Awards and Scholarships
- IEEE Into Focus Photo Contest winner, October, 2017 https://ieee-into-focus.org/winners/
- IEEE IES Student Paper Travel Assistance winner, IEEE International Conference on Mechatronics (ICM 2017), Gippsland, Australia, Feb. 13-15, 2017 https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7956333
- Australian Postgraduate Award 2016 - 2018
- UTS Research Excellence Scholarship 2016 - 2018
- UTS FEIT Top-up Scholarship 2015 - 2016
- BUET Board & Technical Scholarship 2004 - 2009
- Smart Materials and Structures
- Magnetorheological Materials
- Sliding Mode Control
- Electromechanical Automation 48531 (Autumn 2015 - present)
- Introduction to Electrical Engineering 48510 (Autumn 2015 - present)
- Advanced Control 48580 (Autumn 2015 - present)
- Introductory Control 48560 (Spring 2018 - present)
Building structures, subject to dynamic loadings or external disturbances, may undergo destructive vibrations and encounter different degrees of deformation. Modeling and control techniques can be applied to effectively damp out these vibrations and maintain structural health with a low energy cost. Smart structures embedded with semi-active control devices, offer a promising solution to the problem. The smart damping concept has been proven to be an effective approach for input energy shaping and sup- pressing unwanted vibrations in structural control for buildings embedded with magnetorheological fluid dampers (MRDs). In this paper, the dissipation energy in MRD is studied by using results from induced hysteretic effect of structural vibrations while the fluid is placed under a controlled magnetic field. Then, a frequency-shaped second-order sliding mode controller (FS2SMC) is designed along with a low-pass filter to implement the desired dynamic sliding surface, wherein the frequency responses of the hysteretic MRD is represented by its magnitude and phase describing functions. The proposed controller can thus shape the frequency characteristics of the equivalent dynamics for the MRD-embedded structure against induced vibrations, and hence, dissipate the energy flow within the smart devices to prevent structural damage. Simulation results for a 10-floor building model equipped with current-controlled MRDs, subject to horizontal seismic excitations validate the proposed technique for low-energy structures with smart devices. The closed-loop performance and comparison in terms of energy signals indicate that the pro- posed method allows not only to reduce induced vibrations and input energy, but also its spectrum can be adjusted to prevent natural modes of the structure under external excitations.
Yu, Y, Li, Y, Li, J, Gu, X & Royel, S 2018, 'Nonlinear Characterization of the MRE Isolator using Binary-Coded Discrete CSO and ELM', International Journal of Structural Stability and Dynamics, vol. 18, no. 8.View/Download from: UTS OPUS or Publisher's site
© 2018 World Scientific Publishing Company Magnetorheological elastomer (MRE) isolator has been proved as a promising semi-active control device for structural vibration control. For its engineering application, developing an accurate and robust model is definitely necessary and also a challenging task. Most of the present models, belonging to parametric models, need to identify various model parameters and sometimes are not capable of perfectly capturing the unique characteristics of the device. In this work, a novel nonparametric model is proposed to characterize the inherent dynamics of the MRE isolator with the features of hysteresis and nonlinearity. Initially, dynamic tests are conducted to evaluate the performance of the isolator under various loading conditions, including harmonic, random, and seismic excitations. Then, on the basis of the captured experimental results, a hybrid learning method is designed to forecast the nonlinear responses of the device with known external inputs. In this method, a type of single hidden layer feed-forward network, called extreme learning machine (ELM), is developed to forecast the nonlinear responses (shear force) of the device with captured velocity, displacement, and current level. To obtain optimal performance of the developed model, an improved binary-coded discrete cat swarm optimization (BCDCSO) method is adopted to select optimal inputs and neuron number in the hidden layer for the network development. The performance of the proposed method is verified through the comparison between experimental results and model predictions. Due to the noise influence in the practical condition, the robustness of the proposed method is also validated via adding noise disturbance into the supplying currents. The results show that the proposed method outperforms the standard ELM in terms of characterization of the MRE isolator, even though the captured responses are polluted with external measurement noises.
