Kian Jalaleddini - Academia.edu (original) (raw)
Papers by Kian Jalaleddini
IFAC Proceedings Volumes, 2011
This paper describes an algorithm to identify state-space models for single input single output (... more This paper describes an algorithm to identify state-space models for single input single output (SISO) Hammerstein structures based on input-output measurements. The algorithm consists of two main steps. First, a subspace algorithm is used to determine the system order and estimate the A and C system matrices. Estimation of the other state space matrices as well as the nonlinearity is then formulated as nonlinear optimization problem in which the state space model of the linear component and the coefficients of the basis function expansion of the nonlinear component are distinct. This formulation minimizes the number of parameters to estimate; moreover any one parameter is related to either the linear dynamics or the static nonlinearity. The unknown parameters are then estimated using an iterative procedure that solves a least square problem at each step. Simulation studies using a well known model of ankle joint reflex stiffness demonstrate that the algorithm is accurate and performs well in the non-ideal conditions that prevail during practical experiments.
It is not trivial to acquire data under stationary conditions from biomedical systems since they ... more It is not trivial to acquire data under stationary conditions from biomedical systems since they frequently show time-varying and/or switching behaviour. It is often possible to acquire short segments of stationary data and repeat the experiment many times. However, initial conditions contribute substantially to the transient response and must therefore be accounted for explicitly. This paper presents a subspace algorithm for the identification of Hammerstein systems from short segments of data that estimates the initial condition of each segment and the parameters of the nonlinearity, as well as a state-space model for the linear part. A previously developed algorithm suffers from two issues. Firstly, all segments had to be equal lengths, and secondly the algorithm provided an over-parameterized model of the Hammerstein system rather than an individual model for each component of the cascade. We resolved the first issue by introducing a new formulation of the problem and the second one by developing an iterative method to separate the estimated parameters. Simulation results on Hammerstein model of reflex joint stiffness show the algorithm is capable of identifying accurate models even with noisy data. We also show the application of this algorithm on a set of experimental data acquired from one subject.
Globecom 2009 2009 Ieee Global Telecommunications Conference, Nov 1, 2009
In this paper, the problem of resource allocation in IS-856 uplink in the presence of time-delay ... more In this paper, the problem of resource allocation in IS-856 uplink in the presence of time-delay is studied. A set of nonlinear adaptive controllers are designed to stabilize the wireless network and use the system resources efficiently. The controllers obtained are then modified properly to retain network stability and performance in the presence of time-delay. Simulation results are presented to show the effectiveness of the proposed approach.
Proceedings of the 2009 Ieee International Conference on Communications, Jun 14, 2009
In this paper, data-rate assignment in IS-856 uplink (reverse link) is studied. The problem is fi... more In this paper, data-rate assignment in IS-856 uplink (reverse link) is studied. The problem is first formulated in an interference model framework, and then a dynamic control strategy is developed for efficient rate assignment. In the first step, the controller is designed for the special case when the number of users in the network is fixed. Then, the minimum time
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015
The dynamic relationship between the joint position and reflex EMG in ankle muscles of healthy hu... more The dynamic relationship between the joint position and reflex EMG in ankle muscles of healthy human subjects was studied for time-varying (TV) contractions. A linear parameter varying (LPV) identification algorithm was used to estimate the Hammerstein system relating ankle position to the reflex EMG response. The estimated Hammerstein system comprised a time-invariant (TI) linear element and a TV static nonlinearity that resembled a half-wave rectifier with a threshold and linear gain. The results demonstrated a systematic change in the reflex nonlinearity with the activation level. The gain of TV nonlinearity increased with activation level reaching its peak at 20-30% maximum voluntary contraction and then decreased. The threshold of the nonlinearity decreased with increasing activation level reaching it minimum at the same point where the gain was maximal. Using the LPV-Hammerstein method in this work, the underlying TV dynamics were extracted from small number of trials. Thus, this method can be used to study stretch reflexes in subjects with neuromuscular disorders.
Proceedings of the 2011 American Control Conference, 2011
This paper describes a new algorithm for the identification of single-input single-output Hammers... more This paper describes a new algorithm for the identification of single-input single-output Hammerstein systems using the multivariable output error state space (MOESP) class of subspace identification algorithms. The algorithm consists of three main steps. First, the MOESP algorithm is used to determine the system order and estimate two of the state space model matrices. Second, a least squares problem is solved to minimize the prediction error. Finally, the global search optimization is needed to be used to estimate optimal values for the remaining parameters. Performance of the model was evaluated by simulating a model of ankle joint reflex stiffness, a well known Hammerstein system. The results demonstrate that the algorithm estimated the model parameters very accurately in the presence of additive, output noise.
