Matching Items (18)

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Image Processing for an Autonomous Throwing Arm and Smart Catching System

Description

In this paper, we propose an autonomous throwing and catching system to be developed as a preliminary step towards the refinement of a robotic arm capable of improving strength and

In this paper, we propose an autonomous throwing and catching system to be developed as a preliminary step towards the refinement of a robotic arm capable of improving strength and motor function in the limb. This will be accomplished by first autonomizing simpler movements, such as throwing a ball. In this system, an autonomous thrower will detect a desired target through the use of image processing. The launch angle and direction necessary to hit the target will then be calculated, followed by the launching of the ball. The smart catcher will then detect the ball as it is in the air, calculate its expected landing location based on its initial trajectory, and adjust its position so that the ball lands in the center of the target. The thrower will then proceed to compare the actual landing position with the position where it expected the ball to land, and adjust its calculations accordingly for the next throw. By utilizing this method of feedback, the throwing arm will be able to automatically correct itself. This means that the thrower will ideally be able to hit the target exactly in the center within a few throws, regardless of any additional uncertainty in the system. This project will focus of the controller and image processing components necessary for the autonomous throwing arm to be able to detect the position of the target at which it will be aiming, and for the smart catcher to be able to detect the position of the projectile and estimate its final landing position by tracking its current trajectory.

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Created

Date Created
  • 2018-05

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Modeling, Analysis, Control and Design of Highly Maneuverable Quadcopters

Description

With the revolution of low-cost microelectronics, rotary-wing vehicles have grown increasingly popular and important in the past two decades. With increased interest in quadcopters comes the need to for a

With the revolution of low-cost microelectronics, rotary-wing vehicles have grown increasingly popular and important in the past two decades. With increased interest in quadcopters comes the need to for a systematic and rigorous framework to model, analyze, control, and design them. This thesis presents the beginning of such a framework.

The work presents the nonlinear equations of motion of a quadcopter. This includes the translational and rotational equations of motion, as well as an analysis of the nonlinear actuator dynamics. The work then analyzes the static properties of a quadcopter in forward flight equilibrium and shows how static properties change as physical properties of the vehicle are varied. Next, the dynamics of forward flight are linearized, and a dynamic analysis is provided.

After dynamic analysis, the work shows detailed hierarchical control system design trade studies, which includes attitude and translational inner-outer loop control. Among other designs, the following are presented: PD control, proportional control, pole-placement control. Each of these control architectures are employed for the inner loops and outer loops. The work also analyzes linear versus nonlinear simulation performance of a quadcopter, specifically for a step x-axis reference command. It is found that the nonlinear dynamics of the actuator cause significant discrepancy between linear and nonlinear simulation.

Finally, this thesis establishes directions for future graduate research. This includes hardware design, as well as moving toward design of a highly-maneuverable thrust-vectoring quadrotor which will be the focus of the proposed graduate PhD research. In summary, this thesis provides the beginning of a cohesive framework to model, analyze, control, and design quadcopters. It also lays the groundwork for graduate research and beyond.

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Created

Date Created
  • 2019-12

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Low-cost Image-assisted Inertial Navigation System for a Micro Air Vehicle

Description

The increasing civilian demand for autonomous aerial vehicle platforms in both hobby and professional markets has resulted in an abundance of inexpensive inertial navigation systems and hardware. Many of these

The increasing civilian demand for autonomous aerial vehicle platforms in both hobby and professional markets has resulted in an abundance of inexpensive inertial navigation systems and hardware. Many of these systems lack full autonomy, relying on the pilot's guidance with the assistance of inertial sensors for guidance. Autonomous systems depend heavily on the use of a global positioning satellite receiver which can be inhibited by satellite signal strength, low update rates and poor positioning accuracy. For precise navigation of a micro air vehicle in locations where GPS signals are unobtainable, such as indoors or throughout a dense urban environment, additional sensors must complement the inertial sensors to provide improved navigation state estimations without the use of a GPS. By creating a system that allows for the rapid development of experimental guidance, navigation and control algorithms on versatile, low-cost development platforms, improved navigation systems may be tested with relative ease and at reduced cost. Incorporating a downward-facing camera with this system may also be utilized to further improve vehicle autonomy in denied-GPS environments.

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Created

Date Created
  • 2014-12

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The Use of Brain Signals to Control a Robotic Car: A First Step

Description

In this study, the engineers from biomedical engineering and electrical engineering researched and analyzed the components, uses, and processes for the brain and the Brain-Computer Interfaces (BCIs). They investigated the

In this study, the engineers from biomedical engineering and electrical engineering researched and analyzed the components, uses, and processes for the brain and the Brain-Computer Interfaces (BCIs). They investigated the basics on the brain, the signals, and the overall uses of the devices. There have been many uses for electroencephalogram (EEG) signals, including prosthetics for patients after nerve injuries, cursor movements on a computer, moving vehicles, and many more projects. There are studies currently in progress and that will be in progress in the future that extend the uses of BCIs. The researchers in this thesis focused more on the processes the scientists used to approach the given problem. Some worked with patients to better his or her life, while others worked with volunteers to gain more knowledge of the brain and/or the BCIs. This thesis includes many different approaches for many unique projects. The analysis includes the location of the signal, the processing of the signal, the filtering of the signal, the transmission of the signal, and the movement of the device based on the signal. The current BCIs are not ready to be in patient’s daily lives, but the researchers are trying to create and perfect them in order to help as many patients as possible. As a biomedical engineer, the researchers in this thesis can apply the knowledge from the articles to solving potential problems in the future and further specific studies.

