We present a new method for automatic adjustment of camera exposure time for visual-servo systems. The proposed method can improve the robustness of image processing in a high-dynamic-range environment. In this paper, we evaluate an appropriate exposure time by computing the local gradient information of a target area, allowing a camera to capture images without losing target features under artificially adjusted illumination conditions. To validate the advantage of the proposed method, an evaluation is made using an off-the-shelf visual-servo system with a machine vision camera. The experimental results demonstrate the effectiveness of our method, which improves the performance of the target recognition algorithm.

No abstract

Abstract. Based on the fact that the inductors and capacitors are fractional order in nature, the four-order mathematical model of the fractional order quadratic Boost converter in PCCM is established by using the Caputo fractional calculus theory. According to the Lyapunov-like theorem of the fractional order system, a non-linear controller is designed. On the basis of the improved Oustaloup approximation algorithm and the equivalent circuit models of the fractional order inductor and capacitor, the influence of the orders on the performance of the quadratic Boost converter in PCCM and the efficiency of the proposed controller are demonstrated by numerical and circuit simulation.