Image Bi-Level Thresholding Based on Gray Level-Local Variance Histogram

Thresholding is a popular method of image segmentation. Many thresholding methods utilize only the gray level information of pixels in the image, which may lead to poor segmentation performance because the spatial correlation information between pixels is ignored. To improve the performance of thresolding methods, a novel two-dimensional histogram—called gray level-local variance (GLLV) histogram—is proposed in this paper as an entropic thresholding method to segment images with bimodal histograms. The GLLV histogram is constructed by using the gray level information of pixels and its local variance in a neighborhood. Local variance measures the dispersion of gray level distribution of pixels in a neighborhood. If a pixel’s gray level is close to its neighboring pixels, its local variance is small, and vice versa. Therefore, local variance can reflect the spatial information between pixels. The GLLV histogram takes not only the gray level, but also the spatial information into consideration. Experimental results show that an entropic thresholding method based on the GLLV histogram can achieve better segmentation performance

Adaptive Fuzzy Fractional-Order Sliding Mode Controller Design for Antilock Braking Systems

Antilock braking system (ABS) has been designed to attain maximum negative acceleration and prevent the wheels from locking. Many efforts had been paid to design controller for ABS to improve the brake performance, especially when road condition changes. In this paper, an adaptive fuzzy fractional-order sliding mode controller (AFFOSMC) design method is proposed for ABS. The proposed AFFOSMC combines the fractionalorder sliding mode controller (FOSMC) and fuzzy logic controller (FLC). In FOSMC, the sliding surface is PD a , which is based on fractional calculus (FC) and is more robust than conventional sliding mode controllers. The FLC is designed to compensate the effects of parameters varying of ABS. The tuning law of the controller is derived based on Lyapunov theory, and the stability of the system can be guaranteed. Simulation results demonstrate the effectiveness of AFFOSMC for ABS under different road conditions

Parameter identification of fractional-order chaotic system with time delay via multi-selection differential evolution

In this paper, the parameter identification issue of fractional-order chaotic system with time delay is studied, which is important for its modelling and controlling. A numerical algorithm for fractional differential equation with time delay is given. Time delay and fractional order along with other ordinary parameters are estimated together, which is rarely considered before. The identification issue is converted to an optimization problem, which is nonlinear, multivariable and multimodal. To solve this complex optimization problem effectively, a multi-selection differential evolution (MS-DE) is proposed. In MS-DE, multiple vectors are generated as candidate for selection, which can avoid the local extremum and speed up the convergence speed. The simulation results illustrate the effectiveness of the proposed MS-DE method