Magnetic levitation systems (Maglev) are widely used in various industries. Open loop Maglev system is highly nonlinear and unstable. Therefore, designing a simple, but effective controller for such a system is a challenging problem. In this paper, a fractional order Predictive Functional Controller (FPFC) is proposed for control of Magnetic Levitation system based on its linearized unstable model. At first, the unstable plant is decomposed into two stable models. Then, using these two stable models and employing fractional order cost function, the PFC controller is designed. Because of more degrees of freedom and its flexibility of fractional order calculus, the proposed fractional PFC would improve the performance of closed loop system, noticeably. Robust stability of closed-loop system has been also studied considering the uncertainties and model mismatches via small gain theorem. Simulation results show good performance of the proposed controller in nominal and perturbed conditions. Based on provided simulations, via the proposed controller, overshoot has been omitted and performance indices have been improved more than 50% with respect to first and second order of freedom integer/fractional order PID controllers, designed for this system, in the literature.

In this paper, vibration control of a cracked, functoinally graded, uncertain beam allocated in a thermal environment has been investigated. For this purpose, piezoelectric patches are used as sensors to measure the displacement of the beam and also as actuators to apply control forces. In this way, firstly, partial differential equation governing the dynamics of the system is derived by considering the Euler-Bernoulli assumption using Lagrange method. Approximate solution of eigenvalue equation is achieved using Rayleigh–Ritz method. After that, time dependent ordinary differential equations is obtained using Galerkin projection scheme and then represented in the state-space form. Based on this model, a robust observer based output feedback controller is designed for this continuous-time model. In this regard, controller and observer gains are designed by a Lyapunov-based method. This procedure is done by solving a set on linear matrix inequalities. Simulation studies show the effectiveness of the proposed method.

In this paper, control of forced vibration amplitude of a rotating FGM conical shell is studied using FGPM patches. Four piezoelectric patches are placed inner and outer of the shell. In order to obtain the system dynamic equations, the energy method and the classical plate theory are used and simply supported boundary conditions are considered. Each system variable is considered as an expression by separation of variables with variable-time coefficients. Subsequently by substitution the considered responses in the energy functions and finally using the Lagrange equation, the governing equations of the system are obtained. Natural frequencies are compared with the result of previous researches in the case of non-rotating and rotating shell. Also to control vibration, velocity feedback is used so that sensor voltage, which is dependent on the surface, thickness, and location of each sensor, is calculated and used in the actuator voltage. In the following section, control of the system is done for first mode and then convergent system, which in both cases, Closed-loop system well dampens amplitude of forced vibrations.

A new methodology based on a functional link net (FLN) artificial neural network (ANN) is introduced for excitation control of a synchronous generator based on fuzzy power system stabilizer (FPSS). This method combines the advantages of the fuzzy controller along with the independence from model identification and fast processing ANN and proposes a new form of excitation controller for a synchronous generator. Delta-rule is used for training of ANN. ANN is trained for different load patterns which are produced by FPSS, and is continued until the total error was smaller than certain value. The analysis of a three-phase short circuit fault condition under various loading conditions of a single machine infinite bus system is presented to illustrate the application of the developed methodology. The obtained results show that the proposed FLN artificial neural network, based on fuzzy controller for power system stabilizer (PSS), can provide very good damping characteristic through wide rang of operating conditions for power system and it has smoother control for system variables; hence it improves dynamic operating of the system considerably.

In this paper, robust vibration control of a thin functionally graded beam with a variable cross-section has been investigated. For this purpose, piezoelectric patches are used as sensors to measure the displacement of the beam and as actuators to apply control forces. In this way, firstly, Euler-Bernoulli theory is used to derive the governing dynamical partial differential equation, through the Hamilton’s principle. Approximate solution of these equations is achieved using finite difference method, and the proper orthogonal decomposition is then used to obtain vibration mode shapes. After that, time-dependent ordinary differential equations are attained using Galerkin projection scheme and then represented in the statespace form. Since the data measurement is done in sampling intervals, the system is considered as sampleddata. In this way, direct digital control design methodology is used. For this purpose, based on its zero-order hold equivalent model, a robust discrete-time, observer-based, output feedback controller is designed. In this regard, controller and observer gains are designed by a Lyapunov-based method. This procedure is done by solving a set of linear matrix inequalities. Simulation studies show the effectiveness of the proposed method.