16th IFAC Symposium on System Identification, 2012
It is not trivial to acquire data under stationary conditions from biomedical systems since they ... more It is not trivial to acquire data under stationary conditions from biomedical systems since they frequently show time-varying and/or switching behaviour. It is often possible to acquire short segments of stationary data and repeat the experiment many times. However, initial conditions contribute substantially to the transient response and must therefore be accounted for explicitly. This paper presents a subspace algorithm for the identification of Hammerstein systems from short segments of data that estimates the initial condition of each segment and the parameters of the nonlinearity, as well as a state-space model for the linear part. A previously developed algorithm suffers from two issues. Firstly, all segments had to be equal lengths, and secondly the algorithm provided an over-parameterized model of the Hammerstein system rather than an individual model for each component of the cascade. We resolved the first issue by introducing a new formulation of the problem and the second one by developing an iterative method to separate the estimated parameters. Simulation results on Hammerstein model of reflex joint stiffness show the algorithm is capable of identifying accurate models even with noisy data. We also show the application of this algorithm on a set of experimental data acquired from one subject.
Proceedings of the 2010 American Control Conference, 2010
ABSTRACT
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014
This paper describes a novel method for the identification of time-varying ankle joint dynamic st... more This paper describes a novel method for the identification of time-varying ankle joint dynamic stiffness during large passive movements. The method estimates a linear parameter varying parallel-cascade (LPV-PC) model of joint stiffness consisting of two pathways: (a) an LPV impulse response function (IRF) for intrinsic mechanics and (b) an LPV Hammerstein cascade with time-varying static nonlinearity and a time-invariant linear dynamics for the reflex pathway. A subspace identification technique is used to estimate a statespace representation of the reflex stiffness dynamics. Then, an orthogonal projection decouples intrinsic from reflex response and subsequently identifies an LPV-IRF model of intrinsic stiffness. Finally, an LPV model of the reflex static nonlinearity is estimated using an iterative, separable least squares method. The LPV method was validated using experimental data from two healthy subjects where the ankle was moved passively by an actuator through its range of m...
2009 IEEE International Conference on Communications, 2009
In this paper, data-rate assignment in IS-856 uplink (reverse link) is studied. The problem is fi... more In this paper, data-rate assignment in IS-856 uplink (reverse link) is studied. The problem is first formulated in an interference model framework, and then a dynamic control strategy is developed for efficient rate assignment. In the first step, the controller is designed for the special case when the number of users in the network is fixed. Then, the minimum time
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2013
This paper describes a state-space representation of the parallel-cascade model of ankle joint st... more This paper describes a state-space representation of the parallel-cascade model of ankle joint stiffness whose parameters are directly related to the underlying dynamics of the system. It then proposes a two step subspace method to identify this model. In the first step, the intrinsic stiffness is estimated using proper orthogonal projections. In the second step, the reflexive pathway is estimated by iterating between estimating its nonlinear and linear components. The identified models can be easily converted to continuous-time for physiological interpretation. Monte-Carlo studies using simulated data which replicate closely the experimental conditions, were used to compare the performance of the new method with the previous parallel-cascade, and subspace methods. The new method is more robust to noise and is guaranteed to converge.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2013
This paper describes a novel method for the identification of Hammerstein systems with time-varyi... more This paper describes a novel method for the identification of Hammerstein systems with time-varying (TV) static nonlinearities and time invariant (TI) linear elements. This paper develops a linear parameter varying (LPV) state-space representation for such systems and presents a subspace identification technique that gives individual estimates of the Hammerstein components. The identification method is validated using simulated data of a TV model of ankle joint reflex stiffness where the threshold and gain of the model change as nonlinear functions of an exogenous signal. Pilot experiment of TV reflex EMG response identification in normal ankle joint during an imposed walking task demonstrate systematic changes in the reflex nonlinearity with the trajectory of joint position.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2011
Reflex stiffness is often modeled as a Hammerstein system comprising a cascade of a static nonlin... more Reflex stiffness is often modeled as a Hammerstein system comprising a cascade of a static nonlinear element and a linear dynamic element. The nonlinearity is frequently modeled as a half wave rectifier so that changes in the reflex response can only be modeled by changes in the parameters of the linear element. This is an oversimplification since there are physiological mechanisms that could change both the threshold of the nonlinearity and the linear dynamics. This study explores the ability of a new subspace identification algorithm to distinguish changes in parameters of the nonlinear element from those of the linear element. Simulation studies demonstrate that the method does so very effectively even in the presence of substantial output noise. Pilot experiments in which the method was applied to stretch reflex EMG data revealed that both the threshold of the nonlinearity and the gain of the linear element change with muscle activation.
GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference, 2009
In this paper, the problem of resource allocation in IS-856 uplink in the presence of time-delay ... more In this paper, the problem of resource allocation in IS-856 uplink in the presence of time-delay is studied. A set of nonlinear adaptive controllers are designed to stabilize the wireless network and use the system resources efficiently. The controllers obtained are then modified properly to retain network stability and performance in the presence of time-delay. Simulation results are presented to show the effectiveness of the proposed approach.
49th IEEE Conference on Decision and Control (CDC), 2010
ABSTRACT
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014
This paper presents a state-space (subspace) method for identification of parallel-cascade joint ... more This paper presents a state-space (subspace) method for identification of parallel-cascade joint stiffness from short segments of data. It provides unbiased estimates of stiffness by accounting for the contributions of initial conditions of each segment. The method is important in situations where it is not possible to acquire a long stationary data due to switching or time-varying behavior. The power of the method was demonstrated by using it to efficiently characterize ankle joint stiffness through the joint's range of motion.
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013
Noise characteristics play an important role in evaluating tools developed to study biomedical sy... more Noise characteristics play an important role in evaluating tools developed to study biomedical systems. Despite usual assumptions, noise in biomedical systems is often nonwhite or non-Gaussian. In this paper, we present a method to analyze the noise component of a biomedical system. We demonstrate the effectiveness of the method in the analysis of noise in voluntary ankle torque measured by a torque transducer and eye movements measured by electro-oculography (EOG).
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013
Dynamic ankle joint stiffness defines the relationship between the position of the ankle and the ... more Dynamic ankle joint stiffness defines the relationship between the position of the ankle and the torque acting about it and can be separated into intrinsic and reflex components.Under stationary conditions, intrinsic stiffness can described by a linear second order system while reflex stiffness is described by Hammerstein system whose input is delayed velocity. Given that reflex and intrinsic torque cannot be measured separately, there has been much interest in the development of system identification techniques to separate them analytically. To date, most methods have been nonparametric and as a result there is no direct link between the estimated parameters and those of the stiffness model. This paper presents a novel algorithm for identification of a discrete-time model of ankle stiffness. Through simulations we show that the algorithm gives unbiased results even in the presence of large, non-white noise. Application of the method to experimental data demonstrates that it produces results consistent with previous findings.
IFAC Proceedings Volumes, 2011
This paper describes an algorithm to identify state-space models for single input single output (... more This paper describes an algorithm to identify state-space models for single input single output (SISO) Hammerstein structures based on input-output measurements. The algorithm consists of two main steps. First, a subspace algorithm is used to determine the system order and estimate the A and C system matrices. Estimation of the other state space matrices as well as the nonlinearity is then formulated as nonlinear optimization problem in which the state space model of the linear component and the coefficients of the basis function expansion of the nonlinear component are distinct. This formulation minimizes the number of parameters to estimate; moreover any one parameter is related to either the linear dynamics or the static nonlinearity. The unknown parameters are then estimated using an iterative procedure that solves a least square problem at each step. Simulation studies using a well known model of ankle joint reflex stiffness demonstrate that the algorithm is accurate and performs well in the non-ideal conditions that prevail during practical experiments.
It is not trivial to acquire data under stationary conditions from biomedical systems since they ... more It is not trivial to acquire data under stationary conditions from biomedical systems since they frequently show time-varying and/or switching behaviour. It is often possible to acquire short segments of stationary data and repeat the experiment many times. However, initial conditions contribute substantially to the transient response and must therefore be accounted for explicitly. This paper presents a subspace algorithm for the identification of Hammerstein systems from short segments of data that estimates the initial condition of each segment and the parameters of the nonlinearity, as well as a state-space model for the linear part. A previously developed algorithm suffers from two issues. Firstly, all segments had to be equal lengths, and secondly the algorithm provided an over-parameterized model of the Hammerstein system rather than an individual model for each component of the cascade. We resolved the first issue by introducing a new formulation of the problem and the second one by developing an iterative method to separate the estimated parameters. Simulation results on Hammerstein model of reflex joint stiffness show the algorithm is capable of identifying accurate models even with noisy data. We also show the application of this algorithm on a set of experimental data acquired from one subject.
Globecom 2009 2009 Ieee Global Telecommunications Conference, Nov 1, 2009
In this paper, the problem of resource allocation in IS-856 uplink in the presence of time-delay ... more In this paper, the problem of resource allocation in IS-856 uplink in the presence of time-delay is studied. A set of nonlinear adaptive controllers are designed to stabilize the wireless network and use the system resources efficiently. The controllers obtained are then modified properly to retain network stability and performance in the presence of time-delay. Simulation results are presented to show the effectiveness of the proposed approach.
