Area of Specialization
Frequency domain methods for nonlinear systems (the nCOS function or OFRF based methods); Nonlinear vibration & control (with a bio-inspired approach); Robotics—Analysis, Design & Control (Marine robotics, Construction robots and other bio-inspired robots); Robust learning/control methods; Nonlinear system identification and signal processing; Intelligent computing and optimization
Dr X.J. Jing received the B.S. degree from Zhejiang University, Hangzhou, China, in 1998, the M.S. degree and PhD degree in Robotics from Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China, in 2001 and 2005 respectively. He achieved the PhD degree in nonlinear systems and signal processing from the Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, U.K., in 2008.
He is now an Associate Professor with the Department of Mechanical Engineering, the Hong Kong Polytechnic University (PolyU) even since July 2015. Before joining in PolyU as an Assistant Professor in Nov 2009, he was a Research Fellow with the Institute of Sound and Vibration Research, University of Southampton, working on biomedical signal processing. His current research interests include: nonlinear frequency domain methods, nonlinear system identification/control or signal processing, and bio-inspired systems and methods, with applications to vibration isolation or control, robust control, sensor technology, energy harvesting, nonlinear fault diagnosis or information processing, and robotics etc.
Dr Jing received 2016 IEEE SMC Andrew P. Sage Best Transactions Paper Award for the robust control theory in vehicle suspension systems; The passive anti-vibration structure developed by his group received 2017 TechConnect Innovation Award, recognized as the top 20% of all submitted technologies as ranked by the TechConnect Corporate & Investment Partner Committee, which was also reported in many local media press including a specific interview in a TVB program in 2017; He was honored with the 2017 EASD Senior Research Prize in the area of development of methodologies for structural dynamics due to “his important contributions for the analysis and design of nonlinear systems”, awarded by the European Association for Structural Dynamics (EASD), which is an important and prestigious once-3-year event in Europe; The innovative technology BIAVE (bio-inspired anti-vibration exoskeleton for operating hand-held demolition tools) invented by his R&D team received the 2017 Hong Kong CIC Construction Innovation Award (The First Prize in Construction Safety, one of the three First Prizes among more than 120 submissions), which is an important well-recognized once-2-year event in HK with international peers as award committee members each time.
Dr Jing currently serves as Technical Editor of IEEE/ASME Trans. on Mechatronics, Associate Editor of Mechanical Systems and Signal Processing, and also as editorial board members of several other international journals. He was the lead editor of a special issue on “Employing nonlinear benefits in engineering” in the archive journal MSSP in 2018, which is becoming an important and most active research area and has been pursued by Dr Jing in the past years ever since 2005.
Dr Jing is a Senior IEEE member, and actively participate different R&D activities in IEEE community including organizing IEEE conferences and summer camp.
PhD scholarships and RA positions are available from time to time.
You are welcome to contact if you have interest in any topic here.
Candidates from Nonlinear dynamics, Nonlinear vibration, Control and Robotics are highly encouraged.
