- Pointe-Claire, Quebec, Canada
Research Interests:
ABSTRACT Due to unforeseen circumstances and naturally occurring faults, it is desired that an on-board fault-diagnosis system of a space vehicle be capable of detecting, isolating, identifying or classifying faults in the system. In this... more
ABSTRACT Due to unforeseen circumstances and naturally occurring faults, it is desired that an on-board fault-diagnosis system of a space vehicle be capable of detecting, isolating, identifying or classifying faults in the system. In this paper, a novel approach is proposed which strengthens existing efficient fault-detection mechanisms with an additional ability to classify different types of faults to effectively determine potential failure causes in a subsystem. This extra capability ensures a quick and efficient recovery/reconfiguration from disruptions. Our developed diagnosis/analysis procedure exploits a widely used qualitative technique called fault-tree analysis, as a diagnostic aid, for failure analysis in the attitude control subsystem (ACS) of a spacecraft. Constructed fault-trees have been able to represent combinations of events leading to different failures resulting due to artificially injected faults in a MATLAB-Simulink model of the ACS. It is important to emphasize that proposed technique has potentials for being integrated in an on-board health monitoring and diagnosis tool for space vehicles
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Research Interests:
A novel methodology for detecting the anomaly distribution in composite structures by fiber Bragg grating sensor (FBG) fabricated into the high birefringence fiber (Hi-Bi FBG sensor) is presented. The strain and temperature change effects... more
A novel methodology for detecting the anomaly distribution in composite structures by fiber Bragg grating sensor (FBG) fabricated into the high birefringence fiber (Hi-Bi FBG sensor) is presented. The strain and temperature change effects on the embedded Hi-Bi FBG sensor area are separately modeled by introducing the change of the refractive indices and grating period along the fiber to the transfer matrix formulation method. Each Bragg reflection corresponding to the principal axes of the fiber has different dependence on temperature and strain. Using this property, the temperature and strain dependence is separated. Furthermore, the use of genetic algorithm for reconstruction of non-uniform applied anomaly from the reflected spectrum is presented. The presented method is verified through the numerical simulations and the results show that our methodology can effectively represent and model the profile of the applied perturbation profile.
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This paper investigates the problem of fault tolerant cooperative control for UAV rendezvous problem in which multiple UAVs are required to arrive at their designated target despite presence of a fault in the thruster of any UAV. An... more
This paper investigates the problem of fault tolerant cooperative control for UAV rendezvous problem in which multiple UAVs are required to arrive at their designated target despite presence of a fault in the thruster of any UAV. An integrated hierarchical scheme is proposed and developed that consists of a cooperative rendezvous planning algorithm at the team level and a nonlinear
Research Interests:
Similar to many of the existing fault diagnosis methods, the two FDII schemes developed in the previous chapter relied on the availability of full-state measurements. However, even with recent advances in sensor and instrumentation... more
Similar to many of the existing fault diagnosis methods, the two FDII schemes developed in the previous chapter relied on the availability of full-state measurements. However, even with recent advances in sensor and instrumentation technology, all the states of a dynamical system may not be directly measurable. This might be due to unavailability of operational, accurate, or reliable (on-board) sensors
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In this chapter, we start with the formal definition and formulation of the fault detection and diagnosis problem in nonlinear systems. Then, desired attributes of a fault diagnosis system and the rationale behind each attribute are... more
In this chapter, we start with the formal definition and formulation of the fault detection and diagnosis problem in nonlinear systems. Then, desired attributes of a fault diagnosis system and the rationale behind each attribute are discussed. A comprehensive survey and analysis of the literature on model-based and computational intelligence (CI)-based approaches to fault diagnosis is then presented with individual
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The main idea of this paper is the real-time implementation of the Fault Detection Kalman Filter Estimators (FDKFE) in a satellite’s Reaction Wheels during its scientific mission. We assume that the satellite’s reaction wheels are... more
The main idea of this paper is the real-time implementation of the Fault Detection Kalman Filter Estimators (FDKFE) in a satellite’s Reaction Wheels during its scientific mission. We assume that the satellite’s reaction wheels are subjected to several failures due to the abnormal changes in power distribution, motor torque, windings current as well as the temperature caused by a motor current increase or friction. The proposed realtime FDKFE strategies consist of two embedded multiple model bank of nonlinear Kalman Filter (extended and unscented) estimators. This research work is based on our previous results in this field and now we are interested only in real-time implementation of some of these FDKFE strategies (FDDM_EKF and FDDM_UKF). Furthermore we will construct a benchmark to compare their results to have an overall image how perform these strategies.
