Showing papers by "Eugenia Minca published in 2015"

Adaptive Neuro-Fuzzy Inference Systems as a Strategy for Predicting and Controling the Energy Produced from Renewable Sources

Abstract: The challenge for our paper consists in controlling the performance of the future state of a microgrid with energy produced from renewable energy sources. The added value of this proposal consists in identifying the most used criteria, related to each modeling step, able to lead us to an optimal neural network forecasting tool. In order to underline the effects of users’ decision making on the forecasting performance, in the second part of the article, two Adaptive Neuro-Fuzzy Inference System (ANFIS) models are tested and evaluated. Several scenarios are built by changing: the prediction time horizon (Scenario 1) and the shape of membership functions (Scenario 2).

Wheelchair control and navigation based on kinematic model and iris movement

Abstract: This paper deals control and navigation of the wheelchair for elderly and disabled based on kinematic model iris motion and image processing. Cirrus Power Wheelchair was modelled as an wheeled mobile robot (WMR) with two driving and two free wheels (2DW/2FW). An input/output model of the wheel control system consisting of servo-amplifier, DC motor and gear reducer have been experimentally indentified. To control each driving wheel system, PI controller has been used. Pole placement method was used for tuning PI controller. A software solution was proposed for real-time computing of the wheelchair position based on data acquisition from whell encoders. A navigation system, based on iris movement and image processing, was real-time implemented in MATLAB. This navigation system identifies the user's eye movement in three directions: forward, left and right. Stop of the wheelchair is done by eye closing. Using a LabView platform, a graphic user interface has been designed and implemented, allowing user to control wheelchair movements.

Cycle time optimization of a reversible A/DML served by a mobile robotic system

Abstract: This paper presents a new cycle time optimization (CTO) approach for an assembly/disassembly mechatronics line (A/DML) served by a wheeled mobile robot (WMR) equipped with a robotic manipulator (RM). The mobile robot serves A/DML during disassembling for transporting carry the disassembled components from disassembling locations to the corresponding storage warehouse in order to be reused. Disassembling starts if the final product fails the quality test. The cycle time results from adding up the durations of A/D sequences. Since the elementary assembly operations have constant durations (determined by the duration of the each assembly operation and the displacement duration of transporting line at constant speed, between successive workstations), the problem of cycle time optimization concerns only disassembling. During the disassembly, a repetitive sequence can be identified with a single disassembling stage served by WMR equipped with RM. In this case, an elementary cycle time (ECT) optimization is the maximum value between the following time durations: a) time duration of disassembling and transporting remaining piece towards next station; b) time duration of the RM for gripping and storage disassembled part and WMR's displacement. For the events synchronization are inserted the time intervals between: the displacement with constant speed within/between work stations and the manipulations/displacements of the robotic system. For setting time durations and joining the discrete dynamics of the mechatronics line with the continuous dynamics of the robotic system, a Synchronized Hybrid Petri Nets (SHPN) model running autonomously has been used.

Sliding-mode control and sonnar based bubble rebound obstacle avoidance for a WMR

Abstract: In this paper an algorithm for trajectory-tracking and obstacle avoidance for wheeled mobile robots (WMR) is presented. The algorithm creates a trajectory composed of a global trajectory generated off-line and local obstacle avoidance trajectories that are created when an obstacle is detected by the sonar sensors. Only one discrete-time sliding-mode controller is required to track the resulting trajectory and it does not require separate controllers for following the intended trajectory and avoiding the obstacle. The local avoidance trajectories are generated using Quintic equations to generate a path for the robot and assigning calculating the velocity, acceleration, angular velocity and angular acceleration needed by the discrete-time sliding-mode controller.