No abstract

No abstract

No abstract

In this paper, we focus on the analysis of the mobile robot navigation problems with the vector field histogram (VFH) under various driving and environmental conditions. The VFH is one of the popular autonomous navigation algorithms. It constructs a polar histogram on the histogram grid map to express obstacles. To analyze the VFH, a number of numerical simulations are carried out where the number of sectors, the robot speed and the width of the path are regulated. As a result, we obtain the minimum number of sectors depending on the regulated driving and environmental conditions for successful navigation in given environments.

This paper addresses a robust fuzzy control problem for an uncertain large-scale nonlinear system using decentralized static output-feedback scheme for both continuous-time and discrete-time cases. In both cases, sufficient design conditions are derived for robust asymptotic stabilization in terms of linear matrix inequalities (LMIs), and are therefore easily tractable by convex optimization. An illustrative example, a two-area power system with parametric uncertainties and the valve-position limit nonlinearity is provided to verify the effectiveness of the proposed technique.