Abstract - This paper presents a study of fuzzy optimal variance control problem for dynamical systems subject to actuator amplitude and rate constraints. Using Takagi-Sugeno fuzzy modeling and dynamic Parallel Distributed Compensation technique, the stability and the constraints can be cast as a multi-objective optimization problem in the form of Linear Matrix Inequalities. By utilizing the formulations and solutions for the input and output variance constraint problems, we develop a fuzzy full state feedback controller. The stability and performance of the proposed controller are demonstrated through its application to the airfoil flutter suppression.
Abstract - As the applications for using small Unmanned Aircraft Systems (sUAS) beyond visual line of sight (BVLOS) continue to grow in the coming years, it is imperative that intelligent sensor fusion techniques be explored. In BVLOS scenarios the vehicle position must accurately be tracked over time to ensure no two vehicles collide with one another, no vehicle crashes into surrounding structures, and to identify off-nominal scenarios. In this study, an intelligent systems approach is used to estimate the position of sUAS given a variety of sensor platforms, including GPS, radar, and onboard detection hardware. Common research challenges include multiple sensor platforms and sensor reliability. In an effort to resolve these challenges, techniques such as a Maximum a Posteriori estimation and Fuzzy Logic based sensor confidence determination are used.
Abstract - As of late, hierarchical Fuzzy Inference Systems (hFIS) have received considerable attention because of their ability to control complex decision-making procedures. Although the performance of hFISs appears to be extremely effective in complex scenarios, there is a question about the differences between the hierarchical and single FISs (sFIS) and the relationship between the two. In this work, a transformation is derived which converts a Mamdani type hFIS into its equivalent sFIS representation. This is accomplished by equating their output membership functions. The equivalency between the outputs of the two representations is proven using a Satisfiability Modulo Theories (SMT) solver approach. Furthermore, we provide a detailed development procedure and results are presented which demonstrate the ease of implementation of the transformation as well as a wide applicability to meaningful large-scale problems.