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Dynamics and Control of a Stop Rotor Unmanned Aerial Vehicle Alvaro Vargas-Clara; Sangram Redkar
International Journal of Electrical and Computer Engineering (IJECE) Vol 2, No 5: October 2012
Publisher : Institute of Advanced Engineering and Science

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The objective of this work was to develop a variety of control systems for a Stop-Rotor Unmanned Aerial Vehicle (UAV) in hover flight. The Stop-Rotor UAV has capabilities of Vertical Take-off and Landing (VTOL) like a helicopter and can convert from a helicopter mode to an airplane mode in mid-flight. Thus, this UAV can hover as a helicopter and achieve high mission range of an airplane. The stop-rotor concept implies that in mid-flight the thrust generating helicopter rotor stops and rotates the blades into airplane wings. The thrust in airplane mode is then provided by a pusher propeller. The aircraft configuration presents unique challenges in flight dynamics, modeling and control. In this paper a mathematical model is derived, and then the model is simulated with non-zero initial conditions. Various control systems are then implemented. The control techniques utilized are a linear control, optimal linear control and a nonlinear control with the objective of stabilizing the UAV in hover flight. Settling time and control effort are then compared across the different control systems.DOI:http://dx.doi.org/10.11591/ijece.v2i5.1589

Guided Navigation Control of an Unmanned Ground Vehicle using Global Positioning Systems and Inertial Navigation Systems Pooja Velaskar; Alvaro Vargas-Clara; Osama Jameel; Sangram Redkar
International Journal of Electrical and Computer Engineering (IJECE) Vol 4, No 3: June 2014
Publisher : Institute of Advanced Engineering and Science

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This paper demonstrates the use of Global Positioning System (GPS) and Inertial Navigation System (INS) in order to develop an Unmanned Ground Vehicle (UGV) devised to perform a wide variety of outdoor tasks. There are many applications for autonomous UGVs such as tactical and surveillance applications, exploration of areas inaccessible by humans. Capable to navigate to a specific location, and control their motion depending on their surroundings without human intervention. The inertial navigation system makes use of Inertial Measurement Units (IMUs) to measure the change to the UGV's positional parameters, orientation and speed which are continuously monitored and updated. With the advent of GPS, and the positional data from the inertial system the positional information is computed leading to a more accurate control of the UGV; which otherwise suffers from integration drift that occurs with the implementation of inertial systems alone. Autonomous control of the UGV is implemented by coupling GPS sensor and Mission Planner, a tool to map waypoints from Google Maps. Furthermore, system stability and ideal PID (Proportional, Integral and Derivative) values are determined using bicycle modeling analysis to achieve better estimates and control of the UGV.DOI:http://dx.doi.org/10.11591/ijece.v4i3.5183

Characterization of Capacitive Comb-finger MEMS Accelerometers Aaditi Joshi; Sangram Redkar; Thomas Sugar
Bulletin of Electrical Engineering and Informatics Vol 4, No 4: December 2015
Publisher : Institute of Advanced Engineering and Science

This paper discusses various methods for testing the performance of MEMS capacitive comb-finger accelerometers manufactured by Sandia National Laboratories. The use of Capacitive MEMS devices requires complex circuits for measurement of capacitance. Sandia MEMS accelerometer’s capacitance changes in a very small femto-farad (fF) range. The performance of accelerometer is tested using Analog Devices AD7747 sigma-delta capacitance to digital converter. The response of a MEMS capacitive accelerometer to various tests is useful for testing and characterization and investigate it’s suitability for various applications

Characterization of Capacitive Comb-finger MEMS Accelerometers Aaditi Joshi; Sangram Redkar; Thomas Sugar
Bulletin of Electrical Engineering and Informatics Vol 4, No 4: December 2015
Publisher : Institute of Advanced Engineering and Science

This paper discusses various methods for testing the performance of MEMS capacitive comb-finger accelerometers manufactured by Sandia National Laboratories. The use of Capacitive MEMS devices requires complex circuits for measurement of capacitance. Sandia MEMS accelerometer’s capacitance changes in a very small femto-farad (fF) range. The performance of accelerometer is tested using Analog Devices AD7747 sigma-delta capacitance to digital converter. The response of a MEMS capacitive accelerometer to various tests is useful for testing and characterization and investigate it’s suitability for various applications

Characterization of Capacitive Comb-finger MEMS Accelerometers Aaditi Joshi; Sangram Redkar; Thomas Sugar
Bulletin of Electrical Engineering and Informatics Vol 4, No 4: December 2015
Publisher : Institute of Advanced Engineering and Science

This paper discusses various methods for testing the performance of MEMS capacitive comb-finger accelerometers manufactured by Sandia National Laboratories. The use of Capacitive MEMS devices requires complex circuits for measurement of capacitance. Sandia MEMS accelerometer’s capacitance changes in a very small femto-farad (fF) range. The performance of accelerometer is tested using Analog Devices AD7747 sigma-delta capacitance to digital converter. The response of a MEMS capacitive accelerometer to various tests is useful for testing and characterization and investigate it’s suitability for various applications

Sensor Fusion via Brain Emotional Learning for Ground Vehicle Alvaro Vargas-Clara; Sangram Redkar
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 7: July 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i7.pp5324-5330

In this work, the analysis of a filter consisting of the Brain Emotional Learning (BEL) algorithm is presented. The inner workings of the BEL filter are based on emotional learning model in mammalians brain. The BEL filter is implemented in simulation for the purpose of sensor fusion in a ground vehicle. In simulation, the signals from a Global Positioning System (GPS) and an Inertial Navigation System (INS) are integrated, in order to accurately track the trajectory of a ground vehicle around a track. The BEL filter is provided with some sensory signal and reward signal, subsequently the filter seeks to diminish noise from both sensing units, thus eliminating tracking error. A performance comparison between the BEL filter, and the more commonly utilized Kalman filter is presented. The BEL filter demonstrated robustness to uncertainties from the sensing units, it adapts quickly with dynamical change in the plant, and has small computational cost. The BEL filter demonstrated to be effective in sensor fusion.

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