8 research outputs found
Sliding Mode Control and Vision-Based Line Tracking for Quadrotors
This thesis describes the design of Sliding Mode Control applied to quadrotor UAV flight. This is a nonlinear control technique in which a discontinuous control signal is applied to drive the so-called sliding variable to zero, which defines the sliding surface. The sliding variable should be designed in such a way that approaching the sliding surface is beneficial to tracking the reference signals. The advantages of Sliding Mode Control are that the need for simplifying the underlying dynamical model through linearization is avoided, it is robust and adaptive, and works even if the system to be controlled is highly nonlinear or has model uncertainties. Sliding Mode Control has one major issue associated with it, namely the chattering phenomena in the control inputs, which is undesirable. This can be tackled by approximating the discontinuous sign function in the control input with a approximated continuous function, or by applying techniques such as adaptive fuzzy gain scheduling. As with other control methods, Sliding Mode Control requires tuning of the control parameters to obtain an optimal performance. In this work, genetic algorithms were investigated as a way to tune the controller parameters. The findings of this thesis were combined with the design of a line tracking algorithm in order to enter the MathWorks Minidrone Competition.This thesis describes the design of Sliding Mode Control applied to quadrotor UAV flight. This is a nonlinear control technique in which a discontinuous control signal is applied to drive the so-called sliding variable to zero, which defines the sliding surface. The sliding variable should be designed in such a way that approaching the sliding surface is beneficial to tracking the reference signals. The advantages of Sliding Mode Control are that the need for simplifying the underlying dynamical model through linearization is avoided, it is robust and adaptive, and works even if the system to be controlled is highly nonlinear or has model uncertainties. Sliding Mode Control has one major issue associated with it, namely the chattering phenomena in the control inputs, which is undesirable. This can be tackled by approximating the discontinuous sign function in the control input with a approximated continuous function, or by applying techniques such as adaptive fuzzy gain scheduling. As with other control methods, Sliding Mode Control requires tuning of the control parameters to obtain an optimal performance. In this work, genetic algorithms were investigated as a way to tune the controller parameters. The findings of this thesis were combined with the design of a line tracking algorithm in order to enter the MathWorks Minidrone Competition
Sliding Mode Control and Vision-Based Line Tracking for Quadrotors
This thesis describes the design of Sliding Mode Control applied to quadrotor UAV flight. This is a nonlinear control technique in which a discontinuous control signal is applied to drive the so-called sliding variable to zero, which defines the sliding surface. The sliding variable should be designed in such a way that approaching the sliding surface is beneficial to tracking the reference signals. The advantages of Sliding Mode Control are that the need for simplifying the underlying dynamical model through linearization is avoided, it is robust and adaptive, and works even if the system to be controlled is highly nonlinear or has model uncertainties. Sliding Mode Control has one major issue associated with it, namely the chattering phenomena in the control inputs, which is undesirable. This can be tackled by approximating the discontinuous sign function in the control input with a approximated continuous function, or by applying techniques such as adaptive fuzzy gain scheduling. As with other control methods, Sliding Mode Control requires tuning of the control parameters to obtain an optimal performance. In this work, genetic algorithms were investigated as a way to tune the controller parameters. The findings of this thesis were combined with the design of a line tracking algorithm in order to enter the MathWorks Minidrone Competition.This thesis describes the design of Sliding Mode Control applied to quadrotor UAV flight. This is a nonlinear control technique in which a discontinuous control signal is applied to drive the so-called sliding variable to zero, which defines the sliding surface. The sliding variable should be designed in such a way that approaching the sliding surface is beneficial to tracking the reference signals. The advantages of Sliding Mode Control are that the need for simplifying the underlying dynamical model through linearization is avoided, it is robust and adaptive, and works even if the system to be controlled is highly nonlinear or has model uncertainties. Sliding Mode Control has one major issue associated with it, namely the chattering phenomena in the control inputs, which is undesirable. This can be tackled by approximating the discontinuous sign function in the control input with a approximated continuous function, or by applying techniques such as adaptive fuzzy gain scheduling. As with other control methods, Sliding Mode Control requires tuning of the control parameters to obtain an optimal performance. In this work, genetic algorithms were investigated as a way to tune the controller parameters. The findings of this thesis were combined with the design of a line tracking algorithm in order to enter the MathWorks Minidrone Competition
Sliding Mode Control and Vision-Based Line Tracking for Quadrotors
This thesis describes the design of Sliding Mode Control applied to quadrotor UAV flight. This is a
nonlinear control technique in which a discontinuous control signal is applied to drive the so-called
sliding variable to zero, which defines the sliding surface. The sliding variable should be designed in
such a way that approaching the sliding surface is beneficial to tracking the reference signals. The
advantages of Sliding Mode Control are that the need for simplifying the underlying dynamical
model through linearization is avoided, it is robust and adaptive, and works even if the system to be
controlled is highly nonlinear or has model uncertainties. Sliding Mode Control has one major issue
associated with it, namely the chattering phenomena in the control inputs, which is undesirable.
