Edwin Yaz | Marquette Univeristy (original) (raw)
Papers by Edwin Yaz
Proceedings of the International Conference of Control, Dynamic systems, and Robotics, Jun 1, 2024
In this paper, static output feedback control is proposed to stabilize a general class of discret... more In this paper, static output feedback control is proposed to stabilize a general class of discrete-time stochastic nonlinear systems. Knowledge of the precise form of the nonlinearity or its statistics are not required. Instead, it is only necessary that a bound on the second moment of nonlinearity can be determined. The control gain is determined by solving a linear matrix inequality which is sufficient to show that the controlled system is stable in the mean square and almost sure senses.
Automatica, Jul 1, 2007
Linear minimum variance unbiased state estimation is considered for systems with uncertain parame... more Linear minimum variance unbiased state estimation is considered for systems with uncertain parameters in their state space models and sensor failures. The existing results are generalized to the case where each sensor may fail at any sample time independently of the others. For robust performance, stochastic parameter perturbations are included in the system matrix. Also, stochastic perturbations are allowed in the estimator gain to guarantee resilient operation. An illustrative example is included to demonstrate performance improvement over the Kalman filter which does not include sensor failures in its measurement model.
2021 American Control Conference (ACC), 2021
The problem of intermittent and random actuator faults is important in many applications, especia... more The problem of intermittent and random actuator faults is important in many applications, especially in wireless systems where interruptions in communication between the plant, the actuators, and the sensors are not uncommon. Much of the work in this topic focuses on fault-tolerant control when the statistics of the faults are known a priori. In this work, the case where the statistics of the actuator faults are unknown is addressed. A modified Kalman filter is used to identify the unknown fault statistics, and this information is used in a technique that can compensate for the intermittent actuator faults. In addition to the theoretical analysis, several simulations involving a DC motor that experiences intermittent actuator faults are used to demonstrate the effectiveness of the proposed compensation method.
ACS Sensors, 2016
This work investigates a sensor system for direct groundwater monitoring, capable of aqueous-phas... more This work investigates a sensor system for direct groundwater monitoring, capable of aqueous-phase measurement of aromatic hydrocarbons at low concentrations (about 100 parts per billion (ppb)). The system is designed to speciate and quantify benzene, toluene, and ethylbenzene/xylenes (BTEX) in the presence of potential interferents. The system makes use of polymer-coated shear-horizontal surface acoustic wave devices and a signal processing method based on estimation theory, specifically a bank of extended Kalman filters (EKFs). This approach permits estimation of BTEX concentrations even from noisy data, well before the sensor response reaches equilibrium. To utilize estimation theory, an analytical model for the sensor response to stepchanges, starting from clean water, to mixtures of multiple analytes is first formulated that makes use of both equilibrium frequency shifts and response times (for individual analyte), the latter being specific for each combination of coated device and analyte. The model is then transformed into state-space form, and the bank of EKFs is used to estimate BTEX concentrations in the presence of interferents from transient responses prior to attainment of equilibrium. Samples used in the experiments were either manually mixed in the laboratory or taken from real monitoring sites; they contained multiple chemically similar analytes with concentrations of individual BTEX compounds in the range of 10-2000 ppb. The estimated BTEX concentrations were compared to independent gas chromatography measurements and found to be in very good agreement (within about 5-10% accuracy), even when the sample contained multiple interferents such as larger aromatic compounds or aliphatic hydrocarbons.
ACS Sensors, 2019
Most chemical sensors are only partially selective to any specific target analyte(s), making iden... more Most chemical sensors are only partially selective to any specific target analyte(s), making identification and quantification of analyte mixtures challenging, a problem often addressed using arrays of partially selective sensors. This work presents and experimentally verifies a signal-processing technique based on estimation theory for online identification and quantification of multiple analytes using only the response data collected from a single polymer-coated sensor device. The demonstrated technique, based on multiple stages of exponentially weighted recursive least-squares estimation (EW-RLSE), first determines which of the analytes included in the sensor response model are absent from the mixture being analyzed; these are then eliminated from the model prior to executing the final stage of EW-RLSE, in which the sample's constituent analytes are more accurately quantified. The overall method is based on a sensor response model with specific parameters describing each coatinganalyte pair and requires no initial assumptions regarding the concentrations of the analytes in a given sample. The technique was tested using the measured responses of polymer-coated shear-horizontal surface acoustic wave devices to multi-analyte mixtures of benzene, toluene, ethylbenzene, xylenes, and 1,2,4-trimethylbenzene in water. The results demonstrate how this method accurately identifies and quantifies the analytes present in a sample using the measured response of just a single sensor device. This effective, simple, lower-cost alternative to sensor arrays needs no arduous training protocol, just measurement of the response characteristics of each individual target analyte and the likely interferents and/or classes thereof.
