Steven W Su

University of Technology Sydney | UTS · Faculty of Engineering and Information Technology

This paper developed an efficient method for calibrating triaxial MEMS gyroscopes, which can be effectively utilized in the field environment. The core strategy is to utilize the criterion that the dot product of the measured gravity and the rotation speed in a fixed frame remains constant. To eliminate the impact of external acceleration, the cali...

This study introduces a novel approach to robot-assisted ankle rehabilitation by proposing a Dual-Agent Multiple Model Reinforcement Learning (DAMMRL) framework, leveraging multiple model adaptive control (MMAC) and co-adaptive control strategies. In robot-assisted rehabilitation, one of the key challenges is modelling human behaviour due to the co...

This paper aims to develop a new human-machine interface to improve rehabilitation performance from the perspective of both the user (patient) and the machine (robot) by introducing the co-adaption techniques via model-based reinforcement learning. Previous studies focus more on robot assistance, i.e., to improve the control strategy so as to fulfi...

Objective: Sleep apnea is a common sleep breathing disorder that can significantly decrease sleep quality and have major health consequences. It is diagnosed based on the apnea hypopnea index (AHI). This study explored a novel, generalized algorithm for the automatic diagnosis of sleep apnea employing airflow (AF) and oximetry (SpO2) signals. App...

Apples are one of the most widely planted fruits in the world, with an extremely high annual production. Several issues should be addressed to avoid the damaging of samples during the quality grading process of apples (e.g., the long detection period and the inability to detect the internal quality of apples). In this study, an electronic nose (e-n...

In the electronic nose (e-nose), a stable feature representation of the gas sensor's response is a key step to realize subsequent odor identification algorithms. However, the noises in gas sensors hinder the acquisition of such features. In order to solve this problem, this article proposes a stable feature extraction algorithm which takes the impu...

As with any profitable industry, the whisky market is subject to fraudulent activity, including adulteration. An expert can identify the differences between whiskies, but it is difficult for the majority of consumers to differentiate fraudulent beverages. Complex chemical and analytical analyses have been able to detect the differences between whis...

Reach-and-grasp is one of the most fundamental activities in daily life, while few rehabilitation robots provide integrated and active training of the arm and hand for patients after stroke to improve their mobility. In this study, a novel hybrid arm-hand rehabilitation robot (HAHRR) was built for the reach-and-grasp task. This hybrid structure con...

This paper aims to improve the performance of an electromyography (EMG) decoder based on a switching mechanism in controlling a rehabilitation robot for assisting human-robot cooperation arm movements. For a complex arm movement, the major difficulty of the EMG decoder modeling is to decode EMG signals with high accuracy in real-time. Our recent st...

Objective.Noise-assisted Multivariate Empirical Mode Decomposition (NA-MEMD) based Causal Decomposition depicts a cause and effect relationship that is not based on the term of prediction, but rather on the phase dependence of time series. Here, we present the NA-MEMD based Causal Decomposition approach according to the covariation and power views...

One-shot neural architecture search (NAS) has recently become mainstream in the NAS community because it significantly improves computational efficiency through weight sharing. However, the supernet training paradigm in one-shot NAS introduces catastrophic forgetting. To overcome this problem of catastrophic forgetting, we formulate supernet traini...

This paper presented an efficient electronic nose (e-nose) system, named “NOS.E”, for odour analysis and assessment. In addition to the reliable hardware and software designs, an airflow intake system is implemented to ensure the precise odour analysis procedure in the NOS.E system. Besides, a particular control logic was introduced to improve the...

Sleep apnea is a common sleep disorder that can significantly decrease the quality of life. An accurate and early diagnosis of sleep apnea is required before getting proper treatment. A reliable automated detection of sleep apnea can overcome the problems of manual diagnosis (scoring) due to variability in recording and scoring criteria (for exampl...

Post-stroke motor recovery highly relies on voluntarily participating in active rehabilitation as early as possible for promoting the reorganization of the patient’s brain. In this paper, a new method is proposed which manipulates cablebased rehabilitation robots to assist multi-joint body motions. This uses an electromyography (EMG) decoder for co...

This paper is devoted to the design of a novel fault‐tolerant control (FTC) using the combination of a robust sliding‐mode control (SMC) strategy and a control allocation (CA) algorithm, referred to as a CA‐based sliding‐mode FTC (SMFTC). The proposed SMFTC can also be considered a modular‐design control strategy. In this approach, first, a high‐le...

In general, existing machine learning based approaches, developed for systolic and diastolic blood pressure (SBP and DBP) estimation from oscillometric waveforms (OWs), employ features extracted from the OW envelope (OWE) alone and ignore important beat-by-beat (BBB) features which represent fundamental physical properties of the entire non-invasiv...

