Journal of Majlesi Journal of Mechatronic Systems
Volume:9 Issue: 4, Dec 2020

Research shows that most of the damage to off-road vehicles is due to a lack of balance in critical situations. This paper is studying the impact of the arm on tracked vehicle trafficability on critical slopes. The position and weight of the arm have a direct effect on the position and location of the tracked vehicle's center of mass. The neural network is used to find the function between the position of the vehicle's center of mass and the maximum slope traverse ability. The neural network is trained using experimental data. In this study, while investigating the effect of arm position on vehicle trafficability, a fuzzy control system is designed to maintain a tracked vehicle balance at a critical slope. This controller prevents the tracked vehicle from tip-over on the critical slope. Based on vehicle speed control, a controlling system is also designed for crossing the bump. A quasi-rotational motion for a tracked vehicle, makes it possible to cross the bump which it cannot pass in normal condition. The small tracked vehicle is equipped for trafficability experiments. The pitch angle is compared and validated between simulations and experiments.

This paper proposes the mitigation of grid voltage disturbances using a nine-level Packed E Cells (PEC9) based dynamic voltage restorer (DVR) solution. Which regulates the injection of the compensation voltage in series and synchronism with the grid during the voltage disturbance events, the auxiliary capacitor voltage, while controlling the PEC9 output current. The nine-level PEC (PEC9) is composed of seven active switches and two dc capacitors that are shunted by a four-quadrant switch to from the E-cell, and it makes use of a single dc link. With the proper design of the corresponding PEC9 switching states, the dc capacitors are balanced using the redundant charging/discharging states. Since the shunted capacitors are horizontally extended, both capacitors are simultaneously charged or discharged with the redundant states, so only the auxiliary dc-link voltage needs to be sensed and regulated to half of the input dc source voltage, and consequently, dc capacitors' voltages are inherently balanced to one quarter of the dc bus voltage. To this end, an active capacitor voltage balancing integrated to the Nearest Level Control (NLC) has been designed based on the redundant charging/discharging states to regulate the dc capacitors voltages of PEC9. Furthermore, using the E-cell not only reduces components count but also the proposed topology permits multi ac terminal operation. The In-Phase control method is selected to control the proposed DVR and use the synchronous reference frame (SRF) method to detect the network voltage fluctuations. To verify and validate the proposed DVR performance, simulations are carried out in the MATLAB / SIMULINK software environment, and the results indicate the optimal performance and desirability of the proposed DVR to compensate for the voltage sag and swell distribution systems. Theoretical analysis and simulation results are given to show the high performance of the proposed solution.

In this present work which mainly concerns the Backstepping control of the manipulator robot with 2 degrees of freedom, we are interested in the dynamic model of the manipulator robot which expresses the torques exerted by the actuators as a function of the positions, speeds and accelerations of the joints by applying to it Backstepping control laws based on a Lyapunov function for a pursuit of certain desired trajectories. The Robustness test is carried out in order to have a better appreciation of the results obtained through the system studied by considering parametric variations of up to 40% for the robot joint masses, the results obtained clearly confirm the dynamic performances and the robustness of the control applied for the pursuit of the trajectories.

The present paper is aimed to analyze static deformation, natural frequency and subharmonic resonance of a bilayer cantilever microbeam, the second layer of which has a variable width and is located on a point along the microbeam's length. Electrostatic actuation is induced by applying the voltage between the microbeam and its opposite electrode. The importance of such configuration is revealed particularly in mass and pollutants micro-sensors. First, the nonlinear equation of motion, which has been extracted in previous studies using Hamilton's principle and considering the bending neutral axis shortening assumption, was rewritten for a microbeam with variable-width second layer. Then differential equations governing the static deflection and free vibration equation around the stability point are solved using Galerkin method. Three mode shapes of a doubled stepped-microbeam are employed as the comparison function. The shapes such as triangular, parabolic, symmetric parabolic and hyperbolic are considered for the second layer. In order to find the optimal length and thickness for the selected form, the relevant diagrams were plotted for static deformation and natural frequency at constant volume and different lengths and thicknesses, and then were analyzed and investigated. The discretized equations are solved by the perturbation theory. The excitation frequency is tuned near twice the fundamental natural frequencies (subharmonic excitation). The results show that system behavior depends on the size, position and width of the coated layer. The results of this paper can be used for optimum design of microsystems such as microswitches and mass and pollutant microsensors.

DVR is one of the important Custom Power Device to compensate sag or swell of voltage in the distribution network that precision of voltage compensation depends on the ability of the PWM design, the appropriate controller and the selection of the filter parameters. Traditional controllers such as PI, PID and smart controllers such as fuzzy controller can be used to control the DVR. Fuzzy controllers are nonlinear controllers with specific structure. The fuzzy controller acts like an expert human when controlling. The disadvantage of these controllers is their inability to learn that genetic algorithms, neural networks and etc are used to solve this problem. In this paper, a genetic algorithm is used to optimize the fuzzy membership functions of the fuzzy controller.

Eavesdropping is a method to access the information. The eavesdropper needs some coding output parameters to access the information on an unspecified channel. Since there are various types of encoders to encode the message, considering a signal decoder for each encoder is not possible. So for retrieving the transmitted information, blind channel parameters detection is a good choice. Up to now various methods such as entropy, hamming weight, interleaving and Gaussian elimination have been proposed to detect blind parameters, but due to the high noise level, in long messages the algorithm has faced with high hardware complexity and accurate estimation. In the entropy method, the detection of parameters in long messages has a time complexity also in Gaussian elimination method we need to determine a threshold that is not reliable. the proposed method reduced the weaknesses of previous algorithms and this method guarantees some parameters estimation in the presence of different noises and its complexity is less than other algorithms. This algorithm is structurally composed of Gaussian elimination and interleaving algorithms. The proposed method well estimates the coded parameters in the presence of different noises.