This paper presents a novel hybrid fault diagnosis approach to detect and estimate component faults in general nonlinear systems with full-state measurement. Unlike most existing fault diagnosis techniques, the proposed solution provides... more
This paper presents a novel hybrid fault diagnosis approach to detect and estimate component faults in general nonlinear systems with full-state measurement. Unlike most existing fault diagnosis techniques, the proposed solution provides an integrated framework to simultaneously detect, isolate, and estimate the severity of faults in system components. The proposed solution consists of a bank of adaptive Neural Parameter Estimators
Research Interests:
Like many other man-made dynamical systems, spacecraft are potentially subjected to unexpected anomalies and failures in subsystems and components during their mission lifetime. Future generations of spacecraft need to show proper... more
Like many other man-made dynamical systems, spacecraft are potentially subjected to unexpected anomalies and failures in subsystems and components during their mission lifetime. Future generations of spacecraft need to show proper reaction to unexpected events such as component/subsystem failures or environmental interactions. Most currently used spacecraft controllers react to different situations according to some, often, hard-coded routines. This is impractical when the spacecraft is facing an unexpected event. On the other hand, the probability of fault occurrence increases with the time needed to accomplish the mission. Hence, the development of technologies that enable the spacecraft to automatically detect, isolate, identify, and eventually respond and recover from (unexpected) faults/failures in its components, subsystems, or mission goals is highly desirable. The main goal of an autonomous operation should be to maintain the spacecraft’s safety and to perform the critical functions in priority.
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In this monograph, a new integrated solution to the problem of fault detection, isolation and identification (FDII) for nonlinear systems is proposed. The proposed fault diagnosis methodology benefits from both a priori mathematical model... more
In this monograph, a new integrated solution to the problem of fault detection, isolation and identification (FDII) for nonlinear systems is proposed. The proposed fault diagnosis methodology benefits from both a priori mathematical model information of the system and the nonlinear function approximation and adaptation capability of neural networks in a hybrid framework. More specifically, mathematical model of the system
Research Interests:
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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... more
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 which can allow for preventive maintenance, or even serve as a countermeasure to the possibility of catastrophic incidence as a result of a failure. Following a short preliminary overview and definitions, this article provides a survey of recent research on fault prognosis. Additionally, we report on some of the significant application domains where prognosis techniques are employed. Finally, some potential directions for future research are outlined.
Research Interests: Condition Monitoring, Survey Research, Batteries, Failure Diagnosis, Failure Analysis, and 8 morePrognosis and health management, Computer Software, Condition monitoring and fault diagnosis of electric machinery, Health monitoring, Bearings, Safety Critical Systems, Remaining Useful Life Estimation, and Electrical And Electronic Engineering
This paper presents a new fault prognosis approach for a multi-functional spoiler (MFS) system which employs an extended Kalman filter (EKF) and Bayesian based method for prognosis. The MFS is an important part of an aircraft spoiler... more
This paper presents a new fault prognosis approach for a multi-functional spoiler (MFS) system which employs an extended Kalman filter (EKF) and Bayesian based 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 safety of the aircraft. To monitor the system, residual estimation based on the EKF method is utilized to observe the progress of the failure in the system. Then, a new measure is introduced by using a transformation to estimate the degradation path (DP) of the failure in the system. Furthermore, a new recursive Bayesian approach is invoked to predict the RUL of the system using the estimated DP data. Finally, for performance assessment, relative accuracy (RA) measure is utilized to evaluate the accuracy of the proposed method. Several test studies are conducted to examine the capability of the proposed method in the prognosis of the MFS system.
Research Interests:
—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... more
—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 internal leakage faults are considered and three parallel fusion blocks are invoked to isolate these faults in the system. In each block, an integrated method using an artificial neural network (ANN) and discrete wavelet transform (DWT) is developed via ordered weighted averaging (OWA) operator to achieve a higher reliability and faster diagnosing system. Moreover, several test scenarios are examined to validate the system performance under faulty conditions. Simulation results show the capability of the system in isolating incipient faults in comparison with artificial neural network and discrete wavelet transform methods.