Users' emotional reaction capturing is one of the primary issues for brain computer interface applications. Despite the intuitive feedback provided by the qualitative methods, emotional reactions are expected to be detected and classified quantitatively. Based on the human emotion representation on physiological signal, this paper offers an hybrid...

Online parameter estimation for nonlinear systems are challenging, especially when only limited computational powers are available. The auto-calibration of triaxial accelerometers is essentially a nonlinear parameter estimation problem. In this paper, a simple but efficient auto-calibration method for micro triaxial accelerometers is proposed. In p...

This paper describes a novel scheme for fault tolerant control using a robust optimal control design method. This scheme can also be employed as actuator redundancy management for over-actuated linear systems. In contrast to many existing methods in the literature, this scheme can be applied to systems whose control input matrix cannot be factorise...

This paper presents a novel electronic nose (E-nose) data pre-processing method, based on a recently developed non-parametric kernel-based modelling (KBM) approach. The proposed method is tested by an automated odour detection and classification system, named “NOS.E” developed by the NOS.E team in University of Technology Sydney. Experimental resul...

Sleep apnea elicits brain and physiological changes and its duration varies across the night. This study investigates the changes in the relative powers in electroencephalogram (EEG) frequency bands before and at apnea termination and as a function of apnea duration. The analysis was performed on 30 sleep records (375 apnea events) of older adults...

Due to the high dimensional, non-stationary and non-linear properties of electroencephalogram (EEG), a significant portion of research on EEG analysis remains unknown. In this paper, a novel approach to EEG-based human emotion study is presented using Big Data methods with a hybrid classifier. An EEG dataset is firstly compressed using compressed s...

The goal of this research was to investigate the effect of wearing high-heeled shoes (HHS) on lower limb muscle synchronisation during walking, using beta band (15–30 Hz) coherence analysis. Fifteen females with no previous neuromuscular disorders volunteered in this study. Surface electromyography in frequency domain was studied from rectus femori...

This paper presents an adaptive neural network (NN) control of a two-degree-of-freedom manipulator driven by an electrohydraulic actuator. To restrict the system output in a prescribed performance constraint, a weighted performance function is designed to guarantee the dynamic and steady tracking errors of joint angle in a required accuracy. Then,...

We present a practical electronic nose (e-nose) sys-tem, NOS.E, for the rapid detection and identification of human health conditions. By detecting the changes in the composition of an individual's respiratory gases, which have been shown to be linked to changes in metabolism, e-nose systems can be used to characterize the physical health condition...

This paper applies a nonparametric modelling method with kernel-based regularization to estimate the carbon dioxide production during jogging exercises. The kernel selection and regularization strategies have been discussed; several commonly used kernels are compared regarding the goodness-of-fit, sensitivity, and stability. Based on that, the most...

In contrast to the traditional centralised power system state estimation approaches, this paper investigates the optimal filtering problem for distributed dynamic systems. Particularly, the interconnected synchronous generators are modelled as a state-space linear equation where sensors are deployed to obtain measurements. As the synchronous genera...

This paper proposes a framework for the design of sparsely distributed output feedback discrete-time sliding mode control (ODSMC) for interconnected systems. The major target here is to develop an observer based discrete-time sliding mode controller employing a sparsely distributed control network structure in which local controllers exploit some o...

Background: Previous studies have indicated that oxygen uptake ([Formula: see text]) is one of the most accurate indices for assessing the cardiorespiratory response to exercise. In most existing studies, the response of [Formula: see text] is often roughly modelled as a first-order system due to the inadequate stimulation and low signal to noise...

This paper describes 2 schemes for a fault-tolerant control using a novel optimal sliding-mode control, which can also be employed as actuator redundancy management for overactuated uncertain linear systems. By using the effectiveness level of the actuators in the performance indexes, 2 schemes for redistributing the control effort among the remain...

Electronic nose devices consisting of a matrix of sensors to sense the smell of various target gases have received considerable attention during the past two decades. This paper presents an efficient classification algorithm for a self-designed electronic nose, which integrates both genetic algorithms (GAs) and fuzzy support vector machines (FSVMs)...

The distribution power subsystems are usually interconnected to each other, so the design of the interconnected optimal filtering algorithm for distributed state estimation is a challenging task. Driven by this motivation, this paper proposes a novel consensus filter based dynamic state estimation algorithm with its convergence analysis for modern...

This paper describes a new framework for the design of a sliding surface for a given system while multi-channel H2 performances of the closed-loop system are under control. In contrast to most of the current sliding surface design schemes, in this new method the level of control effort required to maintain sliding is penalised. The proposed method...