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Created

Date Created
  • 2019-05

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Modeling, Analysis, and Design of an Omni-Directional Ball-Balancing Robot

Description

The focus of this project investigates high mobility robotics by developing a fully integrated framework for a ball-balancing robot. Using Lagrangian mechanics, a model for the robot was derived and

The focus of this project investigates high mobility robotics by developing a fully integrated framework for a ball-balancing robot. Using Lagrangian mechanics, a model for the robot was derived and used to conduct trade studies on significant system parameters. With a broad understanding of system dynamics, controllers were designed using LQR methodology. A prototype was then built and tested to exhibit desired reference command following and disturbance attenuation.

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Created

Date Created
  • 2019-05

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Operational Safety Verification of AI­-Enabled Cyber-­Physical Systems

Description

One of the main challenges in testing artificial intelligence (AI) enabled cyber physicalsystems (CPS) such as autonomous driving systems and internet­-of-­things (IoT) medical
devices is the presence of machine learning

One of the main challenges in testing artificial intelligence (AI) enabled cyber physicalsystems (CPS) such as autonomous driving systems and internet­-of-­things (IoT) medical
devices is the presence of machine learning components, for which formal properties are
difficult to establish. In addition, operational components interaction circumstances, inclusion of human­-in-­the-­loop, and environmental changes result in a myriad of safety concerns
all of which may not only be comprehensibly tested before deployment but also may not
even have been detected during design and testing phase. This dissertation identifies major challenges of safety verification of AI­-enabled safety critical systems and addresses the
safety problem by proposing an operational safety verification technique which relies on
solving the following subproblems:
1. Given Input/Output operational traces collected from sensors/actuators, automatically
learn a hybrid automata (HA) representation of the AI-­enabled CPS.
2. Given the learned HA, evaluate the operational safety of AI­-enabled CPS in the field.
This dissertation presents novel approaches for learning hybrid automata model from time
series traces collected from the operation of the AI­-enabled CPS in the real world for linear
and non­linear CPS. The learned model allows operational safety to be stringently evaluated
by comparing the learned HA model against a reference specifications model of the system.
The proposed techniques are evaluated on the artificial pancreas control system

Contributors

Agent

Created

Date Created
  • 2020

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Modeling and H-Infinity Loop Shaping Control of a Vertical Takeoff and Landing Drone

Description

VTOL drones were designed and built at the beginning of the 20th century for military applications due to easy take-off and landing operations. Many companies like Lockheed, Convair, NASA and

VTOL drones were designed and built at the beginning of the 20th century for military applications due to easy take-off and landing operations. Many companies like Lockheed, Convair, NASA and Bell Labs built their own aircrafts but only a few from them came in to the market. Usually, flight automation starts from first principles modeling which helps in the controller design and dynamic analysis of the system.

In this project, a VTOL drone with a shape similar to a Convair XFY-1 is studied and the primary focus is stabilizing and controlling the flight path of the drone in
its hover and horizontal flying modes. The model of the plane is obtained using first principles modeling and controllers are designed to stabilize the yaw, pitch and roll rotational motions.

The plane is modeled for its yaw, pitch and roll rotational motions. Subsequently, the rotational dynamics of the system are linearized about the hover flying mode, hover to horizontal flying mode, horizontal flying mode, horizontal to hover flying mode for ease of implementation of linear control design techniques. The controllers are designed based on an H∞ loop shaping procedure and the results are verified on the actual nonlinear model for the stability of the closed loop system about hover flying, hover to horizontal transition flying, horizontal flying, horizontal to hover transition flying. An experiment is conducted to study the dynamics of the motor by recording the PWM input to the electronic speed controller as input and the rotational speed of the motor as output. A theoretical study is also done to study the thrust generated by the propellers for lift, slipstream velocity analysis, torques acting on the system for various thrust profiles.

Contributors

Agent

Created

Date Created
  • 2018

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Process Control Applications in Microbial Fuel Cells(MFC)

Description

Microbial fuel cells(MFC) use micro-organisms called anode-respiring bacteria(ARB) to convert chemical energy into electrical energy. This process can not only treat wastewater but can also produce useful byproduct hydrogen peroxide(H2O2).

