Increase in government spending can lead to increase in production, supply of public goods and services as well as utility. However, it should be noted that increasing the role of government in the economy will cause crowding out of the private sector and this will reduce the utility.The present study is looking for Iran's OPTIMAL growth rate of government's spending using time series data in the years 1978-2014. via a DYNAMIC OPTIMAL CONTROL THEORY approach and the maximum principle.The results show that, the OPTIMAL growth rate of government’s expenditure is 7% and the main factors affecting this rate is the ratio of private and public sector investment. Therefore, the current growth rate of government’s spending is not OPTIMAL and the government needs to CONTROL the growth rate of spending especially current expenditure.

One of the issues of reliable performance in the power grid is the existence of electromechanical oscillations between interconnected generators. The number of generators participating in each electromechanical oscillation mode and the frequency oscillation depends on the structure and function of the power grid. In this paper, to improve the transient nature of the network and damping electromechanical fluctuations, a decentralized robust adaptive CONTROL method based on DYNAMIC programming has been used to design a stabilizing power system and a complementary static var compensator (SVC) CONTROLler. By applying a single line to ground fault in the network, the robustness of the designed CONTROL systems is demonstrated. Also, the simulation results of the method used in this paper are compared with CONTROLlers whose parameters are adjusted using the PSO algorithm. The simulation results show the superiority of the decentralized robust adaptive CONTROL method based on DYNAMIC programming for the stabilizing design of the power system and the complementary SVC CONTROLler. The performance of the CONTROL method is tested using the IEEE 16-machine, 68-bus, 5-area is verified with time domain simulation.

A common method for CONTROLling a group of parallel converters in decentralized CONTROL strategy structure in an island microgrid, the use is the droop-down characteristics of frequency ω-P and voltage E-Q. However, the problem with using this method is that the reactive power is not properly distributed (in proportion to the capacity of the micronutrients) between the micronutrients, which may lead to overload in the converters. Microgrids may also suffer from DYNAMIC stability problems such as power fluctuations, which can be increased by switching between active and reactive power CONTROL. To avoid this problem, the X / R ratio of transmission lines is an important parameter that should be carefully considered in the design of micronutrient CONTROLlers. By linearizing and simplifying conditions, the CONTROL system conversion function model becomes a single input-single output system, which is efficient enough to show the relationship between CONTROL parameters such as slope of droop characteristics and derivative sentences, virtual impedance, and voltage CONTROLlers. Using this model, stability conditions for different parameters are analyzed. Also, to improve power distribution stability, common droop strategies are modified by adjusting the slope as well as adding nonlinear sentence sections. This approach reduces the coupling between active and reactive power CONTROL and reduces the dependence of power distribution on grid parameters such as the X / R ratio. To evaluate the reliability of the proposed model, the simulation results in a sample island microgrid in MATLAB software are presented.

The purpose of the present paper is to prove the model-free OPTIMAL CONTROL THEORY. This THEORY is derived from the principles of DYNAMIC programming and it is produced for discrete-time systems. The design of the CONTROLler depends merely on the I/O data of the CONTROLled planet; hence, the CONTROLler is independent of the model. In this paper, two actions have been performed in order to measure the value of the CONTROLler. In the first step, the CONTROL method was designed to CONTROL the attitude of spacecraft. The purpose of this THEORY was to create a model-free OPTIMAL CONTROL for the spatial model and to measure the efficiency of the spacecraft systems. Secondly, designing linear quadratic regulator (LQR) CONTROLler for attitude CONTROL of spacecraft was carried out. The reason for designing this CONTROLler was to compare it with model-free OPTIMAL CONTROL. If the differences between two CONTROLlers was proved to be small, then the THEORY would be proven. Finally, it has been concluded that CONTROLler is valuable and acceptable.

The main goal of this study is to provide a model for OPTIMAL allocation of provincial budget resources with attention to provinces priorities and with the aim of financial and county spatial decentralization and also social welfare maximization. For this purpose, we design an OPTIMAL CONTROL problem and then, we calculate long run equilibrium of this model with focusing of macroeconomic indicators include the mortality rate, unemployment rate, GINI coefficient, literacy rate, economic participation rate, the province proportion of domestic production and the province proportion of industrial, services and agricultural value added and weighted index of educational and health facilities. Also the short run DYNAMICs of OPTIMAL solution has analyzed. Based on the results and according to the long run equilibrium of the OPTIMAL CONTROL model, if budget planer gives equal importance to these indicators, the higher budgets proportion will allocate to less developed provinces that it is contradict to current method of provincial budgeting in Iran. The results also show that any change in budget planner priority change long run equilibrium of the OPTIMAL CONTROL problem and composition of OPTIMAL provincial budget allocation.