The suppression of disturbances under parametric uncertainties is one of the most common control problems in electrohydraulic systems, as both disturbances and uncertainties often significantly degrade the tracking performance and bias the load pressure of the electrohydraulic actuator (EHA). This brief presents a state-constrained control of singl...

Recently, the smart grid has been considered as a next-generation power system to modernize the traditional grid to improve its security, connectivity, efficiency and sustainability. Unfortunately, the smart grid is susceptible to malicious cyber attacks, which can create serious technical, economical, social and control problems in power network o...

Oxygen consumption on-kinetics is an important physiological parameter for the determination of functional health status and muscle energetics during physical exercise. Several experiments suggest that oxygen consumption is mainly controlled by factor related metabolic system. Unlike heart rate, which is affected by mood, stress, etc., the maximum...

When dealing with large-scale systems, manual selection of a subset of components (sensors/actuators), or equivalently identification of a favourable structure for the controller, that guarantees a certain closed-loop performance, is not very feasible. This paper is dedicated to the problem of concurrent optimal selection of actuators/sensors which...

Emotion classification is one of the state-of-the-art topics in biomedical signal research, and yet a significant portion remains unknown. This paper offers a novel approach with a combined classifier to recognise human emotion states based on electroencephalogram (EEG) signal. The objective is to achieve high accuracy using the combined classifier...

This paper investigates the modelling of oxygen consumption (VO2) response to jogging exercise on treadmill. Unlike most of the previous methods, which often use simple parametric models, e.g., first order linear time invariant model, this study applied a nonparametric kernel based regularised method to estimate VO2 to address the ill-conditioned m...

Surface Electromyography (sEMG) has been commonly applied for analysing the electrical activities of skeletal muscles. The sensory system of maintaining posture balance includes vision, proprioception and vestibular senses. In this work, an attempt is made to classify whether the body is missing one of the sense during balance control by using sEMG...

Recognizing emotion from EEG signals is a complicated task that requires complex features and a substantial number of EEG channels. Simple algorithms to analyse the feature and reduce the EEG channel number will give an indispensable advantages. Therefore, this study explores a combination of wavelet entropy and average wavelet coefficient (WEAVE)...

This study was devoted to developing a new auxiliary-model-based damped recursive least squares (AMB-DRLS) by which the heart rate dynamics can be identified in a real-time manner. Unlike the current conventional schemes for heart rate dynamics modeling, the proposed scheme can simultaneously identify the HR response dynamics and compensate for the...

This paper proposes a novel distributed consensus filter based dynamic state estimation algorithm with its convergence analysis for modern power systems. The novelty of the scheme is that the algorithm is designed based on the mean squared error and semidefinite programming approaches. Specifically, the optimal local gain is computed after minimizi...

This paper is devoted to the problem of designing a sparse distributed output feedback discrete-time sliding mode control (ODSMC) for the networked systems. A distributed structure is employed in the discrete-time sliding mode control framework by exploiting other sub-systems’ information to improve the performance of each local controller/observer...

In contrast to the traditional centralised power system state estimation methods, this paper investigates the optimal filtering problem for distributed dynamic systems. Specifically, the interconnected synchronous generators are modelled as a state-space linear equation where sensors are deployed to obtain measurements. As the synchronous generator...

This paper explores the problem of distributed state estimation including packet losses for the environment-friendly renewable microgrid incorporating electricity generating circuits. The problem is becoming critical due to the global warming, increasing green house gas emissions, and practical infeasibility with computational burden of the large-s...

This paper is devoted to the problem of designing an ( )-based optimal sparse static output feedback (SOF) controller for continuous linear time invariant systems. Incorporating an extra term for penalising the number of non-zero entries of the static output (state) feedback gain into the optimisation objective function, we propose an explicit sche...

Given the significant concerns regarding carbon emissions from fossil fuels, global warming and energy crisis, renewable distributed energy resources (DERs) are going to be integrated in smart grids, which will make the energy supply more reliable and decrease the costs and transmission losses. Unfortunately, one of the key technical challenges in...

This paper is devoted to the problem of designing an H2 and/or H∞ row-sparse static output feedback controller for continuous linear time invariant systems with polytopic uncertainty. The immediate application of the proposed approach lies within the problem of the optimal selection of a subset of available actuators during the fault accommodation...

This paper develops a novel stabilising sliding mode for systems involving uncertainties as well as measurement data packet dropouts. In contrast to the existing literature that designs the switching function by using unavailable system states, a novel linear sliding function is constructed by employing only the available communicated system states...