Microbial fuel cells(MFC) use micro-organisms called anode-respiring bacteria(ARB) to convert chemical energy into electrical energy. This process can not only treat wastewater but can also produce useful byproduct hydrogen peroxide(H2O2). Process variables like anode potential and pH play important role in the MFC operation and the focus of this dissertation are pH and potential control problems.

Most of the adaptive pH control solutions use signal-based-norms as cost functions, but their strong dependency on excitation signal properties makes them sensitive to noise, disturbances, and modeling errors. System-based-norm( H-infinity) cost functions provide a viable alternative for the adaptation as they are less susceptible to the signal properties. Two variants of adaptive pH control algorithms that use approximate H-infinity frequency loop-shaping (FLS) cost metrics are proposed in this dissertation.

A pH neutralization process with high retention time is studied using lab scale experiments and the experimental setup is used as a basis to develop a first-principles model. The analysis of such a model shows that only the gain of the process varies significantly with operating conditions and with buffering capacity. Consequently, the adaptation of the controller gain (single parameter) is sufficient to compensate for the variation in process gain and the focus of the proposed algorithms is the adaptation of the PI controller gain. Computer simulations and lab-scale experiments are used to study tracking, disturbance rejection and adaptation performance of these algorithms under different excitation conditions. Results show the proposed algorithm produces optimum that is less dependent on the excitation as compared to a commonly used L2 cost function based algorithm and tracks set-points reasonably well under practical conditions. The proposed direct pH control algorithm is integrated with the combined activated sludge anaerobic digestion model (CASADM) of an MFC and it is shown pH control improves its performance.

Analytical grade potentiostats are commonly used in MFC potential control, but, their high cost (>$6000) and large size, make them nonviable for the field usage. This dissertation proposes an alternate low-cost($200) portable potentiostat solution. This potentiostat is tested using a ferricyanide reactor and results show it produces performance close to an analytical grade potentiostat.

Contributors

Agent

Created

Date Created
  • 2018

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System identification using discontinuous data sets and PID loop-shaping control of a vertical take-off and landing drone

Description

Vertical taking off and landing (VTOL) drones started to emerge at the beginning of this century, and finds applications in the vast areas of mapping, rescuing, logistics, etc. Usually a

Vertical taking off and landing (VTOL) drones started to emerge at the beginning of this century, and finds applications in the vast areas of mapping, rescuing, logistics, etc. Usually a VTOL drone control system design starts from a first principles model. Most of the VTOL drones are in the shape of a quad-rotor which is convenient for dynamic analysis.

In this project, a VTOL drone with shape similar to a Convair XFY-1 is studied and the primary focus is developing and examining an alternative method to identify a system model from the input and output data, with which it is possible to estimate system parameters and compute model uncertainties on discontinuous data sets. We verify the models by designing controllers that stabilize the yaw, pitch, and roll angles for the VTOL drone in the hovering state.

This project comprises of three stages: an open-loop identification to identify the yaw and pitch dynamics, an intermediate closed-loop identification to identify the roll action dynamic and a closed-loop identification to refine the identification of yaw and pitch action. In open and closed loop identifications, the reference signals sent to the servos were recorded as inputs to the system and the angles and angular velocities in yaw and pitch directions read by inertial measurement unit were recorded as outputs of the system. In the intermediate closed loop identification, the difference between the reference signals sent to the motors on the contra-rotators was recorded as input and the roll angular velocity is recorded as output. Next, regressors were formed by using a coprime factor structure and then parameters of the system were estimated using the least square method. Multiplicative and divisive uncertainties were calculated from the data set and were used to guide PID loop-shaping controller design.

Contributors

Agent

Created

Date Created
  • 2015

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Modeling and control of flapping wing micro aerial vehicles

Description

Interest in Micro Aerial Vehicle (MAV) research has surged over the past decade. MAVs offer new capabilities for intelligence gathering, reconnaissance, site mapping, communications, search and rescue, etc. This thesis

Interest in Micro Aerial Vehicle (MAV) research has surged over the past decade. MAVs offer new capabilities for intelligence gathering, reconnaissance, site mapping, communications, search and rescue, etc. This thesis discusses key modeling and control aspects of flapping wing MAVs in hover. A three degree of freedom nonlinear model is used to describe the flapping wing vehicle. Averaging theory is used to obtain a nonlinear average model. The equilibrium of this model is then analyzed. A linear model is then obtained to describe the vehicle near hover. LQR is used to as the main control system design methodology. It is used, together with a nonlinear parameter optimization algorithm, to design a family multivariable control system for the MAV. Critical performance trade-offs are illuminated. Properties at both the plant output and input are examined. Very specific rules of thumb are given for control system design. The conservatism of the rules are also discussed. Issues addressed include

What should the control system bandwidth be vis--vis the flapping frequency (so that averaging the nonlinear system is valid)?

When is first order averaging sufficient? When is higher order averaging necessary?

When can wing mass be neglected and when does wing mass become critical to model?

This includes how and when the rules given can be tightened; i.e. made less conservative.

Contributors

Agent

Created

Date Created
  • 2015