Proceedings of 1994 American Control Conference - ACC '94
ABSTRACT
IEEE Transactions on Automatic Control, 2019
As missing sensor data may severely degrade the overall system performance and stability, reliabl... more As missing sensor data may severely degrade the overall system performance and stability, reliable state estimation is of great importance in modern data-intensive control, computing, and power systems applications. Aiming at providing a more robust and resilient state estimation technique, this paper presents a novel secondorder fault-tolerant extended Kalman filter estimation framework for discrete-time stochastic nonlinear systems under sensor failures, bounded observer-gain perturbation, extraneous noise, and external disturbances condition. The failure mechanism of multiple sensors is assumed to be independent of each other with various
Volume 4: Dynamics, Control and Uncertainty, Parts A and B, 2012
A novel non-linear estimation based micro-cantilever bio-chemical rheological sensing technique i... more A novel non-linear estimation based micro-cantilever bio-chemical rheological sensing technique is proposed in this paper. Contrary to classical rheological measurements using micro-cantilevers, which is either restricted to resonant phenomena, or based on the measurement of fluid properties over a range of vibration frequencies, the proposed measurement technique can be applied to arbitrary available vibration frequency. By applying non-linear estimation technique, the fluid characteristic parameters including density and viscosity, can be estimated and used to quantify fluid properties. The preliminary simulation studies demonstrate that vibrating micro-cantilevers with nonlinear estimation can be used as effective and robust fluid characterization micro-system in liquid environments. The proposed technique is encouraging for the development of a useful micro-rheometer on a silicon chip for fluid detection application.
IEEE Transactions on Energy Conversion, 2008
The advantages and demerits of a 5-hp Induction Motor reconfigurable induction motor, which was d... more The advantages and demerits of a 5-hp Induction Motor reconfigurable induction motor, which was designed for Faults experimental emulation of stator winding inter-turn and broken rotor bar faults, are presented in this paper. It was perceived f kdricAI f chanicc that this motor has the potential of quick and easy F-a J u ' l FaLili reconfiguration to produce the desired stator and rotor faults in a variety of different fault combinations. Accordingly, this would M sr rt) Ffnillt FrLilt. I
Extensions of sliding-mode adaptive observer are presented for state reconstruction of nonlinear ... more Extensions of sliding-mode adaptive observer are presented for state reconstruction of nonlinear systems with uncertainty having unknown bounds. The observer uses nonlinear gains that are smoothened versions of classical sliding-mode gains and they are continuously updated to guarantee a globally stable observation error. This observer is applied to Chua’s circuit in a chaotic synchronization scheme. A generalization to known waveform type disturbances and measurement uncertainties is pointed out. �S0022-0434�00�02304-2�
A novel robust/adaptive observer is presented for state reconstruction of nonlinear systems with ... more A novel robust/adaptive observer is presented for state reconstruction of nonlinear systems with uncertainty having unknown bounds. The observer uses a nonlinear gain which is continuously adapted to guarantee a uniformly bounded and convergent observation error. Some generalizations to known waveform type disturbances and measurement uncertainties are pointed out.
Journal of Dynamic Systems, Measurement, and Control
This paper considers a novel coupled state-dependent Riccati equation (SDRE) approach for systema... more This paper considers a novel coupled state-dependent Riccati equation (SDRE) approach for systematically designing nonlinear quadratic regulator (NLQR) and H∞ control of mechatronics systems. The state-dependent feedback control solutions can be obtained by solving a pair of coupled SDREs, guaranteeing nonlinear quadratic optimality with inherent stability property in combination with robust L2 type of disturbance reduction. The derivation of this control strategy is based on Nash's game theory. Both finite and infinite horizon control problems are discussed. An under-actuated robotic system, Furuta rotary pendulum, is used to examine the effectiveness and robustness of this novel nonlinear control approach.
