Bicycle dynamics and behaviors have been vastly studied through modeling and
simulation. Due to the complexity, software models are often assumed subjecting
to di erent nonholonomic constraints in order to simplify the models and control
algorithms. A real life autonomous bicycle faces perturbances from the road, wind,
tire deformation, slipping among other external forces. Limitations of simulations
will not always allow these to apply. All these issues make the autonomous bicycle
research very challenging.
To study the bicycle control problems a few research results from the literature
are reviewed. A nonlinear bicycle model was used to conduct control simulations.
Model based nonlinear controllers were applied to simulate the balance and path
tracking control. A PID controller is more practical to replace the non-linear controller
for the balance control. Simulation results of the di erent controllers are
compared in order to decide the proper control strategies on the hardware platform.
The controller design of the platform complies with practicality based on the hardware
con guration. Two control schemes are implemented on the test platform;
both are developed with PID algorithms. The rst scheme is a single PID control
loop in which the controller takes the roll angle feedback and balances the running
platform by means of steering. If the desired roll angle is zero the controller will try
to hold the platform at the upright position. If the desired roll angle is non-zero
the platform will be balanced at an equilibrium roll angle. A xed roll angle will
lead to a xed steering angle as the result of balance control. The second scheme
is directional control with balance consisting of two cascaded PID loops. Steering
is the only means to control balance and direction. To do so the desired roll angle
must be controlled to achieve the desired steering angle. The platform tilts to
the desired side and steering follows to the same side of the tilt; the platform can
then be lifted up by the centrifugal force and eventually balanced at an equilibrium
roll angle. The direction can be controlled using a controlled roll angle. Many implementation
issues have to be dealt with in order for the control algorithm to be
functional. Dynamic roll angle measurement is implemented with complementary
internal sensors (accelerometer and gyroscope). Directional information is obtained
through a yaw rate gyroscope which operates on the principle of resonance. To monitor
the speed of the platform, a rotational sensor was formed by using a hard drive
stepper motor attached to the axis of the vehicle's driving motor. The optoelectronic
circuit plays the vital role to ensure the system functionality by isolating the
electromagnetic noise from the motors. Finally, in order to collect runtime data, the
wireless communication is implemented through Bluetooth/RS232 serial interface.
The data is then plotted and analyzed with Matlab. Controller gains are tuned
through numerous road tests.
Field test results show that the research has successfully achieved the goal of
testing the low level control of autonomous bicycle. The developed algorithms are
able to balance the platform on semi-smooth surfaces. / UOIT
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OOSHDU.10155/143 |
| Date | 01 March 2011 |
| Creators | Wang, Xinqi |
| Contributors | Eklund, Mikael |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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