Research Topics and Selected Publications
* A full list can be referred to the following websites:
Monograph/Books or Book chapters:
- Jing, X. J., & Vakakis, A. F. (Special Issue). Exploring nonlinear benefits in engineering. Mechanical Systems and Signal Processing. 125:1-3, 15, June 2019, https://doi.org/10.1016/j.ymssp.2019.01.059
- Jing X.J. and Lang Z.Q., Frequency Domain Analysis and Design of Nonlinear Systems Based on Volterra Series Expansion — A Parametric Characteristic Approach; XJ Jing and ZQ Lang, Springer International Publishing Switzerland, 2015, XV, 331p.ISBN: 978-3-319-12390-5, DOI: 10.1007/978-3-319-12391-2; http://www.springer.com/978-3-319-12390-5A monograph published by Springer in Feb 2015 which serves a summary of my research on the analysis and design theory and methods of nonlinear systems in the frequency domain in the past years
- Chen, Y., Jing, X., Cheng, L. (Chapter 12), Frequency Domain Analysis and Design of Nonlinear Vehicle Suspension Systems, in Handbook of Vehicle Suspension Control Systems, Edited by Honghai Liu, Huijun Gao & Ping Li, ISBN: 978-1-84919-633-8, IET control book series, 2013, http://www.theiet.org/resources/books/control/hvscs.cfm
- Xingjian Jing (Chapter 1), Vibration Control by Exploiting Nonlinear Influence in the Frequency Domain, in the book Advances on Analysis and Control of Vibrations – Theory and Applications edited by Mauricio Zapateiro de la Hoz and Francesc Pozo, ISBN 978-953-51-0699-9, InTech, Sep 9, 2012. http://www.intechopen.com/books/advances-on-analysis-and-control-of-vibrations-theory-and-applications/vibration-control-by-exploiting-nonlinear-influence-in-the-frequency-domain
- Xingjian Jing (Editor and Chapter 10), Mobile Robots Motion Planning—New Challenges, In-Tech, Vienna, Austria, ISBN: 978-953-7619-01-5, 2008, http://www.intechopen.com/books/show/title/motion_planning (downloaded 5345 times by Feb 2013)
[A] Frequency domain analysis and design of Nonlinear systems
Some cutting-edge progress and results have been done in this particular area related to frequency domain analysis and design of nonlinear systems based on the Volterra series. Several are as follows:
(1) A benchmark parametric characteristic approach-nCOS (initially OFRF)
For nonlinear analysis and design in the frequency domain, I systematically proposed and developed this method, which presents an explicit analytical structure and expression of the output spectrum of nonlinear systems with respect to model parameters of interest (both linear and/or nonlinear components), frequency variable, and excitation amplitude (which are referred to as characteristic parameters) [A1.1-A1.11]. To this aim, I proposed two important operators for abstracting parametric characteristics 2006 [A1.1], and from parameter characteristics to frequency response functions (GFRF or OFRF) there are explicit invertible mapping relationships [A1.4]. Both analytical calculation and numerical methods are therefore developed named as OFRF (output frequency response function) initially or nCOS (nonlinear characteristic output spectrum) method later, based on the parametric characteristics. The first result providing the benchmark technical methods was published in 2006, strengthened or demonstrated in 2008, 2009, 2012, 2014, 2015, 2016, and most results were summarized into a monograph in 2015. Some works done by others later are following these technical lines.
[A1.1] Jing X. J., et.al., The parametric characteristic of frequency response functions for nonlinear systems. International Journal of Control, Vol. 79, No. 12, December 2006, 1552–1564
—This is the first benchmark work to present the parametric characteristic approach for nonlinear analysis and design in the frequency domain with reviewer comments as: “… significant in the area and would merit the literature…”
[A1.2] Jing X. J., et.al., Output Frequency Response Function based Analysis for Nonlinear Volterra Systems. Mechanical Systems and Signal Processing, 22, 102–120, 2008
[A1.3] Jing X. J., et.al., Frequency domain analysis for nonlinear Volterra systems with a general nonlinear output function. International Journal of Control, 81:2, 235 – 251, 2008
—This is to generalize the work in [A1.1] to single input multi output case and system optimization with respect to a performance function can therefore be conducted.
[A1.4] Jing X. J., et.al., Mapping from parametric characteristics to generalized frequency response functions of nonlinear systems. International Journal of Control, Vol. 81, No. 7, 1071–1088, July 2008
[A1.5] Jing X. J., et.al., Parametric Characteristic Analysis for Generalized Frequency Response Functions of Nonlinear Systems, Circuits, Systems and Signal Processing, 28: 699–733, 2009
[A1.6] Jing X. J., et.al., Determination of the analytical parametric relationship for output spectrum of Volterra systems based on its parametric characteristics. Journal of Mathematical Analysis and Applications, 351, 694-706, 2009
[A1.7] Jing X. J., Truncation Order and its Effect in a Class of Nonlinear Systems, Automatica, 48(11), 2978-2985, November 2012 (doi:10.1016/j.automatica.2012.08.004)
—This is to reveal a fundamental and generic relationship between distinct real numbers, based on which accurate estimation of nonlinear output spectrum is generally guaranteed without effect incurred by truncation error
[A1.8] Jing X.J., Nonlinear characteristic output spectrum for nonlinear analysis and design, IEEE/ASME Transaction on Mechatronics, 19(1), 171 – 183, 2014
—This is to systematic present and summarize the parametric characteristic approach based on the technical lines in [A1.1-7], named as the nonlinear characteristic output spectrum (nCOS) based method, taking the analysis and design of vehicle suspension as examples.