Ha, Q, Sayed, R, Li, J & Li, Y 2016, 'Hysteresis Modeling of Smart Structure MR Devices using Describing Functions', IEEE-ASME Transactions on Mechatronics, vol. 21, no. 1, pp. 44-50.View/Download from: UTS OPUS or Publisher's site
Magneto-rheological (MR) devices have been quite promising for semi-active control thanks to their capability of adjusting structural parameters, under a low-power control signal, to effectively withstand severe dynamic loadings including seismic events. MR devices, using visco-elastic and ferromagnetic materials, are subject to hysteresis, which may degrade the performance of smart structures. Therefore, this multi-valued nonlinearity needs to be properly modelled and characterized for control and health monitoring. As engineering structures operate as low-pass filter in normal conditions, it is suitable to use the classical describing function (DF) method for modelling and analysis of the hysteretic behaviors in MR device-based smart structures. Data obtained from characterizing tests are recorded in look-up tables to obtain the DFs for these devices, using a curve-fitting technique. The proposed DFs are then useful in structural frequency analysis. Experimental results are reported for a steel beam with MR pin joints subject to quake-induced vibrations provided by a shake table.
Yu, Y, Li, Y, Li, J, Gu, X, Royel, S & Pokhrel, A 2016, 'Nonlinear and hysteretic modelling of magnetorheological elastomer base isolator using adaptive neuro-fuzzy inference system', Applied Mechanics and Materials, vol. 846, pp. 258-263.View/Download from: UTS OPUS or Publisher's site
Magnetorheological elastomer (MRE) base isolator is a semi-active control device which has currently obtained increasing attention in the field of vibration control of civil structures. However, the inherent nonlinear and hysteretic response of the device is regarded as a challenge
aspect for using the smart device to realize the high performance. Therefore, an accurate and robust
model is essential to make full use of these unique features for its engineering applications. In this
paper, to solve this issue, adaptive neuro-fuzzy inference system (ANFIS) is utilized to characterize
the dynamic behavior of the device. In this proposed model, the inputs are historical displacements
and applied current of the device while the output is the shear force generated. To validate its forecast performance, the ANFIS model is also compared with some conventional models. Finally, the result verifies that ANFIS has the best perfection ability among existing MRE-based device models.
Yu, Y, Royel, S, Li, J, Li, Y & Ha, Q 2016, 'Magnetorheological elastomer base isolator for earthquake response mitigation on building structures: modeling and second-order sliding mode control', Earthquake and Structures, vol. 11, no. 6, pp. 943-966.View/Download from: UTS OPUS or Publisher's site
Recently, magnetorheological elastomer (MRE) material and its devices have been developed and attracted a good deal of attention for their potentials in vibration control. Among them, a highly adaptive base isolator based on MRE was designed, fabricated and tested for real-time adaptive control of base isolated structures against a suite of earthquakes. To perfectly take advantage of this new device, an accurate and robust model should be built to characterize its nonlinearity and hysteresis for its application in structural control. This paper first proposes a novel hysteresis model, in which a nonlinear hyperbolic sine function spring is used to portray the strain stiffening phenomenon and a Voigt component is incorporated in parallel to describe the solid-material behaviours. Then the fruit fly optimization algorithm (FFOA) is employed for model parameter identification using testing data of shear force, displacement and velocity obtained from different loading conditions. The relationships between model parameters and applied current are also explored to obtain a current-dependent generalized model for the control application. Based on the proposed model of MRE base isolator, a second-order sliding mode controller is designed and applied to the device to provide a real-time feedback control of smart structures. The performance of the proposed technique is evaluated in simulation through utilizing a three-storey benchmark building model under four benchmark earthquake excitations. The results verify the effectiveness of the proposed current-dependent model and corresponding controller for semi-active control of MRE base isolator incorporated smart structures.
Royel, S, Ha, QP & Aguilera, RP 2018, 'Frequency-Shaped Second-Order Sliding Mode Control for Smart Suspension Systems', 2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018, International Conference on Control, Automation, Robotics and Vision, IEEE, Singapore, Singapore, pp. 907-912.View/Download from: UTS OPUS or Publisher's site
© 2018 IEEE. Design of a frequency-shaped second-order sliding mode (FS2SM) controller is demonstrated by means of exploiting second-order low-pass filter (LPF) to model the dynamic sliding surface to shape the frequency characteristics of the equivalent dynamics. The proposed technique is numerically verified in the simulation of a half-car model (HCM) with inbuilt active hydraulically interconnected suspension (HIS) system. The closed-loop performances confirm that inclusion of an appropriate filter in the control scheme allows not only to reduce the roll angle but also its spectrum can be shaped.
