Journal of Control
Year:2011 | Volume:5 | Issue:3|Papers Count:9

current inertial navigation systems usually use liner accelerometer and gyroscopes to sense linear accelerations and angular velocity, respectively. The gyroscopes have the disadvantage such as: complicated manufacture technique, high cost, and large volume and so on. Due to these factors the small accelerometers with low cost to replace the gyroscopes in some inertial navigation systems.In this paper a ten-accelerometer configuration is proposed which can determine linear acceleration an angular velocity completely. The advantages of this method in comparison with previous works are the simplicity of the equations and elimination of direct integration of angular acceleration.Actual accelerometers have errors such as bias and misalignment which have significant effect on precision of inertial navigation systems. So, these errors and their effect on navigation are considered in modelling and simulation. The obtained results of simulation show that this method has suitable precision in short time navigation systems.

In this paper a new method to design dynamical decoupler is presented. This method is based on drawing the frequency characteristic of decoupler and its estimation by using of a proper, stable and causal transfer function in a determined frequency range. Then has been discussed about the relationship between design decoupler and controller and its role in reducing the interactions of loops. Finally the sequential loop closing method with relay test and PID controllers is combined with the proposed decoupler design method. Successful results of this method in decoupling the multivariable system is shown with simulation.

In this paper, we compare the performance of state vector fusion methods for data fusion of multi sensors networks by comparing the estimation errors covariance. Here, we represent the three main state vector data fusion methods and we prove the equivalency of the estimation error covariance matrices corresponding to these three methods. In last part of the paper, the simulation results are presented to show the effectiveness of the theoretical results. Also, we analyze the computational load of these three methods by simulation analysis.

In this paper, a two point guidance law for homing interceptors using finite time second order sliding mode control and based on parallel navigation is proposed. In the proposed guidance law, sliding surface is selected as the line of sight rate and the target maneuvers are considered as an uncertainty which only needs the upper bound of these maneuvers. Furthermore, the proposed algorithm can guarantee the finite time convergence of the LOS rate to zero or a small neighborhood of zero. Therefore, the performance and stability of guidance loop against maneuvering targets are increased.

Damping of low-frequency electro-mechanical oscillation is very important for the system secure operation. The fast acting, FACTS device which is capable of improving both steady state and dynamic performance permit newer opproaches to system stabilization. In this paper, presents a novel approach for designing of damping controller for STATCOM in order to enhance the damping of power system low frequency oscillations (LFO). Based on Phillips-heffron model linearization, problem of damping controller design considered as an optimizing problem of multi purpose with criterion function and it is solved with utilizing honey bee mating optimization algotithm. To validate the accuracy of results a comparison with GA has been made. This controller is designed in order to transmit unstable electromechanical modes to specific area of complex plane. The proposed controller performance is confirmed by analysis of eigenvalue and nonlinear timedomain simulation under various disturbances with both control parameter of STATCOM (capacitor voltage control and terminal voltage control). Simulation results illustrate that design of controller based of capacitor voltage control in comparison with terminal voltage control has better low frequency oscillation damping and it increases dynamical stability of power system.

In this paper, the problem of trajectory planning for a high speed planing boat with the aim of time optimization under nonlinear equality and inequality constraints is addressed. First, a nonlinear mathematical model of the craft dynamic and then the Hamiltonian boundary value problem (HBVP) equations are derived. The problem is solved using nolinear programming by discretizing the control time history and adjoining the constraints to the cost function via Linear Extended Penalty Function (LEPF) method. The Steepest Descent (SD) approach is used to solve this nonlinear programming. Some examples of boat minimum time maneuver are presented to demonstrate the effectiveness of the approach for designing optimal maneuvers.

In most industrial applications, attaining minimum output variance certifies the efficiency of system and results in increasing productivity and decreasing energy consuming. Therefore, minimum variance index is considered as one of the main subjects in control engineering field. A minimum variance controller is an optimal controller that provides (theoretically) the minimum possible variance. Designing this controller, however, requires exact models of both the system and disturbance. Due to existence of interactions among loops, modeling MIMO systems is often complicated. Existence of disturbance is another reason for this complication. In this paper, in order to avoid the need for an analytical model of system, VARX model has been used to simultaneous identification of the plant and disturbance. Then, the estimated model is used for designing a minimum variance controller. In this method, operating data of inputs and outputs of the system are the only requirements for identification of the VARX model. The proposed method has been tested on an experimental benchmark such as a four-tank system which has a nonlinear behavior. The investigation results show that a minimum variance controller can be designed, based on an identified VARX model, for a MIMO system, without any need for an exact model of the system, while at the same time, capable of providing an acceptable minimum variance compared to that precisely obtained using the model-based “Interactor-Matrix” method.