[A1.9] Xiao Z.L., Jing X.J.*, An SIMO Nonlinear System Approach to Analysis and Design of Vehicle Suspensions, IEEE/ASME Trans on Mechatronics, 20 (6), 3098 – 3111, 2015
—This is to systematically apply the nCOS method to vehicle suspension systems, innovatively for the first time regarding performance function as system output with a single input multi output approach
[A1.10] Xiao Z.L., Jing X.J.*, A Novel Characteristic Parameter Approach for Analysis and Design of Linear Components in Nonlinear Systems, IEEE Trans on Signal Processing, 64(10), 2528-2540, 2016
[A1.11] Xiao Z.L., Jing X.J.*, Frequency-Domain Analysis and Design of Linear Feedback of Nonlinear Systems and Applications in Vehicle Suspensions, IEEE/ASME Trans on Mechatronics, 21(1), 506-517, 2016
—This is the first work to present the parametric characteristics of model parameters defining linear components in the frequency domain and thus to provide a novel method for designing linear components in a nonlinear systems
(2) General and specific parametric convergence bounds (PCB) guiding the convergence of Volterra series expansion to a nonlinear system: Parametric Convergence Bounds & Parametric Convergence Margins
This was systematically developed in recent years with results published in 2013, 2014, 2015, 2017. These results can clearly say at what parametric range and what frequency range a given nonlinear system has a convergent Volterra series expansion. On the other hand, the results indicate also the appearance of complicated non-Volterra nonlinear dynamics such as chaos or bifurcation with a specific and explicit parameter range. These results solve the long lasting fundamental issue related to the application of Volterra series based methods. Technically, these results adopted the general parametric characteristic approach which was applied to the bound evaluation of output frequency response function of nonlinear systems in 2007, 2008, 2009.
[A2.1] Jing XJ, Xiao ZL, On Convergence of Volterra Series Expansion of a Class of Nonlinear Systems, Asian Journal of Control, 19 (3), 1089-1102, 2017
[A2.2] Xiao Z.L., Jing X.J.*, An SIMO Nonlinear System Approach to Analysis and Design of Vehicle Suspensions, IEEE/ASME Trans on Mechatronics, 20 (6), 3098 – 3111, 2015
[A2.3] Xiao Z.L., Jing X.J.*, et.al., Estimation of Parametric Convergence Bounds for Volterra Series Expansion of Nonlinear Systems, Mechanical Systems and Signal Processing, 45(1), 28-48, 2014
[A2.4] Xiao Z.L., Jing X.J.*, et.al., Parameterized Convergence Bounds for Volterra Series Expansion of NARX Models, IEEE Transaction on Signal Processing, 61 (20), 5026 – 5038, 2013
—This is for the first time to reveal a parametric bound of the convergence of Volterra series expansion to a given parametric NARX model
[A2.5] Jing X. J., et.al., Frequency-Dependent Magnitude Bounds of the Generalized Frequency Response Functions for NARX model, European Journal of Control, 15(1), 2009
[A2.6] Jing X. J., et.al., Magnitude bounds of generalized frequency response functions for nonlinear Volterra systems described by NARX model. Automatica, 44, 838-845, 2008
[A2.7] Jing X. J., et.al., New Bound Characteristics of NARX Model in the Frequency Domain. International Journal of Control, Vol 80, No1, 140-149, 2007
(3) Applications to vibration control and signal processing: Exploring nonlinear benefits in Engineering
I started the study on “Exploring nonlinear benefits in engineering” ever since 2005 through a series of application of the methods above for nonlinear vibration control, nonlinear damping design, system identification, fault detection and so on. In vibration control, it is theoretically shown that nonlinear damping has very good advantage over linear damping with results published in 2006, 2008, 2009, 2011, 2013. It is for the first time revealed that the output frequency response would take an alternating series with respect to the concerned characteristic parameters for convergence and beneficial effect 2011 (based on the parametric characteristic approach) [A3.2]. Some novel output frequency characteristics were also clearly discussed 2010 [A3.3]. I developed a general technique for easily considering nonlinear damping effect, i.e., the effect for w<1, w=1 and w>1, well with the frequency domain approach above 2009 [A3.4]. It is noticed that, the method was well used in many other publications later on.
