Anisotropic Force Ellipsoid Based Multi-axis Motion Optimization of Machine Tools

The existing research of the motion optimization of multi-axis machine tools is mainly based on geometric and kinematic constraints, which aim at obtaining minimum-time trajectories and finding obstacle-free paths. In motion optimization, the stiffness characteristics of the whole machining system, including machine tool and cutter, are not considered. The paper presents a new method to establish a general stiffness model of multi-axis machining system. An analytical stiffness model is established by Jacobi and point transformation matrix method. Based on the stiffness model, feed-direction stiffness index is calculated by the intersection of force ellipsoid and the cutting feed direction at the cutter tip. The stiffness index can help analyze the stiffness performance of the whole machining system in the available workspace. Based on the analysis of the stiffness performance, multi-axis motion optimization along tool paths is accomplished by mixed programming using Matlab and Visual C＋＋. The effectiveness of the motion optimization method is verified by the experimental research about the machining performance of a 7-axis 5-linkage machine tool. The proposed research showed that machining stability and production efficiency can be improved by multi-axis motion optimization based on the anisotropic force ellipsoid of the whole machining system.

Optimization of Blade Motion of Vertical Axis Turbine

In this paper,a method is proposed to improve the energy efficiency of the vertical axis turbine.First of all,a single disk multiple stream-tube model is used to calculate individual fitness.Genetic algorithm is adopted to optimize blade pitch motion of vertical axis turbine with the maximum energy efficiency being selected as the optimization objective.Then,a particular data processing method is proposed,fitting the result data into a cosine-like curve.After that,a general formula calculating the blade motion is developed.Finally,CFD simulation is used to validate the blade pitch motion formula.The results show that the turbine＇s energy efficiency becomes higher after the optimization of blade pitch motion;compared with the fixed pitch turbine,the efficiency of variable-pitch turbine is significantly improved by the active blade pitch control;the energy efficiency declines gradually with the growth of speed ratio;besides,compactness has lager effect on the blade motion while the number of blades has little effect on it.

Optimal control of stretching process of flexible solar arrays on spacecraft based on a hybrid optimization strategy

The optimal control of multibody spacecraft during the stretching process of solar arrays is investigated,and a hybrid optimization strategy based on Gauss pseudospectral method（GPM） and direct shooting method（DSM） is presented. First, the elastic deformation of flexible solar arrays was described approximately by the assumed mode method, and a dynamic model was established by the second Lagrangian equation. Then, the nonholonomic motion planning problem is transformed into a nonlinear programming problem by using GPM. By giving fewer LG points, initial values of the state variables and control variables were obtained. A serial optimization framework was adopted to obtain the approximate optimal solution from a feasible solution. Finally, the control variables were discretized at LG points, and the precise optimal control inputs were obtained by DSM. The optimal trajectory of the system can be obtained through numerical integration. Through numerical simulation, the stretching process of solar arrays is stable with no detours, and the control inputs match the various constraints of actual conditions.The results indicate that the method is effective with good robustness.

A Novel Nonlinear Scaling Method for Optimal Motion Cueing Algorithm in Flight Simulator

Motion cueing algorithm plays a key role in simulator motion reproduction and improves the realism of movement sensation by combining with the human vestibular system.It is well established that scaling&limiting should be used to decrease the amplitude of the acceleration and angular velocity signals for making full use of limited workspace of motion platform.A novel nonlinear scaling method based on a third-order polynomial and back propagation(BP)neural networks for the motion cueing algorithm is proposed in this paper.The third-order polynomial method is applied to the low amplitude segment of the input signal to minimize the trigger delay of the sensation acceleration;in the high amplitude segment,the BP neural network is used to adaptively adjust the scaling factor of the input signal,to avoid washout displacement and angular displacement beyond the boundary of the workspace.The simulation experiment is verified in the longitudinal/pitch direction for flight simulator,and the result implies that the proposed method not only can overcome the problem of constant scaling parameter and improve motion platform workspace utilization,but also reduce the false cues during the motion simulation process.

Optimal motion cueing algorithm for accelerating phase of manned spacecraft in human centrifuge

This paper presents a novel optimal Motion Cueing Algorithm(MCA)to control the rotations of a Human Centrifuge(HC)and achieve the best simulation of a Space Craft(SC)motion.Relations of the specific forces sensed by astronauts of the SC and the HC have been derived and linearized.A Linear Quadratic Regulator(LQR)controller is implemented for the problem which tends to minimize the error between the two sensed specific forces as well as control input in a cost function.It results in control inputs of the HC to generate its sensed specific force as close as possible to the one in the SC.The algorithm is implemented for both linearized and nonlinear portions of a US space shuttle mission trajectory as a verification using MATLAB.In longitudinal direction,the proposed MCA,works well when the acceleration is less than 2 g in which the tracking error does not exceed 12%.In lateral direction the tracking is much better even in nonlinear region since the error remains less than 7%for tilting up to 50°.Finally,the effect of weight matrixes in the LQR cost function on overall weight and power of the HC motion system is discussed.

A Design of Nonlinear Scaling and Nonlinear Optimal Motion Cueing Algorithm for Pilot’s Station

Motion cueing algorithms(MCA)are often applied in the motion simulators.In this paper,a nonlinear optimal MCA,taking into account translational and rotational motions of a simulator within its physical limitation,is designed for the motion platform aiming to minimize human’s perception error in order to provide a high degree of fidelity.Indeed,the movement sensation center of most MCA is placed at the center of the upper platform,which may cause a certain error.Pilot’s station should be paid full attention to in the MCA.Apart from this,the scaling and limiting module plays an important role in optimizing the motion platform workspace and reducing false cues during motion reproduction.It should be used along within the washout filter to decrease the amplitude of the translational and rotational motion signals uniformly across all frequencies through the MCA.A nonlinear scaling method is designed to accurately duplicate motions with high realistic behavior and use the platform more efficiently without violating its physical limitations.The simulation experiment is verified in the longitudinal/pitch direction for motion simulator.The result implies that the proposed method can not only overcome the problem of the workspace limitations in the simulator motion reproduction and improve the realism of movement sensation,but also reduce the false cues to improve dynamic fidelity during the motion simulation process.