Royel, SA & Ha, Q 2017, 'Frequency Shaped Sliding Mode Control of Magnetorheological Smart Structure Systems', 2017 IEEE International Conference on Mechatronics (ICM), IEEE International Conference on Mechatronics, IEEE, Churchill, VIC, Australia, pp. 117-122.View/Download from: UTS OPUS or Publisher's site
This paper addresses the problem of controlling
multi-degree-of-freedom (MDoF) smart structures integrated
with magnetorheological (MR) devices that are subject to non-
linearity and hysteresis. A fluid based device, namely the MR
damper (MRD), is considered in this study, where hysteresis
appears in both force-displacement and force-velocity relation-
ships of the smart device. Such nonlinear dynamics limit the
performance of the device when embedded in smart structures.
The describing function (DF) technique is employed using only
the displacement as input to the nonlinearity to characterize
this multivalued mechanism. By incorporating the proposed
model into the system dynamics, frequency shaped sliding mode
control (FSSMC) is developed to achieve structural resilience
and sustainability against nonlinearities, modeling uncertainties,
and disturbances from dynamic loadings. Frequency response
functions (FRFs) are obtained for possible analysis of system
conditional assessment in the frequency domain. Simulations
are reported for a three-story building model integrated with
two identical current-dependent MR dampers subject to one-
dimensional quake-induced vibration to investigate lateral dy-
namic responses, as produced by earthquakes or strong winds.
Yu, Y, Li, Y, Li, J, Gu, X & Royel, S 2016, 'Dynamic modeling of magnetorheological elastomer base isolator based on extreme learning machine', Mechanics of Structures and Materials: Advancements and Challenges - Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM24 2016, Australian Conference on the Mechanics of Structures and Materials, CRC press, Perth, Australia, pp. 703-708.View/Download from: UTS OPUS
© 2017 Taylor & Francis Group, London. This paper presents a novel modeling method to describe the nonlinear and hysteretic characteristics of Magnetorheological Elastomer (MRE) isolator, which is a semi-active control device and used in vibration control of engineering structures such as vehicle suspension system, offshore platform and built infrastructure. In the proposed method, a new single-hidden-layer feed-forward neural network algorithm named Extreme Learning Machine (ELM) is adopted to set up the model, in which the captured responses such as displacement and velocity of the device together with applied current level are employed as model inputs while the model output is the shear force generated according to the external excitation. Finally, the experimental data are utilized to validate the performance of the proposed method.
Royel, S, Yu, Y, Li, Y, Li, J & Ha, QP 2015, 'A Hysteresis Model and Parameter Identification for MR Pin Joints using Immune Particle Swarm Optimization', Proceedings of the 2015 IEEE International Conference on Automation Science and Engineering., IEEE Conference on Automation Science and Engineering, IEEE, Gothenburg, Sweden, pp. 1319-1324.View/Download from: UTS OPUS or Publisher's site
A novel hybrid model is proposed in this paper to
describe the highly-nonlinear hysteretic relationship between
the torque and angular velocity in a magnetorheological pin
joint (MRP). The MRP’s hysteresis loop is modelled by a mixture
of hyperbolic and Gaussian functions using the curve fitting
technique, resulting in a significant reduction of the model
parameters. To identify the model parameters, an immune
particle swarm optimization (IPSO) algorithm is employed
using torque-angular displacement/velocity experimental data
recorded under various loading conditions. To demonstrate
the accuracy of the proposed model and the effectiveness of
parameter identification process, characterization test data of
the smart pin torque and angular velocity are utilized for
Royel, SA, Movassaghigilani, S, Kwok, NM & Ha, QP 2012, 'Smart Structures Using MR Dampers with Second Order Sliding Mode Control', Proc. 2012 International Conference on Control, Automation and Information Sciences, International Conference on Control, Automation and Information Sciences, IEEE, Ho Chi Minh City, Vietnam, pp. 170-175.View/Download from: UTS OPUS or Publisher's site
This paper presents the design of a second-order sliding mode controller using Magneto-rheological (MR) fluid dampers integrated in smart structures to sustain external earthquakes or dynamic loadings. The advantages of these structures come from the use of semi-active devices for the fail safe operations and low energy consumption. However, the control of MR dampers is hindered by their nonlinear forcedisplacement and hysteresis force-velocity responses which usually affect control performance. On the other hand, the required yielding force to suppress structural vibrations results from the magnetization of the fluid particle suspension in the damper housing via the controlled current. To robustly control the dampersâ magnetization current, the sliding mode control methodology is adopted. Simulation results and evaluation are included to show effectiveness of the proposed approach.