[A3.1] Xiao Z.L., Jing X.J.*, et.al., The Transmissibility of Vibration Isolators with Cubic Nonlinear Damping under Both Force and Base Excitations, Journal of Sound and Vibration, 332(5), 1335–1354, 4 March 2013, http://dx.doi.org/10.1016/j.jsv.2012.11.001
[A3.2] Jing X. J., et.al., Nonlinear influence in the frequency domain: Alternating series, Systems and Control Letters, 60 (5), 295-309, 2011
—This for the first time presents a unique point of view — alternative series– into nonlinear influence in dynamic systems and reveals the beauty of nonlinear effect in the frequency domain
[A3.3] Jing X.J., et.al., Output Frequency Properties of Nonlinear Systems, International Journal of Non-Linear Mechanics, 45(7), Sep 2010, p 681-690
—This exactly reveals the output frequency properties due to super-harmonics and modulation of input frequencies
[A3.4] Jing X. J. et.al., Frequency Domain Analysis of a Dimensionless Cubic Nonlinear Damping System Subject to Harmonic Input, Nonlinear Dynamics, 58: 469–485, 2009
[A3.5] Jing X.J., et.al. Frequency Domain Analysis for Suppression of Output Vibration from Periodic Disturbance using Nonlinearities. Journal of sound and vibration 314, 536–557, 2008
[A3.6] Jing X.J., et. al., Frequency domain analysis based nonlinear feedback control for suppressing periodic disturbance, The 6th World Congress on Intelligent Control and Automation, June 21–23, Dalian, China, 2006
—This actually the first preliminary work in this series of studies for employing nonlinear benefits in engineering systems and also starting the study of the parametric characteristics approach
[A3.7] Jing XJ, et. al., Output Frequency Response Function for NARX model of Nonlinear Volterra Systems. Proceedings of the 12th Chinese Automation & Computing Society Conference in the UK, Loughborough, England, 16 September 2006
[B] Nonlinear Vibration Isolation/Suppression/Control: A bio-inspired approach
In recent years, we focus more on “Employing nonlinear benefits” in vibration control. The one issue is about how to realize beneficial nonlinearity in vibration control. It is known theoretically from out past research studies that some special nonlinearity can take very beneficial role in vibration control [A3.1-8]. Realization of these beneficial nonlinearities using active control methods would always meet some drawbacks such as energy /development /manufacturing /maintenance cost and/or actuators’ saturation etc. The best way is of course to achieve these nonlinearities at system or structure design stage using purely passive ways.
To this aim, we developed a bio-inspired limb-like or X-shaped structure approach ever since 2010 starting from a MSC thesis [B1.12]. It is noticed that animal or insect can always have very good body control during walking, running or jumping on even rough terrain. Their leg or limb skeleton usually takes very similar X-like, Z-like, quadrilateral shape, triangle shape, or any other similar shapes. This structure or its variants (with quadrilateral or polygon or triangle shape) can also be found in cranial bone and materials etc. These greatly motivate our current research efforts. It is revealed that the bio-inspired X-shaped structure can provide very beneficial nonlinear stiffness and damping characteristics [B.1.1, B1.6-11]] and can be applied extensively to various critical engineering issues, including vibration control [B1.1- B1.3, B1.13], energy harvesting [B3.1-4], and sensor design [B2.1-3] etc. Even though in active vibration control, the bio-inspired nonlinear dynamics can also help save energy cost [B1.2]. Robotic design benefits from the bio-inspired passive structure for advantageous body suspension as well. Potentially, the X-shaped structure approach presents an innovative technology to extensive engineering issues for vibration control. Based on these, a novel human body inspired vibration isolation system is also proposed for the first time in [B1.14], which is shown to be capable of presenting beneficial passive adjustable nonlinear stiffness, nonlinear damping and nonlinear inertia (or equivalent mass) simultaneously!