The purpose of this study is to analyze oil and tax revenues in the Iranian economy. Applying the stochastic dynamic general equilibrium approach, a model for the oil exporting economy was simulated. In order to recover the tax system, oil and tax revenues added to the model as a part of government’s revenue. The present study applies Dynare software with Matlab to estimate the model’s parameters by Bayesian statistical techniques based on Monte Carlo method with Markov chain in the form of Metropolis-Hastings algorithm. The period of study is from 1368 to 1396 in a quarterly setting. In order to analyze the shocks, two scenarios were designed. In the first scenario, it was assumed that the government has oil revenues and all oil revenues are spent by the government so that the government does not rely on tax revenues. In the second scenario, it is assumed that 40% of the government's oil revenues are injected into the Development Fund and a percentage of it, is allocated to facilitate the production sector, and the government mostly relies on the taxes. The results show that the tax and oil shock by reducing dependence on oil and reliance on tax revenues, has negative impact on macroeconomic variables in the short term, but in the long run, with increasing tax revenues, production and, consequently, investment, consumption, employment has increased. JEL classification: H21 C13، E17، G5

Identification and analysis of geographic and climatic conditions for scientific researches and strategic studies is one of the main issues in countries. Nowadays, the use of Unmanned Aerial Vehicle because of its safety and high performance has been widely used in many countries. Exact action of this system leads to obtain accurate data and thereby achieve critical information. Therefore, an appropriate control system and perfect control of the drone is important. In this paper, an intelligent control using Fuzzy- Genetic Algorithm is presented on longitudinal flight dynamics of an Unmanned Aerial Vehicle. In this approach, all the membership functions and fuzzy rules are extracted from genetic algorithm method to minimize the over shoot and the steady-state error of the system. Finally, an example is illustrated to compare the proposed method with the classical PID controller.

In the investigation, the vibrations of a rotating functionally graded cylindrical shell under axial and internal pressure with ring and stringer stiffened and simply supported boundary condition based on Love's shell theory is studied. The cylindrical shell with ring and stringer stiffened widely used in structures such as rockets, submarines and fuel tank of aircraft. The material properties of the rotating functionally graded (FG) cylindrical shell vary continuously across the thickness according to the power law distribution. In this study considers functionally graded material composed of Nickel and stainless steel, in which FG cylindrical shell has Nickel on its inner surface and stainless steel on its outer surface. The governing equations of a cylindrical shell are derived using Hamilton's principle and energy method and the effect of various parameters such as angular speed, ring and stringer stiffened, axial load, internal pressure and the functionally graded material are investigated. The validity of the results by comparing them with the results of previous research is investigated, in which there is a very good agreement between the results of the present work and previous studies.

Control of transmitted active power is an important issue in operation and management of power systems especially in congestion or fault conditions. In these situations, Thyristor Controlled Series Capacitor (TCSC) is used to continuous control and increase the transmitted power due to these facts that TCSC can act dynamically and is able to stable the system during fault conditions. In this paper, the transmitted power is controlled in the ten megawatt span by using the TCSC. For this purpose, various controllers such as PID, fuzzy and Adaptive Network-based Fuzzy Interface System (ANFIS) are designed to continuous control of the transmitted power. Simulation results evaluate advantages and disadvantages these controllers. ANFIS controller is designed by open loop method which has a good transient response. However, it has a large steady state error and is very sensitive to the variations in system. Fuzzy and ANFIS controllers are combined to remove these defects. The simulation results verify the advantages of the fuzzy-ANFIS controller with respect to the other designed controllers.