Sharif Digital Repository

In this paper, an attractive and novel algorithm for improving irreducible model identification of continuous time(CT) MIMO systems has been presented. The algorithm is based on least - squares (LS) estimates of Markov parameters (MP) using input output data and residual whitening. By choosing a linear-in-parameters model structure, the estimation becomes linear and asymptotically robust to zero-mean additive disturbances. CT Markov parameters may result in diverging approximations even for stable systems. To remove the existing limitations in the case of systems with low or zero damping, Markov Poisson parameters have been used to lend much flexibility to the estimation model. The MIMO... 

System Identification is a key technology for the development and integration of modern engineering systems including unconventional flying vehicles. These systems are highly parametric with complex dynamics and nonlinearities. Ducted fans are special class of these vehicles that can take off vertically, hover and cruise at very low speed. In this paper, an exact equivalent linear system is found from the non-linear dynamic model of a ducted fan by use of frequency response identification. Here, power spectral density analysis is performed, using CIFER software, to evaluate the input-output responses in hover and to derive the transfer functions based on the coherence criterion. Then,... 

In this paper, an extended dynamic model of peripheral milling process including process damping, structural and cutting force nonlinearities is presented. Cutting forces are described through a third-order polynomial function of chip thickness while a cubic nonlinear function is considered for the structural stiffness. Under stable and regenerative chatter conditions and using Fourier series components, closed form expressions for the nonlinear cutting forces are derived. Parameters of the proposed model are identified through a set of experiments. For this purpose, modal experiments and measurement of cutting forces (at various feed rates) are performed to determine the modal parameters... 

In this paper, a novel generalized predictive control (GPC) strategy using multiple models approach has been presented. The proposed strategy is realized based on the Takagi-Sugeno-Kang (TSK) fuzzy-based modeling for control of a tubular heat exchanger system. In this strategy, different operating environments of the system with varying parameters are first identified. Then for each environment, a linear model and its corresponding fuzzy predictive controller are designed. For demonstrating the effectiveness of the proposed approach, simulations are done and the results are compared with those obtained using the single model predictive control approach. The results can verify the validity of... 

Purpose: The purpose of this paper is to analyze the stability of aeroelastic systems using a novel reduced order aeroelastic model. Design/methodology/approach: The proposed aeroelastic model is a reduced-order model constructed based on the aerodynamic model identification using the generalized aerodynamic force response and the unsteady boundary element method in various excitation frequency values. Due to the low computational cost and acceptable accuracy of the boundary element method, this method is selected to determine the unsteady time response of the aerodynamic model. Regarding the structural model, the elastic mode shapes of the shell are used. Findings: Three case studies are... 

As wind energy is becoming one of the fastest-growing renewable energy resources, controlling large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties. The main goal of the current work is to propose an intelligent control of the wind turbine system without the need for model identification. For this purpose, a novel model-independent nonsingular terminal sliding-mode control (MINTSMC) using the basic principles of the ultra-local model (ULM) and combined with the single input interval type-2 fuzzy logic control (SIT2-FLC) is developed for non-linear wind turbine pitch angle control. In the suggested control framework, the... 

As wind energy is becoming one of the fastest-growing renewable energy resources, controlling large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties. The main goal of the current work is to propose an intelligent control of the wind turbine system without the need for model identification. For this purpose, a novel model-independent nonsingular terminal sliding-mode control (MINTSMC) using the basic principles of the ultra-local model (ULM) and combined with the single input interval type-2 fuzzy logic control (SIT2-FLC) is developed for non-linear wind turbine pitch angle control. In the suggested control framework, the... 

Purpose: The purpose of this paper is to analyze the stability of aeroelastic systems using a novel reduced order aeroelastic model. Design/methodology/approach: The proposed aeroelastic model is a reduced-order model constructed based on the aerodynamic model identification using the generalized aerodynamic force response and the unsteady boundary element method in various excitation frequency values. Due to the low computational cost and acceptable accuracy of the boundary element method, this method is selected to determine the unsteady time response of the aerodynamic model. Regarding the structural model, the elastic mode shapes of the shell are used. Findings: Three case studies are... 

System Identification is a key technology for the development and integration of modern engineering systems including gas turbines. These systems are highly parametric with complex dynamics and nonlinearities. Small turbojet engines are special class of gas turbines that are suitable for scientific purposes and researches in the area of stability, performance, simulation and fuel control design. The motivation behind the presented study is to improve the speed, quality and cost of engine testing and to gain insight into alternatives to traditional identification methods for gas turbines. It discusses the identification of small turbojet engine dynamics by validating the thermodynamic model... 

In some systems with hysteresis behavior like Shape Memory Alloy (SMA) actuators and Piezo actuators, we essentially need an accurate modeling of hysteresis either for controller design or performance evaluation. One of the most interesting Hysteresis non-linearity identification methods is Preisach model in which hysteresis is modeled by linear combination of elemental operators. Despite good ability of Preisach modeling to extract main features of system with hysteresis behavior, cause of tough numerical nature of Preisach, it is not convenient to use in real-time control applications. In this paper we present a novel method based on Artificial Neural Network. For evaluation of proposed... 

Renovation and retrofit of gas turbine control systems yield significant economic savings, enhanced reliability, and improved performance. In recent years, the gas turbine industry is increasingly facing the need to well-established procedures for the acceptance tests of renovated control systems. This paper proposes a unified framework to evaluate the performance of renovated gas turbine control systems. Under a set of assumptions on the ambient and fuel conditions, a low-complexity modular model is presented and identified using optimization-oriented identification techniques. The accuracy of the proposed model is validated through experimental studies in full-load, min-load, and no-load... 

Renovation and retrofit of gas turbine control systems yield significant economic savings, enhanced reliability, and improved performance. In recent years, the gas turbine industry is increasingly facing the need to well-established procedures for the acceptance tests of renovated control systems. This paper proposes a unified framework to evaluate the performance of renovated gas turbine control systems. Under a set of assumptions on the ambient and fuel conditions, a low-complexity modular model is presented and identified using optimization-oriented identification techniques. The accuracy of the proposed model is validated through experimental studies in full-load, min-load, and no-load... 

In today's world, control and navigation of autonomous underwater vehicles (AUVs) are quite challenging issues. In these fields, obtaining an identified dynamic model of AUV is a vital part. In this paper, a method for parameter estimation of an AUV planar model is proposed, which uses augmented state space technique and Square Root Transformed Unscented Kalman Filter (SR-TUKF) as an estimator. Furthermore, by modeling, misalignment between Inertial Measurement Unit (IMU) and Doppler Velocity Log (DVL) is estimated, simultaneously. Parameter identification is conducted using data of an AUV, equipped with Gyroscope, DVL and Encoder for measuring control inputs, in a planar maneuver. According...