A novel spatial parallel manipulator designed to assemble diagnostic instruments in SG-III is introduced in this paper. Firstly, resorting to screw theory, mobility analysis is presented for this manipulator. Then, the inverse KINEMATICS problem is determined by the method of RPY transformation with the singularity analyzed. As a key issue in parallel manipulators, it is more di cult to solve the FORWARD KINEMATICS problem, since it is highly nonlinear and coupled. In this work, three di erent approaches are presented to deal with this issue, namely, the back propagation neural network, the simpli ed ant colony optimization, and the proposed improved Newton iterative method. Simulation of each approach is conducted, and their merits and demerits are compared in detail. It is concluded that the improved Newton iterative method, which can provide good initial iteration values, shows the best performance in estimation of the nonlinear FORWARD kinematic mapping of the considered parallel manipulator.

The FORWARD position KINEMATICS (FPK) of a parallel manipulator with new architecture supposed to be used as a moving mechanism in a flight simulator project is discussed in this paper. The closed form solution for the FPK problem of the manipulator is first determined. It has, then, been shown that there are at most 24 solutions for FPK problem. This result has been verified by using other techniques such as geometric approach and a numerical method known as polynomial continuation. Numerical examples are performed to display all possible solutions available for the devised manipulator.

Unlike serial manipulators, FORWARD kinematic problem (FKP) of parallel robots is highly complicated and its analytical solution is not generally le. Therefore, in most cases numerical methods are used to solve this problem which are relatively time consuming. On the other hand, reducing the duration of FKP analysis is an essential task for applications like real-time control. In this paper, artificial neural networks and a 3rd-order numerical algorithm are combined and a new hybrid strategy is proposed for FORWARD KINEMATICS analysis of parallel manipulators which significantly increases the speed of the FKP solution. In the proposed method, an approximate solution of the FKP is first produced by the neural network. This solution is next considered as an initial guess for the 3rd-order numerical technique which solves the nonlinear FORWARD KINEMATICS equations and obtains the answer with a desired level of accuracy. The proposed method is applied to a spatial 3-PSP parallel manipulator. The results show that using this method will lead to a 35 percent reduction in number of iterations and a 12 percent reduction in the FKP analysis time, while maintaining high level of solution accuracy.

Purpose: FORWARD Walking (FW) and Backward Walking (BW) on different gradients of the treadmill is a common exercise for lower extremity rehabilitation. However, limited studies are found about the three-dimensional analysis of lower extremity and status of the knee joint during FW and BW on different gradients. Therefore, this study aimed to investigate the lower extremity joints KINEMATICS during FW and BW on incline and decline surfaces.Methods: The current research has a quasi-experimental design. Sixteen healthy males with the mean (SD) age of 22.4 (2.5) years, volunteered to participate in this study. The subjects’ FW and BW with their preferred speed on a treadmill at four gradients (-7.5%, 0%, +5% and+10%), were analyzed by using motion capture system. All data were analyzed using paired sample t test (P<0.05).Results: Significant differences were seen between FW and BW in most angular variables in sagittal plane. However, there were no significant differences between FW and BW in most parameters of knee angle in frontal plane.Conclusion: Based on the results, with increase in FW inclination and decrease in BW inclination, the knee varus angle in frontal plane reduces. Therefore, FW on the upslope surfaces or BW on downslope surfaces, probably is a suitable solution to reduce the loads exerted on medial compartment of the knee.

In this paper, a novel spatial six-degree-of freedom parallel manipulator actuated by three base-mounted partial spherical actuators is studied. This new parallel manipulator consists of a base platform and a moving platform, which are connected by three legs. Each leg of the manipulator 'is composed of a spherical joint, prismatic joint and universal joint. The base-mounted partial spherical actuators can only specify the direction of their corresponding legs. In other' words, the spin of each leg is a passive degree-of-freedom. The inverse pose and FORWARD pose of the new mechanism are described. In the inverse pose pneumatics, active joint variables are calculated with no need for evaluation of the passive joint variables. To solve the FORWARD pose problem, a much simpler method compared to the traditional method is introduced. Closed form relations for the inverse and FORWARD and KINEMATICS are proposed. Finally, two sets of singular consignation of the newly introduced manipulator with different natures are obtained.

The Stewart platform is primarily used for generating arbitrary motions in three-dimensional space. However, it can also be utilized for measuring the three-dimensional position of an object attached to the moving platform. In this configuration, the Stewart platform functions as a sensory system. One challenge of this application is the high computational cost associated with determining the position of the moving platform relative to the fixed reference platform using data from six-length sensors. In this study, the sensory capabilities of the Stewart platform are investigated by introducing a high-performance and numerically agile approach. This approach involves developing an extended set of nonlinear algebraic equations that are well-suited for real-time applications. By applying this procedure to derive the Cartesian coordinates of three points on the moving platform and comparing the results with those obtained from computer-aided design software, a strong correlation is observed. To further evaluate the effectiveness of the approach, its performance is analyzed when subjected to harmonic time histories from six length sensors and when the legs' base positions are arranged regularly or non-regular on the fixed platform. The results demonstrate that the present method, particularly by updating initial conditions at every time increment, exhibits high computational efficiency.

This paper offers a modified circuit for improving linearization of power amplifier with based on the model of the Feed FORWARD circuit amplifier. With the help of mathematical model for the single power amplifier, the circuit is simulated und a demonstrator is built and measured. it is used a complex Taylor series for modeling the power amplifier by the approximation of the amplitude transfer function and the level-dependence of the transmission-phase of the power amplifier and can be understood as a simplified form of Volterra series. In our proof of concept experiment, we verified the concept but also found that the adjustment of the circuit is critically dependent on the drive conditions and linearization is achieved only for a narrow range of drive power. The simulation of the total circuit is largely determined by the models for the transmission characteristics of the two power amplifiers. The new circuit in compare with the conventional Feed FORWARD amplifier, in addition a significant increase in efficiency to minimize the power of the distortion signal 3IMD for large driving amplitude (large signals).