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ABSTRACT The presence of measurement noise and model uncertainties in sensor arrays and the lack of statistical information poses several challenges for development of effective and robust algorithms for the direction-of-arrival (DOA)... more
ABSTRACT The presence of measurement noise and model uncertainties in sensor arrays and the lack of statistical information poses several challenges for development of effective and robust algorithms for the direction-of-arrival (DOA) estimation problem in array processing. In this paper, we will investigate the improvements that are achievable in the DOA estimation problem by properly alleviating uncertainty effects through the application of robust H∞ filtering techniques as a pre-processing stage. The proposed methodology is implemented for a wideband DOA estimation approach that is based on the incoherent wideband MUSIC (IWM) algorithm. Comparisons with and without robust filtering algorithm are also presented.
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In this work, we propose a framework for supervisory cooperative estimation of multi-agent nonlinear systems. We introduce a group of sub-observers, each estimating certain states conditioned on certain given input, output, and state... more
In this work, we propose a framework for supervisory cooperative estimation of multi-agent nonlinear systems. We introduce a group of sub-observers, each estimating certain states conditioned on certain given input, output, and state information. The cooperation among the sub-observers is supervised by a discrete-event system (DES). The supervisor makes decisions on selecting and configuring a set of sub-observers, so that
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ABSTRACT Formation flying is an emerging area in Earth and space science domain that utilizes multiple inexpensive spacecraft by distributing the functionalities of a single platform among miniature inexpensive platforms. Traditional... more
ABSTRACT Formation flying is an emerging area in Earth and space science domain that utilizes multiple inexpensive spacecraft by distributing the functionalities of a single platform among miniature inexpensive platforms. Traditional spacecraft fault diagnosis and health monitoring practices that involve around-the-clock monitoring, threshold checking, and trend analysis of a large amount of telemetry data by human experts do not scale well for multiple space platforms. In this paper, a multi-level fault diagnosis methodology utilizing fuzzy rule-based reasoning is presented to enhance the level of autonomy in fault diagnosis at the ground stations. Effectiveness of the proposed fault diagnosis methodology is demonstrated by utilizing synthetic formation flying attitude control subsystem data. The proposed scheme has potential to serve as a prognostic tool when designed based on multiple fault severities, and hence can contribute in the overall health management process.
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ABSTRACT In this paper, a new hybrid and switching framework is proposed for cooperative actuator fault estimation of formation flying satellites in deep space. The formation states are distributed among local detection and estimation... more
ABSTRACT In this paper, a new hybrid and switching framework is proposed for cooperative actuator fault estimation of formation flying satellites in deep space. The formation states are distributed among local detection and estimation filters. Each system mode represents a certain cooperative estimation scheme and communication topology among local estimation filters. The mode transition represents the reconfiguration of the estimation scheme, and the transition is governed by information provided by the detection filters. Simulation results confirm the effectiveness of our proposed framework in confining the effects of unmodeled and undesirable dynamics to local parameter estimates, thereby preventing the propagation of these undesirable effects to other estimation filters.
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In this paper, a hybrid fault detection, isolation, and recovery (FDIR) methodology is developed for a team of unmanned vehicles which takes advantage of the cooperative nature of the system to accomplish the desired mission in presence... more
In this paper, a hybrid fault detection, isolation, and recovery (FDIR) methodology is developed for a team of unmanned vehicles which takes advantage of the cooperative nature of the system to accomplish the desired mission in presence of failures. The proposed methodology is hybrid and consists of a low level (agent level) and a high level (team level) FDIR. The
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ABSTRACT In this paper, a new fault detection and isolation (FDI) scheme using recurrent adaptive time delay neural networks(ATDNN) is proposed and investigated for satellite's attitude control subsystem (ACS). Results provided... more
ABSTRACT In this paper, a new fault detection and isolation (FDI) scheme using recurrent adaptive time delay neural networks(ATDNN) is proposed and investigated for satellite's attitude control subsystem (ACS). Results provided illustrate the excellent properties of our proposed detection scheme (both in identifying fault occurrence and clearance times). The faults considered have occurred in reaction wheels which are commonly used in the ACS as actuators. Simulations for the detection results for multiple faults, simultaneous faults, as well as influences caused by dynamic coupling effects of one axis on others in the ACS have also been provided.