Proceedings of the 2009 Ieee International Conference on Communications, Jun 14, 2009
In this paper, data-rate assignment in IS-856 uplink (reverse link) is studied. The problem is fi... more In this paper, data-rate assignment in IS-856 uplink (reverse link) is studied. The problem is first formulated in an interference model framework, and then a dynamic control strategy is developed for efficient rate assignment. In the first step, the controller is designed for the special case when the number of users in the network is fixed. Then, the minimum time
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015
The dynamic relationship between the joint position and reflex EMG in ankle muscles of healthy hu... more The dynamic relationship between the joint position and reflex EMG in ankle muscles of healthy human subjects was studied for time-varying (TV) contractions. A linear parameter varying (LPV) identification algorithm was used to estimate the Hammerstein system relating ankle position to the reflex EMG response. The estimated Hammerstein system comprised a time-invariant (TI) linear element and a TV static nonlinearity that resembled a half-wave rectifier with a threshold and linear gain. The results demonstrated a systematic change in the reflex nonlinearity with the activation level. The gain of TV nonlinearity increased with activation level reaching its peak at 20-30% maximum voluntary contraction and then decreased. The threshold of the nonlinearity decreased with increasing activation level reaching it minimum at the same point where the gain was maximal. Using the LPV-Hammerstein method in this work, the underlying TV dynamics were extracted from small number of trials. Thus, this method can be used to study stretch reflexes in subjects with neuromuscular disorders.
Proceedings of the 2011 American Control Conference, 2011
This paper describes a new algorithm for the identification of single-input single-output Hammers... more This paper describes a new algorithm for the identification of single-input single-output Hammerstein systems using the multivariable output error state space (MOESP) class of subspace identification algorithms. The algorithm consists of three main steps. First, the MOESP algorithm is used to determine the system order and estimate two of the state space model matrices. Second, a least squares problem is solved to minimize the prediction error. Finally, the global search optimization is needed to be used to estimate optimal values for the remaining parameters. Performance of the model was evaluated by simulating a model of ankle joint reflex stiffness, a well known Hammerstein system. The results demonstrate that the algorithm estimated the model parameters very accurately in the presence of additive, output noise.
16th IFAC Symposium on System Identification, 2012
It is not trivial to acquire data under stationary conditions from biomedical systems since they ... more It is not trivial to acquire data under stationary conditions from biomedical systems since they frequently show time-varying and/or switching behaviour. It is often possible to acquire short segments of stationary data and repeat the experiment many times. However, initial conditions contribute substantially to the transient response and must therefore be accounted for explicitly. This paper presents a subspace algorithm for the identification of Hammerstein systems from short segments of data that estimates the initial condition of each segment and the parameters of the nonlinearity, as well as a state-space model for the linear part. A previously developed algorithm suffers from two issues. Firstly, all segments had to be equal lengths, and secondly the algorithm provided an over-parameterized model of the Hammerstein system rather than an individual model for each component of the cascade. We resolved the first issue by introducing a new formulation of the problem and the second one by developing an iterative method to separate the estimated parameters. Simulation results on Hammerstein model of reflex joint stiffness show the algorithm is capable of identifying accurate models even with noisy data. We also show the application of this algorithm on a set of experimental data acquired from one subject.
Proceedings of the 2010 American Control Conference, 2010
ABSTRACT
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014
This paper describes a novel method for the identification of time-varying ankle joint dynamic st... more This paper describes a novel method for the identification of time-varying ankle joint dynamic stiffness during large passive movements. The method estimates a linear parameter varying parallel-cascade (LPV-PC) model of joint stiffness consisting of two pathways: (a) an LPV impulse response function (IRF) for intrinsic mechanics and (b) an LPV Hammerstein cascade with time-varying static nonlinearity and a time-invariant linear dynamics for the reflex pathway. A subspace identification technique is used to estimate a statespace representation of the reflex stiffness dynamics. Then, an orthogonal projection decouples intrinsic from reflex response and subsequently identifies an LPV-IRF model of intrinsic stiffness. Finally, an LPV model of the reflex static nonlinearity is estimated using an iterative, separable least squares method. The LPV method was validated using experimental data from two healthy subjects where the ankle was moved passively by an actuator through its range of m...
