Vahid R. Dehkordi

A Channel Differential EZW Coding Scheme for EEG Data Compression

In this paper, a method is proposed to compress multi-channel electroencephalographic (EEG) signals in a scalable fashion. Correlation between EEG channels is exploited through clustering using a k-means method. Representative channels for each of the clusters are encoded individually while other channels are encoded differentially, i.e., with respect to their respective cluster representatives. The compression is performed using the embedded zero-tree wavelet encoding adapted to 1-D signals. Simulations show that the scalable features of the scheme lead to a flexible quality/rate tradeoff, without requiring detailed EEG signal modeling.

Robust controller order reduction

In this paper a method is proposed to reduce the order of a multi-input multi-output robust controller. The controller ensures system robust performance and reducing its order may result in loss of robust performance. A lower bound on the controller order is provided using balanced truncation technique which guarantees that the robust performance of the closed-loop system is maintained. Simulation results show the effectiveness of the proposed technique.

Frequency-domain robust performance condition for controller uncertainty in SISO LTI systems: a geometric approach

This paper deals with the robust performance problem of a linear time-invariant control systemin the presence of robust controller uncertainty. Assuming that plant uncertainty ismodeled as an additive perturbation, a geometrical approach is followed in order to find a necessary and sufficient condition for robust performance in the form of a bound on themagnitude of controller uncertainty. This frequency domain bound is derived by converting the problem into an optimization problem, whose solution is shown to be more time-efficient than a conventional structured singular value calculation. The bound on controller uncertainty can be used in controller order reduction and implementation problems.

Piece-wise linear DFT interpolation for IIR systems: Performance and error bound computation

In this paper, a method is proposed in order to provide an upper bound on the error obtained by approximating a discrete-time system by a finite impulse response, in case of having no a-priori information about the original system other than given frequency response samples. The method uses a first-order frequency-domain approximation for the reconstruction of inter-sample frequency response, leading to fast upper bound calculation. The bound gives useful information about the error magnitude in applications where system blocks are implemented using fast Fourier transform techniques, specially in robust control systems.

A computationally efficient algorithm for order-reduction of IIR filters using control techniques

In this paper, an algorithm is presented for reducing the order of a single-input single-output (SISO) linear time-invariant (LTI) infinite impulse response (IIR) digital filter. The algorithm uses balanced realization method which is widely used in control systems, in order to find a reduced-order approximate model and an estimate of the error bound. The process consists of an HR-to-FIR conversion step which speeds up the algorithm and makes the subsequent calculations easier. This method can be applied to any high-order digital filter used in communication and digital signal processing

Robust SISO controller order reduction

In this paper a method is proposed to reduce the order of a single-input single-output robust controller. The controller ensures system robust performance and reducing its order may result in loss of robust performance. A lower bound on the controller order is provided using balanced truncation technique which guarantees that the robust performance of the closed-loop system is maintained. Simulation results show the effectiveness of the proposed technique.

Frequency-domain robust performance condition for plant and controller uncertainty in SISO LTI systems

This paper addresses the robust performance issue in the presence of controller uncertainty for single-input single-output LTI systems. All system uncertainties are modeled as additive, and the final result is a frequency-domain upper bound for controller uncertainty weighting function which acts as a sufficient condition for maintaining the systempsilas robust performance. The bound is calculated in a simple way which makes it suitable for real-time applications needing multiple controller design attempts due to changes in system components or environmental conditions.

A Model Reduction Technique for IIR Filters using Balanced Realization

In this paper, a method is proposed to reduce the order of a single-input single-output (SISO) infinite impulse response (IIR) digital filter. Since unlike IIR filters an analytical solution exists for the order reduction of FIR systems, the polynomials in the numerator and denominator of the IIR filter are regarded as FIR systems. The balanced realization technique is then applied to each polynomial separately to obtain the reduced order model. An upper bound is provided for the infinity norm of the order reduction error and conditions under which the proposed technique results in a small approximation are also discussed. Simulation results demonstrate the efficacy of the technique.

Design of an H ∞ controller for energy storage in a wind-diesel system

Energy storage systems (ESS) have the potential to improve the utilization of wind energy in wind-diesel power systems by reducing the frequency of dump load. However, an ESS controller must, together with the diesel plant control meet the power system constraints while respecting the limits of the ESS. This paper proposes an H controller as an on-line controller for the system. The problem formulation is presented, followed by design of the controller and simulation results. The results show that the controller performs as designed and provides the basis for future work in the area.

Digital Filter Order Reduction

In this paper, a method is proposed to reduce the order of IIR filters by means of control theory. Using the state space representation of the filter and the controllability and observability gramians of a FIR filter in a closed form, balanced realization method is used to reduce the order of the filter. For IIR filters, long division is used first to find a FIR model for the filter. The balanced realization technique is then utilized to find the reduced order model for the resultant FIR model used to approximate the IIR filter. The reduced-order model obtained for IIR filter consists of the approximation errors in both balanced realization procedure, as well as the long division process. A method is given to obtain an upper bound for the infinity norm of error between the original IIR filter and the FIR model derived from the long division. A bound on the norm of the overall approximation error is then obtained by adding the long division error to the model reduction error of balanced realization.