This can be tackled by approximating the discontinuous sign function in the control input with a
approximated continuous function, or by applying techniques such as adaptive fuzzy gain scheduling.
As with other control methods, Sliding Mode Control requires tuning of the control parameters
to obtain an optimal performance. In this work, genetic algorithms were investigated as a way to
tune the controller parameters. The findings of this thesis were combined with the design of a line
tracking algorithm in order to enter the MathWorks Minidrone Competition.This thesis describes the design of Sliding Mode Control applied to quadrotor UAV flight. This is a
nonlinear control technique in which a discontinuous control signal is applied to drive the so-called
sliding variable to zero, which defines the sliding surface. The sliding variable should be designed in
such a way that approaching the sliding surface is beneficial to tracking the reference signals. The
advantages of Sliding Mode Control are that the need for simplifying the underlying dynamical
model through linearization is avoided, it is robust and adaptive, and works even if the system to be
controlled is highly nonlinear or has model uncertainties. Sliding Mode Control has one major issue
associated with it, namely the chattering phenomena in the control inputs, which is undesirable.
This can be tackled by approximating the discontinuous sign function in the control input with a
approximated continuous function, or by applying techniques such as adaptive fuzzy gain scheduling.
As with other control methods, Sliding Mode Control requires tuning of the control parameters
to obtain an optimal performance. In this work, genetic algorithms were investigated as a way to
tune the controller parameters. The findings of this thesis were combined with the design of a line
tracking algorithm in order to enter the MathWorks Minidrone Competition
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HyperXite Winter Design Review Poster 2021
Abstract: The Hyperloop pod is a vehicle that is set to revolutionize the technological advancement of transportation systems. Like the bullet train, it is meant to transverse from point A to B at a tremendous speed, making it convenient for people that rely on transportation systems for traveling and commuting. However, the Hyperloop pod is designed to travel through a vacuum tube to negate air friction so that the pod can achieve high accelerations. Ideally, the concept compensates the practical modes of transportation by being relatively inexpensive compared to airfares and fast compared to public transportation methods. The HyperXite team has been building scaled-down prototype pods for the past four years with this Hyperloop vision in mind. After determining that building a full prototype pod would not be feasible for the team this year given the state of the competition and budgetary constraints, the team decided to move forward with a scaled down version of the pod with design concepts that we wanted to test. We set a loose requirement of a 3-foot-long pod that would still be able to move along the I-beam track with the given dimensions from the 2019 SpaceX Hyperloop competition. The pod stands at 62.36 inches in length, 30.137 inches in width, 17.452 inches in height, and its current mass is approximately 120lbs. We moved forward with a dual motor design, friction brakes that are actuated by our pneumatic system, and an aluminum chassis. Not having SpaceX Competition design requirements to follow, gave our team the freedom to test different designs for each subsystem
Recommended from our members
HyperXite Winter Design Review Poster 2021
Abstract: The Hyperloop pod is a vehicle that is set to revolutionize the technological advancement of transportation systems. Like the bullet train, it is meant to transverse from point A to B at a tremendous speed, making it convenient for people that rely on transportation systems for traveling and commuting. However, the Hyperloop pod is designed to travel through a vacuum tube to negate air friction so that the pod can achieve high accelerations. Ideally, the concept compensates the practical modes of transportation by being relatively inexpensive compared to airfares and fast compared to public transportation methods. The HyperXite team has been building scaled-down prototype pods for the past four years with this Hyperloop vision in mind. After determining that building a full prototype pod would not be feasible for the team this year given the state of the competition and budgetary constraints, the team decided to move forward with a scaled down version of the pod with design concepts that we wanted to test. We set a loose requirement of a 3-foot-long pod that would still be able to move along the I-beam track with the given dimensions from the 2019 SpaceX Hyperloop competition. The pod stands at 62.36 inches in length, 30.137 inches in width, 17.452 inches in height, and its current mass is approximately 120lbs. We moved forward with a dual motor design, friction brakes that are actuated by our pneumatic system, and an aluminum chassis. Not having SpaceX Competition design requirements to follow, gave our team the freedom to test different designs for each subsystem