Komeil Nosrati

• Doctor of Engineering
• PostDoc Position at Tallinn University of Technology

In the development of linear quadratic regulator (LQR) algorithms, the Riccati equation approach offers two important characteristics —it is recursive and readily meets the existence condition. However, these attributes are applicable only to transformed singular systems, and the efficiency of the regulator may be undermined if constraints are viol...

Smart control techniques have been implemented to address fluctuating power levels within isolated microgrids, mitigating the risk of unstable frequencies and the potential degradation of power supply quality. However, a challenge lies in the fact that employing these computationally complex methods without stability preservation might not suffice...

While model predictive control (MPC) is widely used in the process industry for its ability to handle constraints and address complex dynamics, its conventional formulations often encounter challenges when dealing with descriptor systems. These formulations rely on system transformations that are applicable only to regular systems in specific scena...

In this article, the state estimation problem of linear fractional order singular (FOS) systems subject to matrix uncertainties is investigated where a recursive robust algorithm is derived. Considering an uncertain discrete-time linear FOS system with added process and measurement noises, we aim to design a robust Kalman-type state estimation algo...

Variable output power in isolated microgrids (MGs) threatens frequency stability and may even degrade power quality. In response, intelligent control methods have been developed and applied to frequency deviation control systems with excellent results. Nevertheless, a potential problem is that the application of such advanced techniques with a larg...

Developing accurate mathematical models for mi-crogrid (MG) components is the initial step before implementing various load frequency control (LFC) strategies and analysis. In this regard, different high-order models associated with different nonlinearities have been included to increase the modeling accuracy resulted in a performance improvement i...

Reduction in system inertia and maintaining the frequency at the nominal value is a staple of today's and future power systems since their operation, stability, and resiliency are degraded by frequency oscillation and cascading failures. Consequently, designing a stable, scalable, and robust virtual inertia control system is highly relevant to skil...

Inertia droop characteristics in some areas of the interconnected microgrids may jeopardize frequency stability and trigger the problem of grid frequency mismatch, as result reduce the efficient utilization of energy resources. Advanced and multi scale virtual inertia control methods have been developed and applied to these multi-area systems. Notw...

Numerous remote area applications welcome stand-alone renewable energy power generation systems or isolated microgrids (MGs). Due to the nature of solar and wind energy, the frequency deviation control (FDC) in hybrid MGs has become more complicated and critical than the conventional grid for power quality purposes. By using a coordination control...

Developing accurate and optimum state estimation methods for fractional order systems is highly relevant since it provides vital information related to memory effects. The optimum estimation of these systems can be guaranteed using the Kalman filter (KF) when all parameter matrices are not subject to uncertainties. Nevertheless, this fundamental pr...

Effective and accurate state estimation is a staple of modern modeling. On the other hand, nonlinear fractional-order singular (FOS) systems are an attractive modeling tool as well since they can provide accurate descriptions of systems with complex dynamics. Consequently, developing accurate state estimation methods for such systems is highly rele...

Using the non-causal nature of a fractional-order singular (FOS) model, this paper deals with the modification of an estimation algorithm developed in [1] and demonstrates how the derived estimation procedure can be adjusted by additional information related to the future dynamics. The procedure adopts the maximum likelihood (ML) method leading to...

In our recent paper [1], we have developed a simple algorithm for the state estimation of discrete-time linear stochastic fractional-order singular (FOS) systems based on the deterministic least squares method. In this paper, we shall consider the asymptotic properties of the obtained generalized Riccati equation and the associated state estimator....

In this chapter, singular system theory and fractional calculus are utilized to model the biological systems in the real world, some fractional-order singular (FOS) biological systems are established, and some qualitative analyses of proposed models are performed. Through the fractional calculus and economic theory, a new and more realistic model o...

This study considers the optimal linear estimation problem for the discrete-time stochastic fractional-order system in its more general formulation. The system is allowed to be in singular form, rectangular, with dynamical and measurement noises correlated. First, some new conditions for the solvability, regularity and causality to discrete-time li...

In this paper, a fractional-order singular (FOS) predator–prey model with Holling type-II functional response has been introduced, and the mathematical behavior of the model from the aspect of local stability is investigated. Through the fractional calculus and economic theory, a new and more realistic predator–prey model has been extended, and the...

In this paper, a chaotic communication method based on the Cubature Kalman Filter (CKF) is presented. Using CKF, state estimation of a chaotic dynamical system and synchronization, in the presence of processing noise and measurement noise, are presented. The proposed method is then applied to a private secure communication setup, and an image encry...

This paper presents a novel chaotic communication method using an Unscented Kalman Filter (UKF). Applying UKF, the method proposes the estimation of the state variables of the chaotic dynamical system and synchronization. The proposed method is then applied to new private secure communication. The chaotic synchronization is implemented by the UKF i...

In this paper we present chaotic synchronization of a Lorenz system using Unscented Kalman Filter (UKF). The UKF has shown to produce better results, than Extended Kalman Filter (EKF), without performing potentially ill-conditioned numerical calculations and linearly approximating the evolution of the state vector covariance. The chaotic synchroniz...

In this paper we numerically investigate the chaotic behaviours of the fractional-order Lorenz system and its synchronization. For the first time, a fractional chaotic synchronization using an Unscented Kalman Filter (UKF) is presented. The chaotic synchronization is implemented by the UKF design in the presence of process noise and measurement noi...

Extended Kalman Filter (EKF) has been widely used as an important tool in practical applications to estimate states of nonlinear systems. There are a number of deficiencies in EKF such as biased estimation, complexity in calculation and inefficacity in not being able to compute analytical derivatives affect its application in many fields. In this p...

Since we are not able to replace the battery in a wireless sensor network, energy and lifetime are the most important parameters. Common sensors are not able to connect directly with the central station due to their limited ranges in asymmetrical wireless networks, therefore, we utilize super nodes. A super node has more energy, processing power an...

Energy and lifetime are the most important design objectives in many wireless sensor network applications. In asymmetrical sensor networks, different sensors with various abilities are used. It is crucial to select the parameters of fit function and monitoring sensors optimally in a point coverage network. In this paper, our approach uses genetic a...