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The choice of a mathematical model of eye movement has had a significant impact on scientific research. This research resulted in a controlling robotic arm that could follow the movement of the human eye and thoroughly examine the structure of the human eye. Exploring the previous models, a model equivalent to a robot with two degrees of freedom is presented. Then, by designing and simulating an optimal linear square controller on the desired system, we could model an eye robot. The purpose of tracking is to target the system, which is shown by simulating this controller. This paper describes how to design a fuzzy controller for the system by presenting the simulation results. Finally, the performance of the two control methods in non-zero initial conditions, rapid eye movements, and uncertainty in the model system constructions are compared. The simulation results show that despite the system control provided by both control methods, the fuzzy control method has a better performance for tracking fast eye movements. This method is resistant to modeling uncertainties by using the qualitative behavior of the system instead of its exact mathematical model. Also, the smaller volume of simulation of control inputs in the fuzzy controller will significantly reduce costs by using this controller. [ABSTRACT FROM AUTHOR]

Flight control system is a unit of the air defense and missile system that takes commands prescribed by the guideline law and operates due to the operators embedded in the system. Missile physical system includes nonlinear aerodynamic coefficients and other physical dependent variables, so accurate identification of them is difficult. This issue makes deference between real and mathematic model of missile equations of motion and causes designed linear controller performance degradation. In this paper, inverse dynamic approach is used for uncertainty identifying and mathematic modeling of missile defense system. Then, this model is used for optimizing and controlling the flight of a missile with nonlinear 6 DOF (Degrees of freedom) equations of motion. Thus, the designed controller is a nonlinear fuzzy-adaptive controller which has high adaption and robustness against the parametric changes during missile's flight. Using the invers dynamic method for modeling motion equations of missile defense is the innovation of this research. [ABSTRACT FROM AUTHOR]

Bat Algorithm is a type of swarm intelligence algorithm which is inspired by the behavior of little bats which are looking for direction in hunting opportunities. Swarm intelligence algorithms are inspired by the nature which are very efficient on crucial optimization problems. These algorithms are simple, flexible and can be implemented easily as well. Analyzing swarm intelligence algorithms makes their utilization reliable and guarantees finding answers by them. Earlier, stability analysis has been accomplished for some swarm intelligence algorithms including Particle Swarm Optimization and Gravitational Search but sufficient mathematical analysis for the bat algorithm has not been done. For this purpose, in the present paper, we considered Bat Algorithm stability analysis using Lyapunov method. In this study, at first, stability analysis of standard bat algorithm has been analyzed. Because of unsuccessful attempts to analyze the stability of standard algorithm, new updating relations has been introduced to increase the degree of freedom. The stability analysis has been presented for these relations. Experimental results illustrate the stability of the new updating relations. [ABSTRACT FROM AUTHOR]