2015 54th IEEE Conference on Decision and Control (CDC), 2015
This paper uses the concept of D-stability to place the eigenvalues of the linear component of bo... more This paper uses the concept of D-stability to place the eigenvalues of the linear component of both the controller and observer within separate circular regions in order to design a robust dynamic feedback controller using linear matrix inequality (LMI) techniques to accommodate Lipschitz type nonlinearities for continuous-time systems. Given a feasible result for both the controller and observer design, the regions will be separated in such a way that the state estimation error goes to zero much faster than the state while guaranteeing stability. This design technique is extended to incorporate the H2-norm property. The method is applied to two nonlinear systems to illustrate the design procedure.
2015 54th IEEE Conference on Decision and Control (CDC), 2015
This work analyzes the energy gain of the discrete-time extended Kalman filter used as a nonlinea... more This work analyzes the energy gain of the discrete-time extended Kalman filter used as a nonlinear observer in the presence of stochastic ℓ2 type disturbances to highlight another theoretical property of the ubiquitous extended Kalman filter. The stochastic analysis provides a bound on the ratio of estimation error energy to disturbance energy, which shows that along with being the locally optimal minimum variance estimator, the extended Kalman filter inherently has the H∞-property. A special case of this result is also shown to be the H2-property of the extended Kalman filter.
2016 American Control Conference (ACC), 2016
This work analyzes the finite-time H<sub>∞</sub>-property of the discrete-time extend... more This work analyzes the finite-time H<sub>∞</sub>-property of the discrete-time extended Kalman filter in the presence of uncertain measurements and stochastic ℓ<sub>2</sub> type disturbances. The stochastic analysis provides a bound on the ratio of estimation error energy to disturbance energy. A special case of this result is also shown to be the finite-time H<sub>2</sub>-property of the extended Kalman filter.
2015 European Control Conference (ECC), 2015
In this work, a procedure is presented for performance analysis intended to evaluate the resilien... more In this work, a procedure is presented for performance analysis intended to evaluate the resilience and H2 norm bound of discrete-time systems controlled by full-order dynamic feedback compensators. Acceptable performance is specified by disks in the complex plane within which the eigenvalues of the controller and the observer remain in the presence of perturbations in the controller and observer gains. Maximum gain perturbation bounds can be obtained based on the designer's choices of controller and observer eigenvalue regions and the resulting H2-norm bound is calculated. The linear matrix inequality technique is used throughout the analysis process. Illustrative examples are included to demonstrate the effectiveness of the proposed methodology.
2018 Annual American Control Conference (ACC), 2018
Cybersecurity is a major concern for designers of control systems that can be directed against an... more Cybersecurity is a major concern for designers of control systems that can be directed against any of their components. Observers are an integral part of control systems that require state feedback. This paper considers an observer subject to errors in implementation or subject to cyberattacks. The errors and cyberattacks result in perturbations in the gain and in a finite-energy but unknown disturbance input. We obtain conditions for Q-S-R dissipativity and stability of the observer in the presence of the gain errors and disturbances in the form of linear matrix inequalities (LMIs). Three examples are presented to show how the LMIs can yield resilient observer designs.
In this work, three adaptive estimation methods are considered for the identification of the stat... more In this work, three adaptive estimation methods are considered for the identification of the stator winding resistance of an interior permanent magnet motor. The layout of the magnets in the motor under consideration produces a trapezoidal back electromotive force (emf), which is more challenging for the estimators due to the introduction of higher order harmonics. The three estimation techniques are compared in terms of accuracy in estimating the true parameter value. The multiple model estimation (MME) algorithm utilizing Kalman filters provides the most accurate estimate with the least computational complexity while the additional complexity of the extended Kalman filter (EKF) and the fading memory extended Kalman filter (FM-EKF) results in a poor estimate of the parameter.
In this paper, state-space modeling techniques and nonlinear state/parameter estimation are appli... more In this paper, state-space modeling techniques and nonlinear state/parameter estimation are applied to the analysis of the dynamic response of microcantilevers in determining the viscosity and density of viscous fluid loads. Unlike classical methods used to analyze fluid-loaded microcantilevers, the approach presented in this paper is based on the transient response of the fluid-beam system rather than its frequency response. A state-space model describing the dynamic behavior of the fluid-beam system is developed. Then, Extended Kalman Filter is employed to estimate the fluid properties based on temporal measurements of the deflection of an externally excited microcantilever placed in the fluid. Results of the analysis for a wide range of excitation frequencies and viscosities show that good estimates with less than 10% error can be obtained irrespective of whether the excitation frequency is close to the resonant frequency or not.
