Advanced Materials Research Vols. 403-408

Abstract: automated motorized line of sight control of antennas is discussed in this paper which is an advanced technique. By using automated system between the antennas to obtain maximum signal strength and reduce the over all fading diffractions between the two antennas.

Abstract: The problem of micromouse is 30 years old but its importance in the field of robotics is unparalleled, as it requires a complete analysis & proper planning to solve the problem. This paper proposes two computationally efficient algorithms for maze solving. Most of the reported algorithms explore complete maze before finding the shortest path to the center of the maze, thereby taking large exploration time. Our proposed algorithms take less time in maze exploration by exploring the maze partially and by traversing less number of cells to reach the center of the maze. An optimal method for maze solving with partial exploration of the maze can hardly be found applicable to all type of mazes, but our algorithms are found to be efficient in most of the cases. Simulation of our proposed algorithms on the some standard mazes show that one of the two algorithms described in this paper gives the better solution by only partially exploring the maze and the other algorithm also gives the comparative results when compared with the algorithms reported in the literature.

Abstract: This paper describes the non Verbal communication method for developing a gesture-based system using Mimesis model. The proposed method is applicable to any hand gesture represented by a multi-dimensional signal. The entire work concentrates mainly on hand gestures recognition. It develops a way to communicate between Humans and the Humanoid Robots through gestural medium. The Mimesis is the technique of performing human gestures through imitation, recognition and generation. Different Gestures are being converted into code words through the use of code book. These code words are then converted into Proto-Symbols, these proto symbol then forms basis for training of the Humanoid robot. The recognition part is performed through a “distance vector”, a novel algorithm developed by us which is a combination of Euclidean distance and K-nearest neighbor. The generation part is done through the use of WEBOTS which include use of Humanoid robot HOAP 2 having 25 degrees of freedom. All the process of training, recognition and generation are simulated through MATLAB.

Abstract: This paper is related to the human perception based idea by using heuristic information for the navigation of mobile robots in cluttered dynamic environments which provides a general, robust, safe and optimized path. The heuristic rule base network consists of a simple algorithm which makes predefined estimation function very smaller. The estimation function should be adequately defined for desired movement in the environments. A navigation system using rule based technique that allows a mobile robot to travel in an environment about, which the robot has no prior knowledge. This heuristic rule is applied in conjunction with artificial neural network. The proposed intelligent controller provides an optimum trajectory which increases the effectiveness of a mobile robot. A series of simulations test has been conducted to show the effectiveness of the proposed algorithm.

Abstract: In this paper the singular perturbation theory is used to design observer for estimation of state variables for proper control of half-car active suspension system. The liner quadric Gaussian (LQG) controller has been used to obtain feedback gains. The suspension system performance is optimized with respect to ride comfort, tire deflections and front and rear suspension travels. The simulation results show that the proposed approach is highly effective in evaluating the performance of an active suspension system.

Abstract: This paper presents a fuzzy controller for positioning control with a newly developed surgical navigation system which uses tactile signals as feedback to the operator. The advantage of using tactile vibrations to transmit feedback information about the position of the surgical tool relative to particular tissues is the reduction of the contant gaze of the operator from the field of operation to a remote screen. The Fuzzy controller was derived without any analytical system model and its efficiency was compared to that of an already developed classical controller.

Abstract: In this paper the digital controller design for vehicle suspension system, based on a half-car model using singular perturbed systems is considered. This strategy is based on the slow and fast subsystems controller design. The simulation results show them favorable performance of the controller and achieve fast and good response.

Abstract: In this paper, a feedback control method is proposed for the anti-control of chaos of linear controllable systems based on model-matching. First, it is considered that the linear system is completely known and an anti-control method is designed. Then, the parameters of the linear controllable system in companion form are assumed to be unknown. The chaotification is achieved choosing an appropriate control law and a parametric updating law based on Lyapunov stability theory, which provides the stability of the resulting adaptive system and the convergence of the tracking errors to zero. The proposed method is applied to anti-control of chaos of a linear system, while the Rössler chaotic system is the reference model. The numerical simulation results show the effectiveness of the proposed method.

Abstract: Application of fractional order (FO) PID controllers has been proposed over an unreliable network with random delays and packet dropouts. The gain and order of the controllers have been tuned offline to obtain optimal time domain performance for different network conditions with the help of Genetic Algorithm (GA). The FO controller parameters are then scheduled for time varying network conditions and the performance is compared with their integer order counterparts.

Abstract: In this paper, Genetic Algorithm is utilized to optimize the coefficients of a decentralized PID controller for a nonlinear Multi-Input Multi-output process by minimizing the Integral Absolute Error (IAE).The controller is tuned at chosen operating points, which are selected to cover the nonlinear range of the process. The optimal PID controller parameters are gain scheduled using a Fuzzy Gain scheduler. The effectiveness of the proposed control scheme has been demonstrated by conducting simulation studies on a Continuous Stirred Tank Reactor (CSTR) process which exhibits dynamic nonlinearity