2009 IEEE International Conference on Communications, 2009
In this paper, data-rate assignment in IS-856 uplink (reverse link) is studied. The problem is fi... more In this paper, data-rate assignment in IS-856 uplink (reverse link) is studied. The problem is first formulated in an interference model framework, and then a dynamic control strategy is developed for efficient rate assignment. In the first step, the controller is designed for the special case when the number of users in the network is fixed. Then, the minimum time
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2013
This paper describes a state-space representation of the parallel-cascade model of ankle joint st... more This paper describes a state-space representation of the parallel-cascade model of ankle joint stiffness whose parameters are directly related to the underlying dynamics of the system. It then proposes a two step subspace method to identify this model. In the first step, the intrinsic stiffness is estimated using proper orthogonal projections. In the second step, the reflexive pathway is estimated by iterating between estimating its nonlinear and linear components. The identified models can be easily converted to continuous-time for physiological interpretation. Monte-Carlo studies using simulated data which replicate closely the experimental conditions, were used to compare the performance of the new method with the previous parallel-cascade, and subspace methods. The new method is more robust to noise and is guaranteed to converge.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2013
This paper describes a novel method for the identification of Hammerstein systems with time-varyi... more This paper describes a novel method for the identification of Hammerstein systems with time-varying (TV) static nonlinearities and time invariant (TI) linear elements. This paper develops a linear parameter varying (LPV) state-space representation for such systems and presents a subspace identification technique that gives individual estimates of the Hammerstein components. The identification method is validated using simulated data of a TV model of ankle joint reflex stiffness where the threshold and gain of the model change as nonlinear functions of an exogenous signal. Pilot experiment of TV reflex EMG response identification in normal ankle joint during an imposed walking task demonstrate systematic changes in the reflex nonlinearity with the trajectory of joint position.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2011
Reflex stiffness is often modeled as a Hammerstein system comprising a cascade of a static nonlin... more Reflex stiffness is often modeled as a Hammerstein system comprising a cascade of a static nonlinear element and a linear dynamic element. The nonlinearity is frequently modeled as a half wave rectifier so that changes in the reflex response can only be modeled by changes in the parameters of the linear element. This is an oversimplification since there are physiological mechanisms that could change both the threshold of the nonlinearity and the linear dynamics. This study explores the ability of a new subspace identification algorithm to distinguish changes in parameters of the nonlinear element from those of the linear element. Simulation studies demonstrate that the method does so very effectively even in the presence of substantial output noise. Pilot experiments in which the method was applied to stretch reflex EMG data revealed that both the threshold of the nonlinearity and the gain of the linear element change with muscle activation.
GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference, 2009
In this paper, the problem of resource allocation in IS-856 uplink in the presence of time-delay ... more In this paper, the problem of resource allocation in IS-856 uplink in the presence of time-delay is studied. A set of nonlinear adaptive controllers are designed to stabilize the wireless network and use the system resources efficiently. The controllers obtained are then modified properly to retain network stability and performance in the presence of time-delay. Simulation results are presented to show the effectiveness of the proposed approach.
49th IEEE Conference on Decision and Control (CDC), 2010
ABSTRACT
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014
This paper presents a state-space (subspace) method for identification of parallel-cascade joint ... more This paper presents a state-space (subspace) method for identification of parallel-cascade joint stiffness from short segments of data. It provides unbiased estimates of stiffness by accounting for the contributions of initial conditions of each segment. The method is important in situations where it is not possible to acquire a long stationary data due to switching or time-varying behavior. The power of the method was demonstrated by using it to efficiently characterize ankle joint stiffness through the joint's range of motion.
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013
Noise characteristics play an important role in evaluating tools developed to study biomedical sy... more Noise characteristics play an important role in evaluating tools developed to study biomedical systems. Despite usual assumptions, noise in biomedical systems is often nonwhite or non-Gaussian. In this paper, we present a method to analyze the noise component of a biomedical system. We demonstrate the effectiveness of the method in the analysis of noise in voluntary ankle torque measured by a torque transducer and eye movements measured by electro-oculography (EOG).
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013
Dynamic ankle joint stiffness defines the relationship between the position of the ankle and the ... more Dynamic ankle joint stiffness defines the relationship between the position of the ankle and the torque acting about it and can be separated into intrinsic and reflex components.Under stationary conditions, intrinsic stiffness can described by a linear second order system while reflex stiffness is described by Hammerstein system whose input is delayed velocity. Given that reflex and intrinsic torque cannot be measured separately, there has been much interest in the development of system identification techniques to separate them analytically. To date, most methods have been nonparametric and as a result there is no direct link between the estimated parameters and those of the stiffness model. This paper presents a novel algorithm for identification of a discrete-time model of ankle stiffness. Through simulations we show that the algorithm gives unbiased results even in the presence of large, non-white noise. Application of the method to experimental data demonstrates that it produces results consistent with previous findings.