Proceedings of the International Conference of Control, Dynamic systems, and Robotics, Jun 1, 2024
In this paper, static output feedback control is proposed to stabilize a general class of discret... more In this paper, static output feedback control is proposed to stabilize a general class of discrete-time stochastic nonlinear systems. Knowledge of the precise form of the nonlinearity or its statistics are not required. Instead, it is only necessary that a bound on the second moment of nonlinearity can be determined. The control gain is determined by solving a linear matrix inequality which is sufficient to show that the controlled system is stable in the mean square and almost sure senses.
Automatica, Jul 1, 2007
Linear minimum variance unbiased state estimation is considered for systems with uncertain parame... more Linear minimum variance unbiased state estimation is considered for systems with uncertain parameters in their state space models and sensor failures. The existing results are generalized to the case where each sensor may fail at any sample time independently of the others. For robust performance, stochastic parameter perturbations are included in the system matrix. Also, stochastic perturbations are allowed in the estimator gain to guarantee resilient operation. An illustrative example is included to demonstrate performance improvement over the Kalman filter which does not include sensor failures in its measurement model.
2021 American Control Conference (ACC), 2021
The problem of intermittent and random actuator faults is important in many applications, especia... more The problem of intermittent and random actuator faults is important in many applications, especially in wireless systems where interruptions in communication between the plant, the actuators, and the sensors are not uncommon. Much of the work in this topic focuses on fault-tolerant control when the statistics of the faults are known a priori. In this work, the case where the statistics of the actuator faults are unknown is addressed. A modified Kalman filter is used to identify the unknown fault statistics, and this information is used in a technique that can compensate for the intermittent actuator faults. In addition to the theoretical analysis, several simulations involving a DC motor that experiences intermittent actuator faults are used to demonstrate the effectiveness of the proposed compensation method.
ACS Sensors, 2016
This work investigates a sensor system for direct groundwater monitoring, capable of aqueous-phas... more This work investigates a sensor system for direct groundwater monitoring, capable of aqueous-phase measurement of aromatic hydrocarbons at low concentrations (about 100 parts per billion (ppb)). The system is designed to speciate and quantify benzene, toluene, and ethylbenzene/xylenes (BTEX) in the presence of potential interferents. The system makes use of polymer-coated shear-horizontal surface acoustic wave devices and a signal processing method based on estimation theory, specifically a bank of extended Kalman filters (EKFs). This approach permits estimation of BTEX concentrations even from noisy data, well before the sensor response reaches equilibrium. To utilize estimation theory, an analytical model for the sensor response to stepchanges, starting from clean water, to mixtures of multiple analytes is first formulated that makes use of both equilibrium frequency shifts and response times (for individual analyte), the latter being specific for each combination of coated device and analyte. The model is then transformed into state-space form, and the bank of EKFs is used to estimate BTEX concentrations in the presence of interferents from transient responses prior to attainment of equilibrium. Samples used in the experiments were either manually mixed in the laboratory or taken from real monitoring sites; they contained multiple chemically similar analytes with concentrations of individual BTEX compounds in the range of 10-2000 ppb. The estimated BTEX concentrations were compared to independent gas chromatography measurements and found to be in very good agreement (within about 5-10% accuracy), even when the sample contained multiple interferents such as larger aromatic compounds or aliphatic hydrocarbons.
ACS Sensors, 2019
Most chemical sensors are only partially selective to any specific target analyte(s), making iden... more Most chemical sensors are only partially selective to any specific target analyte(s), making identification and quantification of analyte mixtures challenging, a problem often addressed using arrays of partially selective sensors. This work presents and experimentally verifies a signal-processing technique based on estimation theory for online identification and quantification of multiple analytes using only the response data collected from a single polymer-coated sensor device. The demonstrated technique, based on multiple stages of exponentially weighted recursive least-squares estimation (EW-RLSE), first determines which of the analytes included in the sensor response model are absent from the mixture being analyzed; these are then eliminated from the model prior to executing the final stage of EW-RLSE, in which the sample's constituent analytes are more accurately quantified. The overall method is based on a sensor response model with specific parameters describing each coatinganalyte pair and requires no initial assumptions regarding the concentrations of the analytes in a given sample. The technique was tested using the measured responses of polymer-coated shear-horizontal surface acoustic wave devices to multi-analyte mixtures of benzene, toluene, ethylbenzene, xylenes, and 1,2,4-trimethylbenzene in water. The results demonstrate how this method accurately identifies and quantifies the analytes present in a sample using the measured response of just a single sensor device. This effective, simple, lower-cost alternative to sensor arrays needs no arduous training protocol, just measurement of the response characteristics of each individual target analyte and the likely interferents and/or classes thereof.