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... In van der Walle, Fidan, Sutton, Yu, and Anderson (200833. van der Walle, D, Fidan, B, Sutton, A, Yu, C and Anderson, BDO. Non-hierarchical UAV Formation Control for Surveillance Tasks. American Control Conference. ... In Ni and... more
... In van der Walle, Fidan, Sutton, Yu, and Anderson (200833. van der Walle, D, Fidan, B, Sutton, A, Yu, C and Anderson, BDO. Non-hierarchical UAV Formation Control for Surveillance Tasks. American Control Conference. ... In Ni and Fuller (200326. Ni, L and Fuller, CR. 2003. ...
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... This centralized observer is capable of detecting and isolating the faults in the system. ... designed for each single UAV Consequently, lower severity faults can be detected by employing the low-level observer-based detection methods... more
... This centralized observer is capable of detecting and isolating the faults in the system. ... designed for each single UAV Consequently, lower severity faults can be detected by employing the low-level observer-based detection methods through our semi-decentralized observers. ...
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ABSTRACT
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Abstract The main goal of this work is to design a controller for a team of unmanned vehicles that can accomplish a cohesive motion in a modified leader-follower structure. The desired output (command) is available for only the leader and... more
Abstract The main goal of this work is to design a controller for a team of unmanned vehicles that can accomplish a cohesive motion in a modified leader-follower structure. The desired output (command) is available for only the leader and the followers are communicating to ...
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The objective of this work is performance analysis for a cooperative team of agents in presence of team members faults. The team goal is to accomplish a cohesive motion in a modified leader-follower architecture using a semi-decentralized... more
The objective of this work is performance analysis for a cooperative team of agents in presence of team members faults. The team goal is to accomplish a cohesive motion in a modified leader-follower architecture using a semi-decentralized optimal control introduced previously by the authors. This controller is designed based on minimization of individual cost functions over a finite horizon using
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In this paper, stable adaptive formation control algorithms for two-dimensional models of aircraft are developed in the presence of unknown leader commands and disturbances due to vortex effects. The analysis is presented in the... more
In this paper, stable adaptive formation control algorithms for two-dimensional models of aircraft are developed in the presence of unknown leader commands and disturbances due to vortex effects. The analysis is presented in the leader-follower frame for three cases of unknown leader commands and vortex forces in the velocity and heading angle dynamics. The algorithms are applied to the formation
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For time-delayed dependent scalable differentiated services (DiffServ) networks the use of robust control techniques are essential for addressing the congestion control problem. Sliding mode-based variable structure control (SM-VSC)... more
For time-delayed dependent scalable differentiated services (DiffServ) networks the use of robust control techniques are essential for addressing the congestion control problem. Sliding mode-based variable structure control (SM-VSC) technique robustness capabilities are utilized in this paper to design on the basis of an inaccurate/uncertain model, a new congestion control algorithm. The utilized fluid flow model (FFM) is of low order
Research Interests: Congestion Control, Markov Processes, Queueing theory, Robust control, Fluid Dynamics, and 13 moreStability, Control Systems, Probability, Time Delay, Stability Analysis, Sliding mode control, Fluid flow, Robustness, Variable Structure Control, Delays, Sliding Mode, Probabilistic Model, and Difference Operator
This paper presents a new robust dynamic congestion control for a network of control systems. Due to an intensive flow of information/data between sensors, decision makers and actuators in the network, synchronization and planning of... more
This paper presents a new robust dynamic congestion control for a network of control systems. Due to an intensive flow of information/data between sensors, decision makers and actuators in the network, synchronization and planning of information/data arrivals, departures, updates and optimal resource allocations take on a significant degree of importance. Sliding mode based variable structure techniques provide robust solutions for complex, nonlinear and strongly coupled control problems and are well-known for their rich analysis and design methodologies. Among the number of possible variable structure algorithms, the proposed controller in this paper is based on the Fliess's approach known as the generalized variable structure (GVS). Introduced recently, this new variable structure approach is designed in the context of differential algebra. Containing principally the derivative of the input, the new observable canonical form is used for design of the controller. Thereby facilitating the main benefit of this algorithm as far as reducing the correspondingly known chattering phenomena that is the main drawback in standard variable structure control (VSC) techniques.
