K. Khorasani

K. Khorasani
Concordia University Montreal · Department of Electrical and Computer Engineering

Ph.D.

About

513
Publications
48,176
Reads
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11,317
Citations
Citations since 2017
60 Research Items
5221 Citations
20172018201920202021202220230200400600800
20172018201920202021202220230200400600800
20172018201920202021202220230200400600800
20172018201920202021202220230200400600800
Additional affiliations
January 2011 - present
Qatar University
January 2006 - December 2008
January 2004 - December 2006
Hiroshima Prefectural University

Publications

Publications (513)
Article
Aircrafts are complex engineering systems composed of many interconnected subsystems with possible uncertainties in their structure. They often function for long number of flight hours under varying or harsh environments. Hence, Prognostic and Health Management (PHM) of critical subsystems or components within the overall system is crucial for main...
Article
Full-text available
In this study, a robust feedforward hybrid active noise control (ANC) system with online secondary‐path modelling (SPM) is proposed that is capable of not only effectively suppressing the broadband and narrowband noise components but also tracking the secondary path (SP) variations. An finite impulse response online SPM subsystem as well as an effi...
Article
Failure prognostic predicts the Remaining Useful Life (RUL) of machine/components, which will allow timely maintenance and repair leading to continuous reliable and safe operating conditions. In this paper, a novel hybrid RUL prediction approach is proposed for heavy-duty gas turbines. Two common failures, namely the fouling in the gas turbine comp...
Article
There are vast fields of application for optical fiber sensors. Fiber Bragg Gratings (FBGs) are commonly used for Structural Health Monitoring (SHM) as an optical sensor to detect various physical phenomena affecting the system to assess its structure in a reliable and accurate manner. Due to the cross-sensitivity of the FBG detection, identifying...
Article
The objective of this paper is to provide a stochastic framework to optimally avoid collision between a maneuverable spacecraft and a space object or debris. The satellite collision can be caused through a cyber-attack on a satellite by colliding it with a considered strategic satellite. Consequently, it is highly imperative that critical operation...
Preprint
Full-text available
In this paper, a novel hybrid-degree dual estimation approach based on cubature rules and cubature-based nonlinear filters is proposed for fault diagnosis of nonlinear systems through simultaneous state and time-varying parameter estimation. Our proposed dual nonlinear filtering scheme is developed based on case-dependent cubature rules that are mo...
Article
Fault diagnosis and prognosis are some of the most crucial functionalities in complex and safety-critical engineering systems, and particularly fault diagnosis, has been a subject of intensive research in the past four decades. Such capabilities allow for detection and isolation of early developing faults as well as prediction of fault propagation...
Article
One of the main concerns associated with diagnosis, prognosis, and health management (DPHM) of engineering systems is the accuracy of estimates that are derived from Bayesian tracking methods. Estimating the exiting degradation based on stochastic models and evaluating the remaining useful life (RUL) of the system is inherently associated with vari...
Article
Full-text available
In this paper, the problem of distributed event-based control of large scale power systems in presence of denial-of-service (DoS) cyber attacks is addressed. Towards this end, a direct current (DC) microgrid composed of multiple interconnected distributed generation units (DGUs) is considered. Voltage stability is guaranteed by utilizing decentrali...
Article
In this paper the stochastic fault and cyber-attack detection and consensus control problems are investigated for multi-agent systems. By using a Markovian approach, Linear Matrix Inequalities (LMI) are derived that incorporate relative information among the agents to detect stochastic faults and cyber-attacks and then resiliently control the syste...
Article
In this paper, an in-depth statistical analysis is conducted for a typical narrowband active noise control (ANC, NANC) system that is based on a simplified variable step-size (VSS) filtered-x least mean square (SVSS-FXLMS) scheme. Difference equations are derived first that describe the NANC system convergent behavior in both mean and mean square s...