The X-shaped structure is inspired from animal leg/limb skeleton and takes a truss or scissor-like shape as mentioned above, which is already adopted in many engineering practices as different supporting structures. The joint of the X-shaped structure can be rotational joints with or without bearings or just rotational joint with elastic materials. There are many different forms in practical designs. However, it should be emphasized that, the fantastic nonlinear stiffness and damping characteristics are only known recently due to the series of pioneering works done by us, and there are still more amazing nonlinear dynamic features yet to be explored. This is similar to the fact that we are familiar with and even use our brain or body to do many things everyday but we really understand them a little!
The bio-inspired limb-like or X-shaped structures and applications
[B1.1] Bian J, Jing XJ, Superior nonlinear passive damping characteristics of the bio-inspired limb-like or X-shaped structure, to appear in Mechanical Systems and Signal Processing, 2018
[B1.2]Feizhou Hu, Jing XJ*, A 6-DoF passive vibration isolator based on Stewart structure with X-shaped legs, Nonlinear Dynamics, 91 (1), 157-185, 2018
[B1.3] Huihui Pan, Jing XJ*, Weichao Sun, and Huijun Gao, A Bio-inspired Dynamics-Based Adaptive Tracking Control for Nonlinear Suspension Systems, IEEE Transactions on Control Systems Technology, 26(3), 903-914, MAY 2018
—It is revealed for the first time that the bio-inspired nonlinearity based tracking control in vehicle suspension can save energy cost
[B1.4] Wu Z, Jing XJ*, Sun B, Li F, A 6DOF Passive Vibration Isolator Using X-shape Supporting Structures, Journal of Sound and Vibration, 380, 90-111, 2016
[B1.5] Sun X.T., Jing X.J.*, A nonlinear vibration isolator achieving high-static-low-dynamic stiffness and tunable anti-resonance frequency band, Mechanical Systems and Signal Processing, 80, 166-188, 2016
[B1.6] Wu Z, Jing XJ*, Bian J, Li F, and Allen R, Vibration isolation by exploring bio-inspired structural nonlinearity, Bioinspiration & Biomimetics, 10 (5), 056015-056015, 2015
—This is the first time that we presented and formulated the work and ideas in the context of bio-inspired methodologies. This is actually the true source where the idea came from, although it was initially named as scissor-like structure.