OPTIMAL path planning with OPTIMAL journey time and the motor saturation limit are two main challenges in mobile industrial robot design. The motion speed and motor saturation limit are important factors determining the required torque. Calculating the OPTIMAL torque value reduces the construction and motor selection costs. This paper proposes the THEORY of OPTIMAL CONTROL open-loop base model for path planning by simultaneously minimizing the journey time, wheels’,torque for industrial robots. In this study, nonlinear equations of robot motion were considered as a constraint in OPTIMAL CONTROL problems. Next, the cost function was proposed, including the torque of the left and right wheels and time-related terminal conditions and disturbance, in which the nonlinear equations of the industrial robot motion are assumed as constraints. The final equations were numerically solved, and the effectiveness of the proposed method was demonstrated by simulating and path design for industrial robots' motions along with considering motor saturation limit.

A lot of researches have been focused on the CONTROL design of systems regarding to time OPTIMAL moving of end effectors between two points in Cartesian space. Also a number of researchers have tried to solve the time invariant problem of CONTROL systems. A few works were done for time varying systems. For 2D gantry crane systems, the equations of motion and state space equations were obtained. Switching times have been calculated for such crane by means of phase plane analysis and algorithm genetic. The best input for system is Bang-Bang input and phase plane analysis here uses an open loop method.If the length of cable does not vary during the motion, the switching times were obtained, by the results of Genetic Algorithm method and have been verified by the phase plane method. It is shown that the Algorithm Genetic method is a useful method for obtaining switching times. If the length of cable varies during the motion, the oscillation of a cable in the end of the motion were justified and CONTROLled by means of Fuzzy CONTROL method. The rule-based method has been used for adjusting the fuzzy CONTROLler.

In this paper we have utilized optimum CONTROL procedures to derive an optimum monetary rule for Iran's economy; assuming the policy makers are using the interest rate as a policy variable. In doing so a DYNAMIC stochastic model with rational expectation was setup. The model is calibrated with the use of previous findings in the literature. The results show that the optimum reacrion of the policy makers should be to raise the interest rate in the event of increase in inflation and output and to lower in response to technological shock. The policy makers should also aggressively increase interest rate to an increase in money supply. The interesting point is that the optimum policy requires reaction of the interest rate to the asset prices under different senarious.

Active magnetic bearings (AMBs) are relatively new members in bearings family. Against other bearings which support loads by forces produced by fluid film pressure or physical contact, AMBs support loads by magnetic fields without any contact with the shaft and make it to be levitated. Because of that feature, AMBs have lots of benefits in comparison with other bearings. This paper presents modelling of AMBs with one and two degrees of freedom and the necessary parameters and equations for CONTROL of them is driven. Then, a numerical method based on orthogonal functions called Direct Method for OPTIMAL CONTROL in AMBs is presented with or without inequality constraints. The approach consists of reducing the OPTIMAL CONTROL problem with a two-boundary-value differential equation to a set of algebraic equations by approximating the state and CONTROL variables. This approximation uses orthogonal functions with unknown coefficients. In addition, the inequality constraints are converted to equal constraints. The problems are solved using Legendre and Haar bases. Simulation results demonstrate the benefits of Legendre functions method in compared with those using Haar bases.

This paper presents robust OPTIMAL CONTROL of an uncertain nonlinear switched system with forced subsystems. The uncertainties include external disturbance and parametric uncertainties. Switching signal and CONTROL input are designed to minimize a given cost function. Approximate DYNAMIC programming (ADP) has been efficiently applied to certain switched systems as an OPTIMAL CONTROL strategy. Since approximate DYNAMIC programming method is model based, there would seem to be some difficulties to apply approximate DYNAMIC programming to uncertain switched system. To overcome these mentioned problems, this paper presents an appropriate model. In order to apply proposed CONTROL approach, robust time-delay CONTROLler is added with ADP CONTROL. At first uncertainties are compensated by robust time-delay CONTROLler. Then the switching signal and the CONTROL input are design by approximate DYNAMIC programming that provides a feedback solution for unspecified initial conditions. The discussing boundedness of states and simulation results verify the effectiveness of the proposed CONTROL approach.