Article
Full-text available
Due to recent increase in deployment of Cyber-Physical Industrial Control Systems in different critical infrastructures, addressing cyber-security challenges of these systems is vital for assuring their reliability and secure operation in presence of malicious cyber attacks. Towards this end, developing a testbed to generate real-time data-sets for...
Article
Second-order IIR adaptive notch filters (ANF) andbanks (ANFB) have been extensively utilized in many applications ranging from biomedical engineering to control systems. In this paper, a new efficient ANFB is proposed that is composed of two filter banks, namely a prefilter bank with cascaded IIR notch filters and a parallel structure IIR ANFB. The...
Preprint
In this paper, the problem of simultaneous cyber attack and fault detection and isolation (CAFDI) in cyber-physical systems (CPS) is studied. The proposed solution methodology consists of two filters on the plant and the command and control (C\&C) sides of the CPS and an unknown input observer (UIO) based detector on the plant side. Conditions unde...
Preprint
Full-text available
This paper aims at investigating a novel type of cyber attack that is injected to multi-agent systems (MAS) having an underlying directed graph. The cyber attack, which is designated as the controllability attack, is injected by the malicious adversary into the communication links among the agents. The adversary, leveraging the compromised communic...
Preprint
The objective in this paper is to study and develop conditions for a network of multi-agent cyber-physical systems (MAS) where a malicious adversary can utilize vulnerabilities in order to ensure and maintain cyber attacks undetectable. We classify these cyber attacks as undetectable in the sense that their impact cannot be observed in the generate...
Conference Paper
Full-text available
A time-delay switch (TDS) cyber attack is a deliberate attempt by malicious adversaries aiming at destabilizing a power system by impeding the communication signals to/from the centralized controller from/to the network sensors and generating stations that participate in the load frequency control (LFC). A TDS cyber attack can be targeting the sens...
Article
In this work, a novel data-driven fault diagnostic framework is developed by using hybrid multi-mode machine learning strategies to monitor system health status. The coexistence of multi-mode and concurrent faults and their adverse coupling effects pose serious limitations for developing reliable diagnostic methodologies. A novel framework is propo...
Article
In this paper, the problem of distributed event-based control of large scale power systems is addressed. Towards this end, a Direct Current (DC) microgrid that is composed of multiple interconnected Distributed Generation Units (DGUs) is considered. Voltage stability is guaranteed by utilizing decentralized local controllers for each DGU. A distrib...
Conference Paper
Fiber Bragg Gratings (FBGs) in Structural Health Monitoring (SHM) are used as an optical sensor to detect various physical phenomena to make the system more reliable and accurate. In this work, theoretical analysis and numerical simulation of an Apodized π-Phase Shifted Fiber Bragg Grating (π-PS FBG) sensor is proposed to evaluate the performance o...
Article
Full-text available
Acoustic emission (AE) signals are recognized as complementary measures for detecting incipient faults and condition monitoring in rotary machinery due to their containment of sources of potential fault energy. However, determining the potential sources of faults cannot be easily realized due to the non-stationarity of AE signals. Available techniq...
Article
Full-text available
We propose a framework for inversion-based estimation of certain categories of faults in discrete-time linear systems. First, we develop a novel methodology for direct estimation of unknown inputs by using only measurements of either minimum or non-minimum phase systems as well as systems with transmission zeros on the unit circle. The unknown inpu...
Article
Full-text available
In this paper, a novel distributed cooperative estimation framework for a formation flight of satellites is proposed. This framework is developed based on the notion of sub-observers. Within a group of sub-observers each one is estimating certain states that are conditioned on a given input, output, and state information. In order to guarantee the...
Conference Paper
Full-text available
Narrowband active noise control (ANC, NANC) systems provide excellent performance in suppressing the annoying noise signals generated by rotating machines, which may be modeled as sinusoidal signals in additive noise. In real-world applications, two important issues including secondary path modeling (SPM) and frequency mismatch (FM), namely, the er...