[B1.7] Liu CC; Jing X.J. *; Chen Z, Band Stop Vibration Suppression Using a Passive X-Shape Structured Lever-Type Isolation System, Mechanical Systems and Signal Processing, 68, 342-353, 2016
[B1.8] Sun X.T., Jing X.J.*, Analysis and Design of a Nonlinear Stiffness and Damping System with a Scissor-Like Structure, Mechanical Systems and Signal Processing, Vol 66–67, Pages 723–742, January 2016
[B1.9] Liu CC, Jing XJ*, Vibration Isolation Using a Hybrid Lever-Type Isolation System with an X-Shape Supporting Structure, International Journal of Mechanical Sciences, Vol 98, Pages 169–177, July 2015
[B1.10] Sun X.T., Jing X.J.*, Multi-Direction Vibration Isolation with Quasi-Zero Stiffness by Employing Geometrical Nonlinearity, Mechanical Systems and Signal Processing, Vol 62–63, Pages 149–163, October 2015
[B1.11] Sun X.T., Jing X.J.*, Xu J., Cheng L., Vibration Isolation via a Scissor-like Structured Platform, Journal of Sound and Vibration, 333(9), 2404-2420, 2014
—This is the first work formally published in this series of studies by following the idea in [B1.12]
[B1.12] B Xue, XJ Jing*, Simulation study on scissor-like element vibrations, MSC thesis, Department of Mechanical Engineering, The Hong Kong Polytechnic University, 2013 (submitted in 2012)
— This is actually the first work starting this series of study ever since 2010, and the structure is initially named by the student as scissor-like element: http://theses.lib.polyu.edu.hk/handle/200/6907
[B1.13] H Dai, X Jing, Y Wang, X Yue, J Yuan, Post-capture vibration suppression of spacecraft via a bio-inspired isolation system, Mechanical Systems and Signal Processing 105, 214-240, 2018
[B1.14] X Feng, X Jing*, Xiao Feng and Xingjian Jing, Human Body Inspired Vibration Isolation: Beneficial Nonlinear Stiffness, Nonlinear Damping & Nonlinear Inertia, Mechanical Systems and Signal Processing, 117: 786-812, 15 Feb 2019
—It is for the first time to develop a human-body inspired passive vibration isolation system and revealed for the first time that the rotation of arms can increase equivalent body mass and vibration damping
The quasi-zero or zero-stiffness based vibration sensors:
A novel concept for absolute vibration displacement measurement; The quasi-zero or zero-stiffness with passive structure design is innovatively explored and employed which can create an absolute stable point in a broadband frequency domain and thus can be employed for vibration measurement, not only in static environments but also in moving platforms. This presents an innovative way to solve the issue for absolute vibration displacement measurement existing in the related field for many years.
[B2.1] Jing X.J.*, Wang Y, Li QK, Sun X.T., Design of a Quasi-Zero-Stiffness based Sensor System for Measurement of Absolute Vibration Displacement of Moving Platforms, Smart Materials and Structures, 25(9), 2016
[B2.2] Sun X.T., Jing X.J.*, Xu J., Cheng L., A 3D Quasi-Zero-Stiffness Based Sensor System for Absolute Motion Measurement and Application in Active Vibration Control, IEEE Transactions on Mechatronics, 20 (1), 254 – 262, 2015
[B2.3] Sun X.T., Jing X.J.*, Xu J., Cheng L., A Quasi-Zero Stiffness based Sensor System in Vibration Measurement, IEEE Transactions on Industrial Electronics, 61(10), 5606 – 5614, 2014
[B2.4] Pan H, Jing X J, Sun W, Li Z, Analysis and design of a bio-inspired vibration sensor system in noisy environment, to appear in IEEE/ASME Transactions on Mechatronics, 2018
[B2.5] Z Li, X Jing, J Yu, Fault Detection Based on a Bio-inspired Vibration Sensor System, IEEE Access, 2017 10.1109/ACCESS.2017.2785406
[B2.6] Jing X.J.*, Wang Y, Li QK, Sun X.T., ‘Design of a Quasi-Zero-Stiffness based Sensor System for Measurement of Absolute Vibration Displacement of Moving Platforms, Smart Materials and Structures, 25(9), 2016
—This is the first prototype of the quasi-zero stiffness based sensor system for directly and accurately measuring absolute vibration displacement in moving platform