In this paper, an output position feedback control of the electro-hydraulic system (EHS) is proposed based on an extended-state-observer (ESO) with backstepping. On the basis of the augmented state model of the EHS, the ESO is designed to handle the unknown load disturbance and uncertain nonlinearity. Then, an observer bandwidth constraint is deriv...

In this paper, we proposed a novel method for autocalibration of triaxial Micro-Electro-Mechanical systems (MEMS) accelerometer that does not require any sophisticated laboratory facilities. In particular, this method is an online calibration method which can be conveniently implemented with the accuracy of MEMS accelerometer being significantly im...

The paper describes a reliable and valid Portable Exercise Monitoring system developed using TI eZ430-Chronos watch, which can control the exercise intensity through audio stimulation in order to increase the Cardiovascular fitness strengthening.

This paper is devoted to the problem of heart rate regulation using a model-based control strategy and a realtime damped parameter estimation scheme. The controller is a time-varying integral sliding mode controller. A recursive damped parameter estimation method is also developed, by incorporation of a weighting upon the one-step parameter variati...

This paper is devoted to the problem of real-time heart rate (HR) response modelling during treadmill exercise. A novel recursive constrained parameter estimation method is developed which in contrast to the conventional parameter estimation schemes (e.g. recursive least squares (RLS) method) can avoid the occurrence of the so-called blowup phenome...

This paper introduces a Silver Gull-inspired hybrid aerial vehicle, the Super Sydney Silver Gull (SSSG), which is able to vary its structure, under different manoeuvre requirements, to implement three flight modes: the flapping wing flight, the fixed wing flight, and the quadcopter flight (the rotary wing flight of Unmanned Air Vehicle). Specifical...

Psychotherapy requires appropriate recognition of patient's facial-emotion expression to provide proper treatment in psychotherapy session. To address the needs this paper proposed a facial emotion recognition system using Combination of Viola-Jones detector together with a feature descriptor we term Edge-Histogram of Oriented Gradients (E-HOG). Th...

This paper explores the problem of distributed state estimation including packet losses for the environment-friendly renewable microgrid incorporating electricity generating circuits. The problem is becoming critical due to the global warming, increasing green house gas emissions, and practical infeasibility with computational burden of the large-s...

The smart grid has been considered as a nextgeneration power system to modernize the traditional grid to improve its security, connectivity and sustainability. Unfortunately, the grid is susceptible to malicious cyber attacks, which can create serious technical, economical and control problems in power network operations. In contrast to the traditi...

This paper is devoted to the problem of regulating the heart rate response along a predetermined reference profile, for cycle-ergometer exercises designed for training or cardio-respiratory rehabilitation. The controller designed in this study is a non-conventional, non-model-based, proportional, integral and derivative (PID) controller. The PID co...

In this paper, a new approach to design a robust discrete-time sliding mode control (DSMC) is proposed for uncertain discrete-time systems. To this end, an LMI approach is used to develop a new framework to design the sliding function which is linear to the state. Our proposed robust DSMC can be applied to unstable systems, and also there is no nee...

The internet of things (IoT) has been a prevalent research topic in recent years in both academia and industry. The main idea of this framework is the integration of physical objects into a global information network. The vision of the IoT is to integrate and connect anything at any time and any place. For this reason, it is being applied in variou...

This study is devoted to the problem of designing a robust output-feedback discrete-time sliding mode control (ODSMC) for the networked systems involving both measuring and actuating data packet losses. Packet losses in the networked control systems (NCSs) have been modelled by utilising the probability and the characteristics of the sources and th...

One of the major public health problems among elderly people is falling injury. This study investigates fall detection and prevention by using inertial sensors for which the major existing challenging is how to significantly reduce false alarming in order to enhance the acceptance of elderly users during rehabilitation and daily exercises. Differen...

This paper investigates the estimation of key cardiac-respiratory variables (e.g.,$VO_2$) by using commercialised wearable sensors such as SensorTag and iPhone. The main aim of this study is to use inexpensive and user-friendly wearable sensors rather than expensive and cumbersome equipment (e.g., metabolic analyser). This study also aims to explor...

Electromyography (EMG) signals are the measure of activity in the muscles. The aim of this study is to identify the neuromuscular disease based on EMG signals by means of classification. The neuromuscular diseases that have been identified are myopathy and neuropathy. The classification was carried out using Artificial Neural Network (ANN). There a...

The optimal power flow (OPF) of a power transmission network is a NP-hard optimization problem with nonlinear equality and inequality constraints on the bus voltages. The existing nonlinear solvers often fail in yielding a feasible solution. Semi-definite relaxation (SDR) could provide an optimal solution only when the optimal solution of the relax...