Article
Multifunctional spoiler (MFS) is one of the most critical parts of the jet aircraft that can be degraded due to incipient faults and consequently jeopardize the safety of a flight. This paper introduces a new fault diagnosis method for the MFS using fusion methodology. Three main faults including null bias current, actuator leakage coefficient, and...
Article
This paper presents a new fault prognosis approach for a multifunctional spoiler (MFS) system which employs an extended Kalman filter (EKF) and Bayesian theorem method for prognosis. The MFS is an important part of an aircraft spoiler control system (SCS), and thus, prognosis and health management (PHM) of this system improves the safety of the air...
Article
Health monitoring of nonlinear systems is broadly concerned with the system health tracking and its prediction to future time horizons. Estimation and prediction schemes constitute as principle components of any health monitoring technique. Particle filter (PF) represents a powerful tool for performing state and parameter estimation as well as pred...
Article
In this work, a data-driven fault detection, isolation, and estimation (FDI&E) methodology is proposed and developed specifically for monitoring the aircraft gas turbine engine actuator and sensors. The proposed FDI&E filters are directly constructed by using only the available system I/O data at each operating point of the engine. The healthy gas...
Article
Recently various forecasting methods for photovoltaic (PV) generation have been proposed in the literature. However, these standard methods cannot be successfully and widely used in general due to the fact that they require access to specialized data that are not always and everywhere readily available in practice. Furthermore, prediction accuracy...
Article
Full-text available
In this paper, we propose and develop a methodology for nonlinear systems health monitoring by modeling the damage and degradation mechanism dynamics as "slow" states that are augmented with the system "fast" dynamical states. This augmentation results in a two-time scale nonlinear system that is utilized for development of health estimation and pr...
Article
Full-text available
In this work, we develop a novel fault detection and isolation (FDI) scheme for discrete-time multi-dimensional (n-D) systems for the first time in the literature. These systems represent as generalization of the Fornasini–Marchesini model II two- and three-dimensional (2-D and 3-D) systems. This is accomplished by extending the geometric FDI appro...
Article
In this paper, the problem of integrated fault detection, isolation, and control design of continuous-time Markovian jump linear systems with uncertain transition probabilities is introduced and addressed for the first time in the literature. A single Markovian jump module designated as the integrated fault detection, isolation, and control under a...
Article
In this paper, a fault detection and isolation (FDI) methodology based on an immune system (IS) inspired mechanism known as the dendritic cell algorithm (DCA) is developed and implemented. Our proposed DCA-based FDI methodology is then applied to a well-known wind turbine (WT) test model. The proposed DCA-based scheme performs both detection as wel...
Article
In this paper, the problem of control and fault recovery for a team of autonomous underwater vehicles (AUVs) in presence of loss of effectiveness (LOE) actuator faults is addressed. Towards this end, two fault recovery control strategies are proposed and developed where the first scheme is based on the model predictive control (MPC) technique and t...
Article
Full-text available
In this paper, a novel computationally intelligent-based electrocardiogram (ECG) signal classification methodology using a deep learning (DL) machine is developed. The focus is on patient screening and identifying patients with paroxysmal atrial fibrillation (PAF), which represents a life threatening cardiac arrhythmia. The proposed approach operat...
Article
In this paper, distributed control reconfiguration strategies for directed switching topology networked multi-agent systems are developed and investigated. The proposed control strategies are invoked when the agents are subject to actuator faults and while the available fault detection and isolation (FDI) modules provide inaccurate and unreliable i...
Article
In this work, we develop a novel fault detection and isolation (FDI) scheme for discrete-time two-dimensional (2D) systems that are represented by the Fornasini–Marchesini model II (FMII). This is accomplished by generalizing the basic invariant subspaces including unobservable, conditioned invariant and unobservability subspaces of 1D systems to 2...
