Journal of Majlesi Journal of Mechatronic Systems
Volume:3 Issue: 1, Mar 2014

Extrusion is one of the important processes to manufacture and produce military and industrial components. Designing its tools is usually associated with trial and error and needs great expertise and adequate experience. Reverse extrusion process is known as one of the common processes for production of hollow parts with closed ends. The significant load required in formation of a workpiece is one of the existing constraints for the reverse extrusion process. This issue becomes rather difficult especially for the parts having thin walls since its analysis using finite element softwares is exposed to some limitations. In this regard, application of artificial intelligence for prediction of load in the reverse extrusion process will not only save time and money, but also improve quality features of the product. Based on the existing data and methods suggested for variations of punching force through the reverse extrusion process, the system is trained and then performance of the system is evaluated using the test data in this paper. Efficiency of the proposed method is also assessed via comparison with the results of others.

The CFAR processors have been utilized in radar systems where the clutter environment is partially unknown and/or has varying statistical properties. In such situations, the performance of the fixed-threshold detector deteriorates significantly, and the CFAR detector is designed to be invariant to changes in the clutter intensity. The CA and OS procedures are the most popular ones in the CFAR world. The CA is the optimum processor in terms of detection probability in homogeneous background while the OS algorithm has its immunity against outlying targets whenever their number is within an allowable range. To benefice the merits of these two algorithms, new versions, which combine the basic of these techniques in estimating the unknown noise power level, have been recently proposed. These versions have improved detection performance either they operate in homogeneous or in non-homogeneous background environments.This paper is devoted to the detection analysis of these versions when the radar receiver contains a noncoherent integrator amongst its fundamental elements. Exact formulas for their false alarm and detection probabilities are derived, in the absence as well as in the presence of interferers. The primary as well as the secondary outlying targets is assumed to be fluctuating in accordance with SWII model. Our obtained results indicate that while the SO version performs nearly as good as the conventional OS scheme in the presence of outlying targets, all the developed versions perform much better than OS in homogeneous situations. In comparison with the CA detector, the modified versions perform better in an ideal operating environment, and behave much better when the background environment is contaminated with a number of spurious targets.

We here proposed the indirect model reference fuzzy control scheme to control the chaotic attitude of a satellite. This paper adopted Lorenz-type attitude motion. This non- linear chaotic system is modeled as a Takagi–Sugeno (TS) fuzzy system. It was shown that using stable adaption law and model reference method, it is possible to control of chaotic behavior of satellite. Our simulation results have demonstrate that the proposed method can satisfy the control object and enhanced stability as well as ease of tuning.

In this paper the stability of the wheel channel or Roll of missile, which has been the focus of attention of scientist for a long time has been investigated. First, its stability has been studied throughLiapanove Stability. Then the visibility and controllability of it have been examined. In order to have access to the missile, the special model has been considered. In order to obtain self regulatory gains, which has been the subject of the current research, LQR method which is a linear estimation has been used. An estimation with order 2 can prepare the regulator for simulation process.

Nowadays, robots help humans with so many works and have replaced them in the assistance of performing some laborious and dangerous tasks. The present study aims at finding a relation between changes in length of 2 degrees of freedom (2-DOF) robotic arm and its angular performance. For this purpose, the capabilities of Adaptive Neuro-fuzzy Inference System (ANFIS) and also inverse kinematics method were applied on 2-DOF robotic. The main purpose of this paper is to identify an appropriate arm length for this robot through analyzing and comparing the obtained results from changes carried out on the arm length.

In this article, we consider the singularity avoidance of a redundant manipulator. It is shown that small perturbations caused by singularities can destabilize the whole system. Its realization would be rigorous physical damages to the robot. The remedy for such structural sensitivity to singularities consists in using an adaptive controller by which the control signal power is dominant over the unstable configurations. In this note, an adaptive algorithm to control redundant manipulators is proposed and its singularity avoidance performance as the secondary task is studied. An outer-inner loop controller called the augmented hybrid impedance control scheme is used. The inner loop consists of a Cartesian-level potential difference controller, a redundancy resolution scheme at the acceleration level, and a joint-space inverse dynamic controller. The proposed scheme works on the redundancy resolution block and is comprised of a multi-state function based on the Jacobean matrix of robot. We applied the proposed algorithm to a Mitsubishi PA10 7-DOF manipulator and simulation results proved the effectiveness of the algorithm.

Engineering and Technology in the coming century instruments, measurements, and products will be related very tiny dimensions (a few tens of nanometers). Knowing the size and particle size distribution of the information required for manufacturing various products. Since the particle size and size distribution, influence on mechanical strength, density and thermal and optical properties of the final product is determined by the sizes are essential. Existing methods of measuring nano particles can be noted that the static and dynamic light scattering measurements. The method of dynamic light scattering hydrodynamic radius of the particle parameters that can be measured. in this method autocorrelation function compute in the certain angle by measure intensity of incident scattering.One of the important method of measuring nano particle is when they are being produced. In this investigation a hardware system is suggested based on theory of two methods (SLS,DLS), then simulation of both methods and the result was compared by traditional methods. In conclusion after simulation in suggested method, measuring time was reduced and an error of about %5 in radius of gyration, average molecular weight, second virial coefficient, hydrodynamic radius were obtained.