Nonlinear Energy Harvesting by employing nonlinear properties and structural benefits
[B3.1] Qian JG, Jing XJ*, Wind-driven Hybridized Triboelectric-Electromagnetic Nanogenerator and Solar Cell as a Sustainable Power Unit for Self-powered Natural Disaster Monitoring Sensor Networks, Nano Energy, 52:78-87, October 2018
[B3.2] Wei CF, K Zhang, C Hu, Y Wang, H Taghavifar, Jing XJ, A Tunable Nonlinear Vibrational Energy Harvesting System with Scissor-like Structure, accepted by Mechanical Systems and Signal Processing, June 2018
[B3.3] Li M, Zhou JJ, Jing XJ*, Improving Low-Frequency Piezoelectric Energy Harvesting Performance with Novel X-structured Harvesters, Nonlinear Dynamics, 94 (2), 1409-1428, Oct 2018
[B3.4] Wei CF, Jing XJ*, A comprehensive review on vibration energy harvesting: modelling and realization, Renewable & Sustainable Energy Reviews, 74(1-18), 2017
[B3.5] Wei CF, Jing XJ*, Vibrational energy harvesting by exploring structural benefits and nonlinear characteristics, Communications in Nonlinear Science and Numerical Simulation, 48: 288–306, 2017
[B3.6] Liu CC, Jing XJ*, Nonlinear Vibration Energy Harvesting with Adjustable Stiffness, Damping and Inertia, Nonlinear Dynamics, 88(1), 79–95, 2017 (doi:10.1007/s11071-016-3231-1)
[B3.7] Liu CC, Jing XJ*, Vibration Energy Harvesting with a Nonlinear Structure, Nonlinear Dynamics, 84(4), 2079-2098, 2016
[C] Fault detection/diagnosis based on vibration signals
Vibration signals based fault detection or diagnosis is done recently. We focus on development of fault diagnosis methods for complex structures with least prior knowledge, less testing data and other practical requirements. A recent work is done for bolt loosening of a satellite-like structure with a “virtual beam” approach, which actually presents a nonlinear feature dynamics based method under further investigation now. We are also developing some new fault-related nonlinear features by using our research results in the frequency-domain nonlinear analysis and design.
The virtual beam approach: nonlinear feature dynamics
[C1.1] Wang H, Jing XJ, Fault diagnosis of sensor networked structures with multiple faults using a virtual beam based approach, Journal of Sound and Vibration, Volume 399, Pages 308-329, 7 July 2017
[C1.2] Wang H, Jing XJ, Vibration signal based fault diagnosis in complex structures: A beam-like-structure approach, Structure Health Monitoring, first published online: May 2, 2017 (DOI: 10.1177/1475921717704383)
[C1.3] Wang H, Jing XJ, A Sensor Network based Virtual Beam-like Structure Method for Fault Diagnosis and Monitoring of Complex Structures with Improved Bacterial Optimization, Mechanical Systems and Signal Processing, 84, 15-38, 2017
Nonlinear frequency-domain features: SOOS more robust and more reliable
[C2.1] Q Li, X Jing*, Fault Diagnosis of Bolt Loosening in Structures with a Novel Second-Order Output Spectrum based Method, Structural Health Monitoring, 21 Mar 2019 https://doi.org/10.1177/1475921719836379
[C2.2] Q Li, X Jing, A second-order output spectrum (SOOS) approach for fault detection of bolt loosening in a satellite-like structure with a sensor chain, Nonlinear Dynamics, Volume 89, Issue 1, pp 587–606, July 2017
[C2.3] Jing X.J.*,Li QK, A Nonlinear Decomposition and Regulation Method for Nonlinearity Characterization, Nonlinear Dynamics, 83 (DOI: 10.1007/s11071-015-2408-3), 1355-1377, 2016
[D] Nonlinear systems: control and identification
We have interest in development of robust control theory or methods in general to solve critical theoretical and/or practical issues focusing more on application oriented control methods [D.1-5]. For system identification, we developed a new robust control approach, which casts the traditional identification problem with input output data into a robust control or robust output feedback control problem and thus achieve more powerful and robust identification performance [D.7-8].