Article
The problem of simultaneous fault detection, isolation and tracking (SFDIT) control design for linear systems subject to both bounded energy and bounded peak disturbances is considered in this work. A dynamic observer is proposed and implemented by using the H∞/H−/L1 formulation of the SFDIT problem. A single dynamic observer module is designed tha...
Article
This paper tackles the development of distributed control reconfiguration and fault accommodation strategies for consensus achievement in multiagent systems in the presence of faulty agents whose actuators are unable to produce their nominal control efforts. A faulty agent can adversely affect and prevent the team from reaching agreement and lead t...
Article
In this paper, we develop nonlinear distributed or semi-decentralized cooperative control schemes for a team of heterogeneous autonomous underwater vehicles (AUVs). The objective is to have the network of AUVs follow a desired trajectory, while the agents maintain a desired formation when there is a virtual leader whose position information is only...
Article
In this paper, a novel hybrid architecture is proposed for developing a prognosis and health monitoring methodology for nonlinear systems through integration of model-based and computationally intelligent-based techniques. In our proposed framework, the well-known particle filters (PFs) method is utilized to estimate the states as well as the healt...
Article
Full-text available
A large class of hyperbolic and parabolic partial differential equation (PDE) systems, such as reaction-diffusion processes, when expressed in the infinite-dimensional (Inf-D) framework can be represented as Riesz spectral (RS) systems. Compared to the finite dimensional (Fin-D) systems, the geometric theory of Inf-D systems for addressing certain...
Article
There has been a growing interest toward the development of networked unmanned autonomous systems that can operate without an extensive involvement of humans. The motivation for this focus can be traced to the emergence of applications where direct human intervention is not possible due to the environmental hazards, complexity of the tasks, or othe...
Article
High operational and maintenance costs represent as major economic constraints in the wind turbine (WT) industry. These concerns have made investigation into fault diagnosis of WT systems an extremely important and active area of research. In this paper, an immune system (IS) inspired methodology for performing fault detection and isolation (FDI) o...
Article
In this paper, a dual estimation methodology is developed for both time-varying parameters and states of a nonlinear stochastic system based on the Particle Filtering (PF) scheme. Our developed methodology is based on a concurrent implementation of state and parameter estimation filters as opposed to using a single filter for simultaneously estimat...
Article
Full-text available
In this paper, we propose a framework for output tracking control of both minimum phase (MP) and non-minimum phase (NMP) discrete-time linear systems. Towards this end, we first address the problem of unknown state and input reconstruction of non-minimum phase systems. An unknown input observer (UIO) is designed that accurately reconstructs the min...
Article
We propose explicit state-space based fault detection, isolation and estimation filters that are data-driven and are directly identified from only the system input-output (I/O) measurements and through the system Markov parameters. The proposed procedures do not involve a reduction step and do not require identification of the system extended obser...
Conference Paper
The problem of event-triggered active fault-tolerant control (E-AFTC) of discrete-time linear systems is addressed in this paper by using an integrated design of event-triggered fault/state estimator with a fault-tolerant controller. An event-triggered observer is proposed which can simultaneously provide an estimate of the system states and faults...
Article
The problem of simultaneous fault detection and consensus control (SFDCC) of linear continuous-time multi-agent systems is addressed in this paper. A mixed formulation of the SFDCC problem is presented and distributed detection filters are designed using only relative output information among the agents. With our proposed methodology, all agents re...
Article
In this paper, a novel robust sensor fault detection and isolation (FDI) strategy using the multiple model-based (MM) approach is proposed that remains robust with respect to both time-varying parameter uncertainties and process and measurement noise in all the channels. The scheme is composed of robust Kalman filters (RKF) that are constructed for...
Article
The increase in energy demand has led to expansion of renewable energy sources and their integration into a more diverse energy mix. Consequently the operation of thermal power plants, which are spearheaded by the gas turbine technology, has been affected. Gas turbines are now required to operate more flexible in grid supporting modes that include...