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ABSTRACT In this paper, a new robust congestion control strategy is proposed for a multi-services architecture, namely a Differentiated-Services (DiffServ) network. In virtue of their robustness capabilities, Sliding Mode-based Variable... more
ABSTRACT In this paper, a new robust congestion control strategy is proposed for a multi-services architecture, namely a Differentiated-Services (DiffServ) network. In virtue of their robustness capabilities, Sliding Mode-based Variable Structure Control (SM-VSC) techniques are utilized to design our proposed controller on the basis of an inaccurate/uncertain Fluid Flow Model (FFM). Developed for an interconnected network as a hop-by-hop distributed control scheme, the proposed algorithm is shown to achieve the desired performance specifications and requirements. Moreover, the error dynamics of the overall time delay dependent network is analytically shown to be L2 stable.
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ABSTRACT The problem of robust fault detection and isolation (FDI) for nonlinear systems is investigated in this paper. The proposed FDI scheme employs a neural network-based observer for detecting and identifying the severity of actuator... more
ABSTRACT The problem of robust fault detection and isolation (FDI) for nonlinear systems is investigated in this paper. The proposed FDI scheme employs a neural network-based observer for detecting and identifying the severity of actuator gain faults in the presence of disturbances and uncertainties in the model and sensory measurements. The neural network weights are updated based on a modified dynamic backpropagation scheme. The proposed FDI scheme does not rely on the availability of full state measurements. In most work in the literature, the fault function acts as an additive (bias) term, whereas in our scheme the fault function acts as a multiplicative (gain) term. This representation makes the stability analysis of the overall FDI scheme rather challenging. Stability properties of the proposed fault detection scheme in the presence of unknown actuator gain faults as well as plant and sensor uncertainties are demonstrated by using Lyapunov's direct method with no restrictive assumptions on the system and/or the FDI algorithm. The performance of our proposed FDI approach is evaluated through simulations performed on a reaction wheel type actuator that is commonly employed in the attitude control subsystem (ACS) of a satellite.
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Research Interests: Topology, Synchronization, Communication Networks, Multi Agent System, Nonlinear Systems, and 15 moreDistributed Control, Multi Agent Systems, Tracking, Lyapunov Stability, Distributed Parameter Systems, System Simulation, Formation Control, Community Networks, Nonlinear system, Network Topology, Switches, Control Algorithm, Synchronisation, Switching Network, and Symmetric Matrices
ABSTRACT In this paper, we first introduce a distributed control strategy for velocity synchronization (or velocity consensus seeking) of multiple heterogeneous Euler-Lagrange (EL) systems with switching communication network topologies.... more
ABSTRACT In this paper, we first introduce a distributed control strategy for velocity synchronization (or velocity consensus seeking) of multiple heterogeneous Euler-Lagrange (EL) systems with switching communication network topologies. This controller is denoted as the “nominal” controller. To guarantee velocity synchronization for switching communication network topologies we require existence of non-vanishing dwell-time between any two sequential switches. Next, we consider two types of actuator faults namely (1) additive actuator fault, and (2) loss of effectiveness actuator fault. By employing the nominal control algorithm developed for velocity synchronization, we introduce two control algorithms for velocity synchronization in presence of the two types of faults. Simulation results illustrate and demonstrate the effectiveness of our proposed control algorithms.
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The main goal of this work is to design a decentralized optimal control for a team of multi-agents that can accomplish consensus in a leaderless structure. Towards this end, a semi-decentralized optimal control strategy is designed based... more
The main goal of this work is to design a decentralized optimal control for a team of multi-agents that can accomplish consensus in a leaderless structure. Towards this end, a semi-decentralized optimal control strategy is designed based on minimization of individual cost functions using local information and based on solving HJB equations. The interaction between agents due to information flow
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ABSTRACT
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The problem of estimating the directions of multiple plane waves using an array of sensors has received considerable attention in the recent signal processing literature. A re-view of the most commonly used estimation techniques can be... more
The problem of estimating the directions of multiple plane waves using an array of sensors has received considerable attention in the recent signal processing literature. A re-view of the most commonly used estimation techniques can be found in [3]. In sensor array applications, ...