Proceedings of 1994 American Control Conference - ACC '94
ABSTRACT
IEEE Transactions on Automatic Control, 2019
As missing sensor data may severely degrade the overall system performance and stability, reliabl... more As missing sensor data may severely degrade the overall system performance and stability, reliable state estimation is of great importance in modern data-intensive control, computing, and power systems applications. Aiming at providing a more robust and resilient state estimation technique, this paper presents a novel secondorder fault-tolerant extended Kalman filter estimation framework for discrete-time stochastic nonlinear systems under sensor failures, bounded observer-gain perturbation, extraneous noise, and external disturbances condition. The failure mechanism of multiple sensors is assumed to be independent of each other with various
Volume 4: Dynamics, Control and Uncertainty, Parts A and B, 2012
A novel non-linear estimation based micro-cantilever bio-chemical rheological sensing technique i... more A novel non-linear estimation based micro-cantilever bio-chemical rheological sensing technique is proposed in this paper. Contrary to classical rheological measurements using micro-cantilevers, which is either restricted to resonant phenomena, or based on the measurement of fluid properties over a range of vibration frequencies, the proposed measurement technique can be applied to arbitrary available vibration frequency. By applying non-linear estimation technique, the fluid characteristic parameters including density and viscosity, can be estimated and used to quantify fluid properties. The preliminary simulation studies demonstrate that vibrating micro-cantilevers with nonlinear estimation can be used as effective and robust fluid characterization micro-system in liquid environments. The proposed technique is encouraging for the development of a useful micro-rheometer on a silicon chip for fluid detection application.
IEEE Transactions on Energy Conversion, 2008
The advantages and demerits of a 5-hp Induction Motor reconfigurable induction motor, which was d... more The advantages and demerits of a 5-hp Induction Motor reconfigurable induction motor, which was designed for Faults experimental emulation of stator winding inter-turn and broken rotor bar faults, are presented in this paper. It was perceived f kdricAI f chanicc that this motor has the potential of quick and easy F-a J u ' l FaLili reconfiguration to produce the desired stator and rotor faults in a variety of different fault combinations. Accordingly, this would M sr rt) Ffnillt FrLilt. I
Extensions of sliding-mode adaptive observer are presented for state reconstruction of nonlinear ... more Extensions of sliding-mode adaptive observer are presented for state reconstruction of nonlinear systems with uncertainty having unknown bounds. The observer uses nonlinear gains that are smoothened versions of classical sliding-mode gains and they are continuously updated to guarantee a globally stable observation error. This observer is applied to Chua’s circuit in a chaotic synchronization scheme. A generalization to known waveform type disturbances and measurement uncertainties is pointed out. �S0022-0434�00�02304-2�
A novel robust/adaptive observer is presented for state reconstruction of nonlinear systems with ... more A novel robust/adaptive observer is presented for state reconstruction of nonlinear systems with uncertainty having unknown bounds. The observer uses a nonlinear gain which is continuously adapted to guarantee a uniformly bounded and convergent observation error. Some generalizations to known waveform type disturbances and measurement uncertainties are pointed out.
Journal of Dynamic Systems, Measurement, and Control
This paper considers a novel coupled state-dependent Riccati equation (SDRE) approach for systema... more This paper considers a novel coupled state-dependent Riccati equation (SDRE) approach for systematically designing nonlinear quadratic regulator (NLQR) and H∞ control of mechatronics systems. The state-dependent feedback control solutions can be obtained by solving a pair of coupled SDREs, guaranteeing nonlinear quadratic optimality with inherent stability property in combination with robust L2 type of disturbance reduction. The derivation of this control strategy is based on Nash's game theory. Both finite and infinite horizon control problems are discussed. An under-actuated robotic system, Furuta rotary pendulum, is used to examine the effectiveness and robustness of this novel nonlinear control approach.
