W., Yue, X., & Narayan, P. (2023). An improved U-control design for nonlinear systems represented by input/output differential models with a disturbance observer. International Journal of Control, 96(11), 2737-2748. https://doi.org/10.1080/00207179.2022.2111370

This paper presents a new method to calculate the inversion of the controlled linear/nonlinear dynamic plants which are described by input–output differential equation models. This new U-model-based inverter (U-inverter), cancels both system dynamics... Read More about An improved U-control design for nonlinear systems represented by input/output differential models with a disturbance observer.

Disturbance-observer-based u-control (Dobuc) for nonlinear dynamic systems (2021)
Journal Article
Li, R., Zhu, Q., Yang, J., Narayan, P., & Yue, X. (2021). Disturbance-observer-based u-control (Dobuc) for nonlinear dynamic systems. Entropy, 23(12), https://doi.org/10.3390/e23121625

U-model, which is a control-oriented model set with the property of generally facilitate nonlinearity dynamic inversion/cancellation, has been introduced to the Disturbance Observer-Based control (DOBC) methods to improve the performance of the nonli... Read More about Disturbance-observer-based u-control (Dobuc) for nonlinear dynamic systems.

Robust standard gradient descent algorithm for ARX models using Aitken acceleration technique (2021)
Journal Article
Chen, J., Gan, M., Zhu, Q., Narayan, P., & Liu, Y. (2022). Robust standard gradient descent algorithm for ARX models using Aitken acceleration technique. IEEE Transactions on Cybernetics, 52(9), 9646-9655. https://doi.org/10.1109/tcyb.2021.3063113

A robust standard gradient descent (SGD) algorithm for ARX models using the Aitken acceleration method is developed. Considering that the SGD algorithm has slow convergence rates and is sensitive to the step size, a robust and accelerative SGD (RA-SG... Read More about Robust standard gradient descent algorithm for ARX models using Aitken acceleration technique.

U-model-based two-degree-of-freedom internal model control of nonlinear dynamic systems (2021)
Journal Article
Li, R., Zhu, Q., Narayan, P., Yue, A., Yao, Y., & Deng, M. (2021). U-model-based two-degree-of-freedom internal model control of nonlinear dynamic systems. Entropy, 23(2), Article 169. https://doi.org/10.3390/e23020169

This paper proposes a U-Model-Based Two-Degree-of-Freedom Internal Model Control (UTDF-IMC) structure with strength in nonlinear dynamic inversion, and separation of tracking design and robustness design. This approach can effectively accommodate mod... Read More about U-model-based two-degree-of-freedom internal model control of nonlinear dynamic systems.

U-Model and U-Control methodology for nonlinear dynamic systems (2020)
Journal Article
Zhang, W., Zhu, Q., Mobayen, S., Yan, H., Qiu, J., & Narayan, P. (2021). U-Model and U-Control methodology for nonlinear dynamic systems. Complexity, 2020(Special issue: Learning and Adaptation for Optimization and Control of Complex Renewable Energy Systems), 1-13. https://doi.org/10.1155/2020/1050254

This study presents the fundamental concepts and technical details of a U-model-based control (U-control for short) system design framework, including U-model realisation from classic model sets, control system design procedures, and simulated showca... Read More about U-Model and U-Control methodology for nonlinear dynamic systems.

Improved gradient descent algorithms for time-delay rational state-space systems: Intelligent search method and momentum method (2020)
Journal Article
Chen, J., Zhu, Q., Hu, M., Guo, L., & Narayan, P. (2020). Improved gradient descent algorithms for time-delay rational state-space systems: Intelligent search method and momentum method. Nonlinear Dynamics, 101, 361-373. https://doi.org/10.1007/s11071-020-05755-8

This study proposes two improved gradient descent parameter estimation algorithms for rational state-space models with time-delay. These two algorithms, based on intelligent search method and momentum method, can simultaneously estimate the time-dela... Read More about Improved gradient descent algorithms for time-delay rational state-space systems: Intelligent search method and momentum method.

A composite feedback approach to stabilize nonholonomic systems with time varying time delays and nonlinear disturbances (2020)
Journal Article
Rasoolinasab, S., Mobayen, S., Fekih, A., Narayan, P., & Yao, Y. (2020). A composite feedback approach to stabilize nonholonomic systems with time varying time delays and nonlinear disturbances. ISA Transactions, 101, 177-188. https://doi.org/10.1016/j.isatra.2020.02.009

In this work, we propose a robust stabilizer for nonholonomic systems with time varying time delays and nonlinear disturbances. The proposed approach implements a composite nonlinear feedback structure in which a linear controller is designed to yiel... Read More about A composite feedback approach to stabilize nonholonomic systems with time varying time delays and nonlinear disturbances.