Article
This brief is concerned with the design of distributed formation recovery control laws for nonlinear heterogeneous multiagent Euler-Lagrange (EL) systems that are simultaneously subject to: 1) diagnostic information imperfections and unreliabilities; 2) parametric uncertainties and external disturbances; and 3) random switching of communication net...
Article
In this paper, a new approach for Fault Detection and Isolation (FDI) of gas turbine engines is proposed by developing an ensemble of dynamic neural network identifiers. For health monitoring of the gas turbine engine, its dynamics is first identified by constructing three separate or individual dynamic neural network architectures. Specifically, a...
Article
In the area of robust control, fault diagnosis, and fault tolerant control of linear systems, many fundamental problems can be recast as H-\infty, l-1 and generalized H-2 control frameworks leading to the so-called mixed norm or multiobjective optimization problems. This paper develops a new linear matrix inequality (LMI) approach to the problems o...
Conference Paper
In order to improve the effectiveness and safety of control systems, the problem of integrated fault diagnosis and control (IFDC) design has attracted significant attention in the recent years, both in the research and in the application domains. The integrated design unifies the control and diagnosis units into a single unit which leads to less co...
Article
This paper is concerned with the design of distributed formation recovery control laws for nonlinear Euler-Lagrange (EL) systems in presence of parameter uncertainty, external disturbances, and diagnostic information imperfections with switching communication network topologies. Specifically, H∞optimal control techniques are employed to formally de...
Article
The main goal of this paper is to design and develop a fault detection and isolation (FDI) scheme for aircraft gas turbine engines by using neural networks. Towards this end, first for the fault detection task two types of dynamic neural networks are used and compared to learn the engine dynamics. Specially, the dynamic neural model (DNM) and the t...
Article
A cooperative actuator fault accommodation strategy for a team of linear time-invariant (LTI) multi-agent systems with a switching topology and directed communication network graph is studied in this paper. The faults can simultaneously occur in more than one agent. The proposed fault accommodation strategy is based on a consensus algorithm that we...
Article
In this paper, an active distributed (also referred to as semi-decentralised) fault recovery control scheme is proposed that employs inaccurate and unreliable fault information into a model-predictive-control-based design. The objective is to compensate for the identified actuator faults that are subject to uncertainties and detection time delays,...
Article
Gas turbines are faced with new challenges of increasing flexibility in their operation while reducing their life cycle costs, leading to new research priorities and challenges. One of these challenges involves the establishment of high fidelity, accurate, and computationally efficient engine performance simulation, diagnosis, and prognosis schemes...
Article
The main objective of this paper is to design distributed cooperative synchronization and reconfigurable control strategies for a network of heterogeneous multi-agent Euler–Lagrange (EL) systems by taking into account constraints on the control inputs and actuator saturation faults. First, bounded distributed cooperative synchronization (or consens...
Article
In this work, an $H_{\infty}$ performance fault recovery control problem for a team of multi-agent systems that is subject to actuator faults is studied. Our main objective is to design a distributed control reconfiguration strategy such that a) in absence of disturbances the state consensus errors either remain bounded or converge to zero asymptot...
Article
In this paper, the problem of health monitoring and prognosis of aircraft gas turbine engines is considered by using computationally intelligent methodologies. Two different dynamic neural networks, namely the nonlinear autoregressive with exogenous input neural networks and the Elman neural networks, are developed and designed for this purpose. Th...
Conference Paper
Full-text available
In this paper, a methodology for an affine quasilinear parameter varying (qLPV) model derivation is proposed. The nonlinear model of the system is converted into a qLPV model by hiding the nonlinearities in the scheduling parameters. In order to select the most suitable model among all the possible models, an algorithm is introduced and proposed to...
Article
In this paper, new fault detection and isolation/identification (FDI) schemes are proposed by using adaptive threshold bands that are generated with locally linear models (LLM) as well as model error modeling (MEM) techniques. The performance capabilities of our two proposed adaptive threshold bands are compared relative to each other as well as wi...