2015 54th IEEE Conference on Decision and Control (CDC), 2015
This paper uses the concept of D-stability to place the eigenvalues of the linear component of bo... more This paper uses the concept of D-stability to place the eigenvalues of the linear component of both the controller and observer within separate circular regions in order to design a robust dynamic feedback controller using linear matrix inequality (LMI) techniques to accommodate Lipschitz type nonlinearities for continuous-time systems. Given a feasible result for both the controller and observer design, the regions will be separated in such a way that the state estimation error goes to zero much faster than the state while guaranteeing stability. This design technique is extended to incorporate the H2-norm property. The method is applied to two nonlinear systems to illustrate the design procedure.
2015 54th IEEE Conference on Decision and Control (CDC), 2015
This work analyzes the energy gain of the discrete-time extended Kalman filter used as a nonlinea... more This work analyzes the energy gain of the discrete-time extended Kalman filter used as a nonlinear observer in the presence of stochastic ℓ2 type disturbances to highlight another theoretical property of the ubiquitous extended Kalman filter. The stochastic analysis provides a bound on the ratio of estimation error energy to disturbance energy, which shows that along with being the locally optimal minimum variance estimator, the extended Kalman filter inherently has the H∞-property. A special case of this result is also shown to be the H2-property of the extended Kalman filter.
2016 American Control Conference (ACC), 2016
This work analyzes the finite-time H<sub>∞</sub>-property of the discrete-time extend... more This work analyzes the finite-time H<sub>∞</sub>-property of the discrete-time extended Kalman filter in the presence of uncertain measurements and stochastic ℓ<sub>2</sub> type disturbances. The stochastic analysis provides a bound on the ratio of estimation error energy to disturbance energy. A special case of this result is also shown to be the finite-time H<sub>2</sub>-property of the extended Kalman filter.
2015 European Control Conference (ECC), 2015
In this work, a procedure is presented for performance analysis intended to evaluate the resilien... more In this work, a procedure is presented for performance analysis intended to evaluate the resilience and H2 norm bound of discrete-time systems controlled by full-order dynamic feedback compensators. Acceptable performance is specified by disks in the complex plane within which the eigenvalues of the controller and the observer remain in the presence of perturbations in the controller and observer gains. Maximum gain perturbation bounds can be obtained based on the designer's choices of controller and observer eigenvalue regions and the resulting H2-norm bound is calculated. The linear matrix inequality technique is used throughout the analysis process. Illustrative examples are included to demonstrate the effectiveness of the proposed methodology.
2018 Annual American Control Conference (ACC), 2018
Cybersecurity is a major concern for designers of control systems that can be directed against an... more Cybersecurity is a major concern for designers of control systems that can be directed against any of their components. Observers are an integral part of control systems that require state feedback. This paper considers an observer subject to errors in implementation or subject to cyberattacks. The errors and cyberattacks result in perturbations in the gain and in a finite-energy but unknown disturbance input. We obtain conditions for Q-S-R dissipativity and stability of the observer in the presence of the gain errors and disturbances in the form of linear matrix inequalities (LMIs). Three examples are presented to show how the LMIs can yield resilient observer designs.
In this work, three adaptive estimation methods are considered for the identification of the stat... more In this work, three adaptive estimation methods are considered for the identification of the stator winding resistance of an interior permanent magnet motor. The layout of the magnets in the motor under consideration produces a trapezoidal back electromotive force (emf), which is more challenging for the estimators due to the introduction of higher order harmonics. The three estimation techniques are compared in terms of accuracy in estimating the true parameter value. The multiple model estimation (MME) algorithm utilizing Kalman filters provides the most accurate estimate with the least computational complexity while the additional complexity of the extended Kalman filter (EKF) and the fading memory extended Kalman filter (FM-EKF) results in a poor estimate of the parameter.
In this paper, state-space modeling techniques and nonlinear state/parameter estimation are appli... more In this paper, state-space modeling techniques and nonlinear state/parameter estimation are applied to the analysis of the dynamic response of microcantilevers in determining the viscosity and density of viscous fluid loads. Unlike classical methods used to analyze fluid-loaded microcantilevers, the approach presented in this paper is based on the transient response of the fluid-beam system rather than its frequency response. A state-space model describing the dynamic behavior of the fluid-beam system is developed. Then, Extended Kalman Filter is employed to estimate the fluid properties based on temporal measurements of the deflection of an externally excited microcantilever placed in the fluid. Results of the analysis for a wide range of excitation frequencies and viscosities show that good estimates with less than 10% error can be obtained irrespective of whether the excitation frequency is close to the resonant frequency or not.