Morphing airfoils analysis using dynamic meshing (2018)
Journal Article
Abdessemed, C., Yao, Y., Bouferrouk, A., & Narayan, P. P. (2018). Morphing airfoils analysis using dynamic meshing. International Journal of Numerical Methods for Heat and Fluid Flow, 28(5), 1117-1133. https://doi.org/10.1108/HFF-06-2017-0261

© 2018, Emerald Publishing Limited. Purpose: The purpose of this paper is to use dynamic meshing to perform CFD analyses of a NACA 0012 airfoil fitted with a morphing trailing edge (TE) flap when it undergoes static and time-dependent morphing. The s... Read More about Morphing airfoils analysis using dynamic meshing.

U-model enhanced dynamic control of a heavy oil pyrolysis/cracking furnace (2018)
Journal Article
Zhu, Q., Zhao, D., Zhang, S., & Narayan, P. (2018). U-model enhanced dynamic control of a heavy oil pyrolysis/cracking furnace. IEEE Caa Journal of Automatica Sinica, 5(2), 577-586. https://doi.org/10.1109/JAS.2017.7510847

This paper proposes a case study in the control of a heavy oil pyrolysis/cracking furnace with a newly extended U-Model based Pole Placement Controller (U-PPC). The major work of the paper includes: 1. establishing a control oriented nonlinear dynami... Read More about U-model enhanced dynamic control of a heavy oil pyrolysis/cracking furnace.

Ensemble-Empirical-Mode-Decomposition based micro-Doppler signal separation and classification (2017)
Journal Article
Chen, H., Lin, P., Emrith, K., Narayan, P. P., & Yao, Y. (2017). Ensemble-Empirical-Mode-Decomposition based micro-Doppler signal separation and classification. International Journal of Computer Applications in Technology, 56(4), 253-263. https://doi.org/10.1504/IJCAT.2017.10009946

The target echo signals obtained by Synthetic Aperture Radar (SAR) and Ground Moving Target Indicator (GMTI platforms are mainly composed of two parts, the micro-Doppler signal and the target body part signal. The wheeled vehicle and the track vehicl... Read More about Ensemble-Empirical-Mode-Decomposition based micro-Doppler signal separation and classification.

Design of U-PPC-Type II for Nonlinear Systems (2016)
Journal Article
Narayan, P., Zhu, G., Qiu, J., Zhu, Q., Narayan, P. P., & Wright, S. (2016). Design of U-PPC-Type II for Nonlinear Systems. https://doi.org/10.1109/ChiCC.2016.7555008

© 2016 TCCT. In this study, a new U-PPC-Type II (U-model Pole Placement Control Type II) control system design procedure is proposed based on the U-model principle. The objective of a U-PPC-Type II design is to determine a linear controller Gc from a... Read More about Design of U-PPC-Type II for Nonlinear Systems.

Embedding human expert cognition into autonomous UAS trajectory planning (2013)
Journal Article
Campbell, D., Narayan, P., Meyer, P., & Campbell, D. A. (2013). Embedding human expert cognition into autonomous UAS trajectory planning. IEEE Transactions on Cybernetics, 43(2), 530-541. https://doi.org/10.1109/TSMCB.2012.2211349

This paper presents a new approach for the inclusion of human expert cognition into autonomous trajectory planning for unmanned aerial systems (UASs) operating in low-altitude environments. During typical UAS operations, multiple objectives may exist... Read More about Embedding human expert cognition into autonomous UAS trajectory planning.

Development of an autonomous unmanned aerial system to collect time-stamped samples from the atmosphere and localize potential pathogen sources (2011)
Journal Article
Walker, R., Gonzalez, F., Castro, M. P., Narayan, P., & Zeller, L. (2011). Development of an autonomous unmanned aerial system to collect time-stamped samples from the atmosphere and localize potential pathogen sources. Journal of Field Robotics, 28(6), 961-976. https://doi.org/10.1002/rob.20417

This paper presents the hardware development and testing of a new concept for air sampling via the integration of a prototype spore trap onboard an unmanned aerial system (UAS). We propose the integration of a prototype spore trap onboard a UAS to al... Read More about Development of an autonomous unmanned aerial system to collect time-stamped samples from the atmosphere and localize potential pathogen sources.