Minisum and maximin aerial surveillance over disjoint rectangles

The aerial surveillance problem (ASP) is finding the shortest path for an aerial surveillance platform that has to visit each rectangular area once and conduct a search in strips to cover the area at an acceptable level of efficiency and turn back to the base from which it starts. In this study, we propose a new formulation for ASP with salient features. The proposed formulation that is based on the travelling salesman problem enables more efficient use of search platforms and solutions to realistic problems in reasonable time. We also present a max–min version of ASP that maximizes the minimum probability of target detection given the maximum flight distance of an aerial platform. We provide computational results that demonstrate features of the proposed models. © 2016, Sociedad de Estadística e Investigación Operativa

A maximal covering location model in the presence of partial coverage

The maximal covering location problem (MCLP) addresses the issue of locating a predefined number of facilities in order to maximize the number of demand points that can be covered. In a classical sense, a demand point is assumed to be covered completely if located within the critical distance of the facility and not covered at all outside of the critical distance. Since the optimal solution to a MCLP is likely sensitive to the choice of the critical distance, determining a critical distance value when the coverage does not change in a crisp way from "fully covered" to "not covered" at a specific distance may lead to erroneous results. We allow the coverage to change from "covered" to "not-covered" within a distance range instead of a single critical distance and call this intermediate coverage level partial coverage, In this paper, we formulate the MCLP in the presence of partial coverage, develop a solution procedure based on Lagrangean relaxation and show the effect of the approach on the optimal solution by comparing it with the classical approach

Peak Observer Based Self-tuning of Type-2 Fuzzy PID Controllers

Part 11: Simulations and Fuzzy ModelingInternational audienceFuzzy PID (proportional-integral-derivative) controllers are commonly used as an alternative to the conventional PID controllers. In order to improve the control system performance of these controllers many self-tuning methods are already studied. It is mostly observed that the self-tuning mechanism should tune the scaling factors of the fuzzy controller to enhance the transient system performance. On the other hand, these studies only focus on the ordinary (Type-1) Fuzzy PID controllers. In this study, Type-2 Fuzzy PID controllers are studied and a peak observer based self-tuning method is proposed for these controllers. In order to show the benefit of the proposed approach, several Matlab simulations are performed where different type of fuzzy control structures are compared. The results obtained from the simulation studies clearly show the advantage of the proposed approach