Intelligent environments aim to maximize the user comfort and safety while achieving other objectives such as energy minimization. Intelligent shared spaces (such as homes, classrooms, offices, libraries, etc.) need to consider the preferences of users from diverse backgrounds. However, there are high levels of uncertainties faced in intelligent shared spaces. Hence, there is a need to employ i...

It has been twenty years since DeWit (1982) first applied fuzzy logic (FL) to insurance. That article sought to quantify the fuzziness in underwriting. Since then, the universe of discourse has expanded considerably and now also includes FL applications involving classification, projected liabilities, future and present values, pricing, asset allocations and cash flows, and investments. This ar...

Different approaches of a learnable Fuzzy-Logic (FL) concept for highly fast and accurate position control of industrial robots will be presented which provides both time-optimality for large position errors as well as well damped response (no overshoot) near the target. For automatic optimization of the control parameters an additional Neural-Network component is introduced. Based on simulatio...

In this paper, the operation of a fuzzy predictive filter used to provide high robustness against feedback signal noise in a fuzzy logic (FL)-based angle estimation algorithm for the switched reluctance motor is described. The fuzzy predictive filtering method combines both FL-based time-series prediction, as well as a heuristic knowledge-based algorithm to detect and discard feedback signal er...

, we present an algorithm for path planning to a target for mobile robot in unknown environment. The proposed algorithm allows a mobile robot to navigate through static obstacles, and finding the path in order to reach the target without collision. This algorithm provides the robot the possibility to move from the initial position to the final position (target). The proposed path finding strate...

This paper presents a strategy for optimization of a fuzzy logic controller based on a control scheme, which consists of a fuzzy logic (FL) controller and a conventional derivative @) controller. For this purpose, we first choose a set of membership functions regarding change-in-error e ' , which represent the feedback of velocity. Then we optimize them using neural network in self-organizing p...

To find an optimal path for robots in an environment that is only partially known and continuously changing is a difficult problem. This paper presents a new method for generating a collision-free near-optimal path for an autonomous mobile robot in a dynamic environment containing moving and static obstacles using neural network and fuzzy logic with genetic algorithm. The mobile robot selects a...

The authors propose the implementation of hybrid Fuzzy Logic-Genetic Algorithm (FL-GA) methodology to plan the automatic assembly and disassembly sequence of products. The GA-Fuzzy Logic approach is implemented onto two levels. The first level of hybridization consists of the development of a Fuzzy controller for the parameters of an assembly or disassembly planner based on GAs. This controller...

This paper discusses the integration of health monitoring and flight control systems for small Unmanned Aerial Vehicles (UAVs). After briefly reviewing previous fuzzy logic controllers (FLC) of air vehicles, a very low cost integration method is proposed. The proposed fuzzy logic (FL) selects the best gain values for the operation of PD or PID controllers of the autonomous flight system accordi...

ABSTRACT Ongoing development in nanotechnology and bioinformatics will enable the construction of nanorobot which will work at nano-scale. Nanorobot development has many challenges and limitations such as its control and behavior in different environments. In this proposed work we present DNA nanorobot design, methodology for identification of metastatic tumor cells and DNA nanorobot control te...