Modelling and adaptive robust control of an unmanned electric Underactuated bicycle

In response to the imperative to achieve net-zero emissions and effectively combat environmental concerns, there is a growing consensus on the need to prioritize ebicycles over conventional automobiles. E-bicycles present a sustainable and energy-efficient mode of transportation, substantially reducing emissions and energy consumption. Encouraging e-bicycle usage for short trips and urban commuting can significantly diminish the collective carbon footprint associated with personal travel. By actively promoting e-bicycle adoption and developing supportive infrastructure, we can actively steer our transportation systems towards a future where e-bicycles take center stage, contributing to our efforts to attain net- zero emissions and foster a cleaner and more sustainable environment. This project is cantered on the modelling and adaptive robust control of unmanned electric underactuated bicycles, navigating through uncertain environments. This project, while challenging, represents an innovative and exciting endeavour.

This research will focus on the following key tasks:

1) System Modelling: create a comprehensive dynamic model of the unmanned electric bicycle, covering aspects such as bicycle kinematics and dynamics, accounting for its underactuated characteristics, mass distribution, inertial properties, motor and battery attributes, wheel and tire dynamics, and environmental factors like friction and wind.

2) Controller Design: propose and implement adaptive control algorithms capable of accommodating variations in system parameters and external disturbances. Adaptive control mechanisms will enable real-time adjustments based on environmental changes. This will include algorithms for estimating dynamic parameters, like variations in mass distribution, tire properties, and friction coefficients. Moreover, we will develop robust control strategies to ensure system stability and performance in the face of uncertainties, allowing the adaptive robust control system to adapt to changes in the system's behaviour, such as parameter variations, external disturbances, and unexpected events.

3) Stability and Performance Analysis: The project will involve an in-depth analysis of control system stability to guarantee the unmanned bicycle's stability across various conditions. We will also assess performance metrics, focusing on tracking accuracy and the system's ability to reject disturbances.

4) Simulation and Experimental Testing: construct a simulated environment to rigorously test the control algorithms and evaluate their performance in diverse scenarios. Additionally, we will implement the control algorithms on embedded hardware for real-time control of the unmanned bicycle. Systematic testing will be conducted on a physical prototype, including controlled experiments and real-world testing.

5) Documentation and Reporting: Throughout the project, we will maintain comprehensive documentation, including model equations, control algorithms, and testing results. We will prepare reports and necessary documentation for stakeholders and regulatory authorities.

Academic qualifications

A first-class honours degree, or a distinction at master level, or equivalent achievements in Computing, or Computing Engineering, or Electronics and electrical engineering, or Robotics, or Control Engineering, or Mathematics.

English language requirement

If your first language is not English, comply with the University requirements for research degree programmes in terms of English language.

Application process

Prospective applicants are encouraged to contact the supervisor, Dr. Hongnian Yu ([Email Address Removed]) to discuss the content of the project and the fit with their qualifications and skills before preparing an application. 

The application must include: 

Research project outline of 2 pages (list of references excluded). The outline may provide details about

• Background and motivation, explaining the importance of the project, should be supported also by relevant literature. You can also discuss the applications you expect for the project results.
• Research questions or
• Methodology: types of data to be used, approach to data collection, and data analysis methods.
• List of references

The outline must be created solely by the applicant. Supervisors can only offer general discussions about the project idea without providing any additional support.

• Statement no longer than 1 page describing your motivations and fit with the project.
• Recent and complete curriculum vitae. The curriculum must include a declaration regarding the English language qualifications of the candidate.
• Supporting documents will have to be submitted by successful candidates.
• Two academic references (but if you have been out of education for more than three years, you may submit one academic and one professional reference), on the form can be downloaded here.

Applications can be submitted here.

Download a copy of the project details here.