In this paper, the guidance laws and controllers for the gliding guided artillery munition is studied. The gliding guided artillery munition has wings for gliding to increase a range; therefore previous guidance laws and controllers for the guided munition could not be applied.Concepts of vector field guidance and proportional navigation guidance are applied for mid-term and terminal guidance, respectively. The gliding guided artillery munition is operated within wide altitude and speed areas; therefore, the controllers are designed for each area, and gain-scheduling and the linear interpolation technique is applied to compute the appropriate gains.
This paper presents results of flight experiments on a navigation algorithm including multiplicative extended Kalman filter for estimating attitude of the guided munition. The filter describes orientation of aircraft by data fusion with low-cost sensors where measurement update is done by multiplication, rather than addition, which is suitable for quaternion representation. In determining attitude from vector observations, the existing approach utilizes a 3-axis accelerometer as a 2-axis inclinometer by measuring gravity to estimate pitch and roll angles, while GNSS velocity is used to derive heading of the vehicle. However, during accelerated maneuvers such as coordinated flight, the accelerometer provides inadequate inclinometer measurements. In this paper, the measurement update process is newly defined to complement the vulnerability by using different vector observations. The acceleration measurement is considered as a result of a centrifugal force and gravity during turning maneuvers and used to estimate roll angle. The effectiveness of the proposed method is verified through flight experiments.
While the rough turning process is machining a workpiece at various cutting depth, the feedrate is usually selected based on the maximum depth of cut. Even if this selection can avoid power saturation or tool breakage, it is very conservative compared to the capacity of machine tools and can reduce the productivity significantly. Many adaptive control techniques have been reported that can adjust the feedrate to maintain the constant cutting force. However, these controllers are not very widely used in manufacturing industry because of the limitations in measuring the cutting force signals and selecting the appropriate cutting force level. In this paper, an unmanned turning process control system is proposed based on the spindle drive characteristics. A synthesized cutting force monitor is used to estimate the cutting force as accurately as a dynamometer does. The reference cutting force level as well as the feed-rate is selected considering the spindle motor characteristics. Because the cutting process is highly nonlinear, a fuzzy logic controller is applied to maintain the desired cutting force level. The experimental results demonstrate that the proposed system can be easily realized in CNC lathe with requiring little additional hardware.
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