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ABSTRACT In this paper a new fault accommodation algorithm based on a two-level architecture is proposed for satellite formation missions. In this two-level framework, the notion of formation-level fault recovery (FLFR) is proposed, and... more
ABSTRACT In this paper a new fault accommodation algorithm based on a two-level architecture is proposed for satellite formation missions. In this two-level framework, the notion of formation-level fault recovery (FLFR) is proposed, and the task of performance monitoring (PM) is defined in the high level (HL). By using the information provided by the PM module, the FLFR is capable of accommodating the ldquounhealthy satelliterdquo that is partially recovered (due to the inexact and inaccurate estimation of the fault by the fault diagnosis and identification (FDI) modules) in the low-level fault recovery (LLFR), but is detected and labeled as ldquounhealthyrdquo by the PM module. Consequently, fault is cooperatively recovered by our proposed architecture, and the specifications of formation mission are satisfied. Simulation results confirm the validity and effectiveness of our proposed algorithm.
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ABSTRACT In this paper, a new robust feedback linearization congestion control strategy for a fluid flow model is introduced. The recourse to a robust control technique permits us to use a non accurate dynamic model in order to design and... more
ABSTRACT In this paper, a new robust feedback linearization congestion control strategy for a fluid flow model is introduced. The recourse to a robust control technique permits us to use a non accurate dynamic model in order to design and analyze the controlled system. The fluid flow model (FFM) under its different types of variants is used for network performance evaluation and control as applied to congestion control. Validated by several researchers, the considered first order non linear model is simple in comparison to the detailed Markovian queuing probabilistic models, and it captures the dominant dynamic behavior of a wide range of queuing systems. The sliding mode generalized variable structure (SM-GVS) control recently introduced by M. Fliess which is based on differential algebra concepts allows the switching to take place on the highest derivative of the control input such that the main drawbacks of the discontinuous control that is the chattering is consequently reduced. In this paper, our proposed controller uses the feedback linearization-based SM-GVS approach with some convergence tuning parameters
Research Interests: Algebra, Differential Algebra, Congestion Control, Markov Processes, Queueing theory, and 15 moreConvergence, Robust control, Fluid Dynamics, Controllability, Linear Model, Observability, Feedback, Sliding mode control, Network Performance, Fluid flow, Tuning, Feedback Linearization, Probabilistic Model, canonical form, and Queuing System
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ABSTRACT The main objective of this paper is development of a fault diagnosis, isolation and detection technique that is constructed based on the interacting multiple model (IMM) algorithm for partial (soft) or total (hard) reaction wheel... more
ABSTRACT The main objective of this paper is development of a fault diagnosis, isolation and detection technique that is constructed based on the interacting multiple model (IMM) algorithm for partial (soft) or total (hard) reaction wheel failures in the spacecraft attitude control system (ACS). Based on different scenarios and assumptions, we develop healthy models of the ACS under various operating conditions and construct faulty modes with respect to temperature changes, power supply line voltage changes, torque variations, and unexpected current variations in each motor axis windings of the reaction wheels. Once a fault mode is detected and isolated, we are capable to develop in certain conditions the recovery procedure through feedback control strategies for the ACS
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... In particular, I truly thank Hessam for his generosity in being always close to our parents so that they could better cope with the emotional suffer-ings over the years that I have been away from them. Montreal, Canada Ehsan... more
... In particular, I truly thank Hessam for his generosity in being always close to our parents so that they could better cope with the emotional suffer-ings over the years that I have been away from them. Montreal, Canada Ehsan Sobhani-Tehrani xi Page 11. ...
ABSTRACT In this work, a novel framework for optimal cooperative supervisory estimation of multi-agent linear time- invariant (LTI) systems is proposed which is applicable to a large class of multi-agent systems. This framework was... more
ABSTRACT In this work, a novel framework for optimal cooperative supervisory estimation of multi-agent linear time- invariant (LTI) systems is proposed which is applicable to a large class of multi-agent systems. This framework was recently developed by the authors based on the notion of sub-observers and a discrete-event system (DES) supervisory control. Each sub-observer estimates certain states that are conditioned on given inputs, outputs, and states information. Moreover, the cooperation among the sub-observers is managed by a DES supervisor. In this work, our proposed supervisory estima- tion framework is extended to the combinatorial optimization domain. When certain anomalies (faults) are present in the system, or the sensors and sub-observers become unreliable, the proposed optimal DES supervisor makes decisions regarding the selection and reconfiguration of sets of sub-observers to es- timate all the system states, while simultaneously a performance index that incorporates the communication cost, computation cost, and reconfiguration cost, and the number of invalid state estimates is minimized. The application of our proposed methodology in a practical industrial process is demonstrated through numerical simulations.