[D.1] Chengwei Wu; Jianxing Liu; Xingjian Jing; Hongyi Li; Ligang Wu, Adaptive Fuzzy Control for Nonlinear Networked Control Systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, Volume: 47, Issue: 8, 2420 – 2430, Aug. 2017
—highly cited papers and hot papers in ISI web of knowledge 2018
[D.2] H Li, C Wu, XJ Jing, L Wu, Fuzzy tracking control for nonlinear networked systems, IEEE trans on Cybernetics, 47(8), 2020 – 2031, Aug. 2017
[D.3] Liu CC; Jing XJ *, Daley S, Li FM, Recent Advances in Micro-Vibration Isolation, Mechanical Systems and Signal Processing, 56, 55–80, 2015
—highly cited papers and hot papers in ISI web of knowledge 2018
[D.4] Hongyi Li, Jing XJ, H.K. Lam, Peng Shi, Fuzzy Sampled-Data Control for Uncertain Vehicle Suspension Systems, IEEE Trans. on Systems, Man and Cybernetics, Part B: Cybernetics, 44(7), 1111 – 1126, July, 2014
—highly cited papers and hot papers in ISI web of knowledge 2015,2016,2017,2018
— The IEEE SMC best transaction paper Award 2016
[D.5] Xing-Jian Jing, Da-Long Tan, Yue-Chao Wang. An LMI Approach to Stability of Systems with Severe Time-Delay. IEEE trans. Automatic Control. 49(7), July, 2004
- A novel and systematic robust control approach to nonlinear system identification and learning/classification problems has been developed in the past years, which casts the traditional identification/learning problems with input output training data into a robust control or robust output feedback control problem and thus achieve more powerful and robust identification performance
[D.6] Hanwen Ning, Guangyan Qing, Xingjian Jing*, Identification of Nonlinear Spatiotemporal Dynamical Systems with Non-Uniform Observations Using Reproducing-Kernel based Integral Least Square Regulation, IEEE Trans. on Neural Networks and Learning Systems, 27(11), 2399 – 2412, 2016, DOI: 10.1109/TNNLS.2015.2473686
[D.7] Xingjian Jing, Li Cheng, An Optimal-PID Control Algorithm for Training Feedforward Neural Networks, IEEE Trans. on Industrial Electronics, 60(6), 2273-2283, 2013
[D.8] Xingjian Jing, Robust Adaptive Learning of Feedforward Neural Networks via LMI Optimizations. Neural Networks, 31:33-45, July, 2012
[D.9] Hanwen Ning, Xingjian Jing*, Li Cheng, Online Identification of Nonlinear Spatio-Temporal Systems Using Kernel Learning Approach, IEEE Trans. on Neural Networks, 22(9), 1381- 1394, 2011
[D.10] Hanwen Ning, Guangyan Qing, Tianhai Tian, Xingjian Jing*, Online identification of nonlinear stochastic spatiotemporal system with multiplicative noise by robust optimal control based kernel learning method, IEEE trans. On Neural Networks and Learning Systems, 30(2):2162-2388, Feb 2019 10.1109/TNNLS.2018.2843883
[E] Robotics: analysis, design and control
We focus on bio-inspired robots, construction robots, marine robots, and other novel robotic applications such as exoskeleton technology, security inspection robots or structural health monitoring robots etc, and related control, navigation and motion planning methods.
[E.1] Sun B, Jing XJ, A tracked robot with novel bio-inspired passive “legs”, Robotics and biomimetics 4 (1), 18, 2017
[E.2] Xing-Jian Jing, Behavior dynamics based motion planning of mobile robots in uncertain dynamic environments, Robotics and Autonomous Systems 53 (2005) 99–123
[E.3] Xing-Jian Jing, Yue-Chao Wang, Da-Long Tan. Artificial coordinating field and its application to robot motion-planning. Science in China (Series: E), Vol34, No.9 in Chinese//Vol47, No.5 in English, 2004,pp577-595
[E.4] Xing-Jian Jing, Yue-Chao Wang, Da-Long Tan. Rational genetic algorithm and its application in motion planning of multi-mobile robots. Acta Automatica Sinica (in Chinese), 28(6), 2002：869-875
Some media news
The 1st Prize for Construction Safety
in Hong Kong CIC Construction Innovation award 2017 – an important once-2-year event
2017 EASD Senior Research Prize in Europe
– a prestigious once-3-year event
2017 TechConnect Innovation Award
(top 20% to have the chance)
2016 IEEE SMC Andrew P. Sage Best Transactions Paper Award
Dynamics and Control
Nonlinear Dynamics, Vibration and Control (NDVC)